variables

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

370 rows where datasetId = 6633 sorted by id descending

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id ▲ name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
954464 Patent applications granted per 1 million people - Field: Transportation granted applications per 1 million people   2024-07-25 13:04:21 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_per_mil__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_per_mil__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Patent applications granted per 1 million people",
    "originalShortName": "num_patent_granted_per_mil"
}
 2 major           Yearly total number of patents granted per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 0505b489a2c963e1387f15b02d3829c1 32a5329034b8b7d37e5c5b94eacc9151
954463 Patent applications per 1 million people - Field: Transportation applications per 1 million people   2024-07-25 13:04:21 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_per_mil__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_per_mil__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Patent applications per 1 million people",
    "originalShortName": "num_patent_applications_per_mil"
}
 2 major           Yearly total number of patent applications per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 5a4c577480a5262f01abcedd1c323c17 c2c215d7303b633af1d33fc2f4aaf5dc
954462 Total patent applications granted - Field: Transportation granted applications   2024-07-25 13:04:21 2024-07-30 06:18:30     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_summary__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_summary__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Total patent applications granted",
    "originalShortName": "num_patent_granted_summary"
}
 2             Total number of patents granted between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 a144a2cf15a79ea6c4b31080e01f36c4 71a982828d7c8d5915657d30152169c9
954461 Total patent applications - Field: Transportation applications   2024-07-25 13:04:20 2024-07-30 06:18:30     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_summary__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_summary__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Total patent applications",
    "originalShortName": "num_patent_applications_summary"
}
 2             Total number of patent applications between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 00b9239206c702da39b19f1b88c7f516 3ff5eb442c377d3cb1d5e269211204ea
954460 Patent applications granted - Field: Transportation granted applications   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Patent applications granted",
    "originalShortName": "num_patent_granted"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 9fe4008b113c6ff1269c806ceb7d85ce 342ddaeb9676147318150a9653463aa6
954459 Patent applications - Field: Transportation applications   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Patent applications",
    "originalShortName": "num_patent_applications"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 95d7216fcae200efd243a9e6443b52bc 142c951b1cd3b2669852a2dae359e4df
954458 Total estimated investment - Field: Transportation constant 2021 US$   2024-07-25 13:04:20 2024-07-30 06:18:30     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 9e735203bd41702b0383aa77c8811a44 ed281cd8220187ab2f8e8f3d56861267
954457 Total disclosed investment - Field: Transportation constant 2021 US$   2024-07-25 13:04:20 2024-07-30 06:18:30     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 a52d7b6ba2c83bfb224e5574b2c16337 087fb13cc29bf8de772fc31664a68244
954456 Estimated investment - Field: Transportation constant 2021 US$   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 a3aa74278f99e069f2583e7968d202c4 b82f2253f25dba31bd4afcbb0270a83b
954455 Disclosed investment - Field: Transportation constant 2021 US$   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_transportation grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_transportation 
{
    "filters": [
        {
            "name": "field",
            "value": "Transportation"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 72aa172fd9daf77883122e7aca116a56 75e6c395f3676dce270cb51a6a721526
954454 Citations per article, 2013-2023 - Field: Theoretical computer science citations per article   2024-07-25 13:04:20 2024-07-30 06:18:30     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations per article",
    "numDecimalPlaces": 0
}
 0     citations_per_article__field_theoretical_computer_science grapher/artificial_intelligence/2024-07-16/cset/cset#citations_per_article__field_theoretical_computer_science 
{
    "filters": [
        {
            "name": "field",
            "value": "Theoretical computer science"
        }
    ],
    "originalName": "Citations per article, 2013-2023",
    "originalShortName": "citations_per_article"
}
 2             The total number of citations per article in the AI field between 2013-2023. Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
 Countries that have published fewer than 1,000 articles on AI between 2010-2023 are excluded to prevent distortion in the "citations per publication" metric, which can occur when dividing by a small sample size.     
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 float 
[]
 eabef5a01df58ba89c195d0e57d0f0c0 f0f04836ef64045f0f45f8f5ab88231e
954453 Number of articles per 1 million people - Field: Theoretical computer science articles per 1 million people   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_articles_per_mil__field_theoretical_computer_science grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_per_mil__field_theoretical_computer_science 
{
    "filters": [
        {
            "name": "field",
            "value": "Theoretical computer science"
        }
    ],
    "originalName": "Number of articles per 1 million people",
    "originalShortName": "num_articles_per_mil"
}
 2 major           Yearly number of articles published in AI fields per 1 million people. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "Data for 2022-2023 is incomplete."
}
 float 
[]
 6d7883f1cab8371964f25f3cab820d85 c5ef829c7f2184ed1717d4ebf78396d4
954452 Total number of citations - Field: Theoretical computer science citations   2024-07-25 13:04:20 2024-07-30 06:18:30     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations_summary__field_theoretical_computer_science grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations_summary__field_theoretical_computer_science 
{
    "filters": [
        {
            "name": "field",
            "value": "Theoretical computer science"
        }
    ],
    "originalName": "Total number of citations",
    "originalShortName": "num_citations_summary"
}
 2             Total number of citations in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 c5436d2ce35fddab1d9b249824114b58 5d9e672bb923c7b986bd65603dd7cd8d
954451 Total number of articles - Field: Theoretical computer science articles   2024-07-25 13:04:20 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles_summary__field_theoretical_computer_science grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_summary__field_theoretical_computer_science 
{
    "filters": [
        {
            "name": "field",
            "value": "Theoretical computer science"
        }
    ],
    "originalName": "Total number of articles",
    "originalShortName": "num_articles_summary"
}
 2             Total number of articles in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 fd8d43c1f7575ffc56d79212305f86d9 6c53d27f4a6aa66ec4d005334b9a2a47
954450 Number of citations - Field: Theoretical computer science citations   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations__field_theoretical_computer_science grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations__field_theoretical_computer_science 
{
    "filters": [
        {
            "name": "field",
            "value": "Theoretical computer science"
        }
    ],
    "originalName": "Number of citations",
    "originalShortName": "num_citations"
}
 2             Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 2dc9f8dd8476d424f3bb7619b870861b 5b5dd69ee0ed55351226a77d6362dd4d
954449 Number of articles - Field: Theoretical computer science articles   2024-07-25 13:04:20 2024-07-30 06:18:30     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles__field_theoretical_computer_science grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles__field_theoretical_computer_science 
{
    "filters": [
        {
            "name": "field",
            "value": "Theoretical computer science"
        }
    ],
    "originalName": "Number of articles",
    "originalShortName": "num_articles"
}
 2             English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 50e86eb78e7317ca1c35756e2bfac2b3 ce1324a600ce9a39582c11de4ffb64c2
954448 Patent applications granted per 1 million people - Field: Telecommunications granted applications per 1 million people   2024-07-25 13:04:19 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_per_mil__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_per_mil__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Patent applications granted per 1 million people",
    "originalShortName": "num_patent_granted_per_mil"
}
 2 major           Yearly total number of patents granted per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 4d07178ab48eb43068a5beeaee67c4ca b63b218759ee1abf0e3545af9c6142cf
954447 Patent applications per 1 million people - Field: Telecommunications applications per 1 million people   2024-07-25 13:04:19 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_per_mil__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_per_mil__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Patent applications per 1 million people",
    "originalShortName": "num_patent_applications_per_mil"
}
 2 major           Yearly total number of patent applications per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 0c8ee9ef0d44b63613266addfaeb215a d69319711f730bafe9b2c3f0e4e223fb
954446 Total patent applications granted - Field: Telecommunications granted applications   2024-07-25 13:04:19 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_summary__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_summary__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Total patent applications granted",
    "originalShortName": "num_patent_granted_summary"
}
 2             Total number of patents granted between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 9716ed9eeb89d57923d6ec635c822603 59a5193323f10185b8b984bba5745122
954445 Patent applications granted - Field: Telecommunications granted applications   2024-07-25 13:04:19 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Patent applications granted",
    "originalShortName": "num_patent_granted"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 9f795b3cb50243ac33fbf21714003f6e 5e4912ec947d415528584be0124ac7a1
954444 Patent applications - Field: Telecommunications applications   2024-07-25 13:04:19 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Patent applications",
    "originalShortName": "num_patent_applications"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 97d6fc324cf17081a201c9a7c1a99b03 3c8c913b54341c6fdcb57f9646b212dd
954443 Total patent applications - Field: Telecommunications applications   2024-07-25 13:04:19 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_summary__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_summary__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Total patent applications",
    "originalShortName": "num_patent_applications_summary"
}
 2             Total number of patent applications between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 a68345cdc3a0e221bea76f0ce5668545 d177f32258f2b067be12d98caf3dad10
954442 Total estimated investment - Field: Telecommunications constant 2021 US$   2024-07-25 13:04:19 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 2b25b8d41b45f8ab09c903a758bf04a4 5b7e4592d6499f54ec48fe9f17d31b00
954441 Total disclosed investment - Field: Telecommunications constant 2021 US$   2024-07-25 13:04:19 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 7f7f8a1e5cb7f7f4e0bb0aeda59d63ce 9252124494d0cdbe2195873d33b140b7
954440 Estimated investment - Field: Telecommunications constant 2021 US$   2024-07-25 13:04:19 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 c9ecddae93c5183104a1f15ea7cb5be0 82db544ffae960f72069f30b5e954294
954439 Disclosed investment - Field: Telecommunications constant 2021 US$   2024-07-25 13:04:19 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_telecommunications grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_telecommunications 
{
    "filters": [
        {
            "name": "field",
            "value": "Telecommunications"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 85efa708e44292f136a1a13f3c626873 d347c69ee3248255cb141047996aa1f8
954438 Total estimated investment - Field: Sports constant 2021 US$   2024-07-25 13:04:19 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_sports grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_sports 
{
    "filters": [
        {
            "name": "field",
            "value": "Sports"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 8a3e29bdd3d4755643eb493d4de3585f 3fce09325593ad61fa49764a2dcd057e
954437 Total disclosed investment - Field: Sports constant 2021 US$   2024-07-25 13:04:18 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_sports grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_sports 
{
    "filters": [
        {
            "name": "field",
            "value": "Sports"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 9a937b6d59e94c81935f00d1ad6e7841 ccb38d69683fe0df3ad5ba45c96b22c9
954436 Estimated investment - Field: Sports constant 2021 US$   2024-07-25 13:04:18 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_sports grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_sports 
{
    "filters": [
        {
            "name": "field",
            "value": "Sports"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 8f48dacb6e94a048b92fd959c8b666c8 7223397c5cf8aab44a20b176db468b52
954435 Disclosed investment - Field: Sports constant 2021 US$   2024-07-25 13:04:18 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_sports grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_sports 
{
    "filters": [
        {
            "name": "field",
            "value": "Sports"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 86a9d423f827f7f6eca625b70cd7203a c74b127fc3cef8919d81678c041b0104
954434 Citations per article, 2013-2023 - Field: Speech recognition citations per article   2024-07-25 13:04:18 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations per article",
    "numDecimalPlaces": 0
}
 0     citations_per_article__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#citations_per_article__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Citations per article, 2013-2023",
    "originalShortName": "citations_per_article"
}
 2             The total number of citations per article in the AI field between 2013-2023. Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
 Countries that have published fewer than 1,000 articles on AI between 2010-2023 are excluded to prevent distortion in the "citations per publication" metric, which can occur when dividing by a small sample size.     
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 float 
[]
 705d0b1fbba9019216a874d1ad69330c 699d2f7e5936ef6d1b329ffff6f6baa1
954433 Number of articles per 1 million people - Field: Speech recognition articles per 1 million people   2024-07-25 13:04:18 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_articles_per_mil__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_per_mil__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Number of articles per 1 million people",
    "originalShortName": "num_articles_per_mil"
}
 2 major           Yearly number of articles published in AI fields per 1 million people. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "Data for 2022-2023 is incomplete."
}
 float 
[]
 23db7706138eb56ffa6513166b980a55 520750a18f21a144f14c000101242e19
954432 Total number of citations - Field: Speech recognition citations   2024-07-25 13:04:18 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations_summary__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations_summary__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Total number of citations",
    "originalShortName": "num_citations_summary"
}
 2             Total number of citations in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 6a31064d6bb83524c4d9adaad2c1c17b 8083583ae8233f0ec6c824de1701433d
954431 Total number of articles - Field: Speech recognition articles   2024-07-25 13:04:18 2024-07-30 06:18:29     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles_summary__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_summary__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Total number of articles",
    "originalShortName": "num_articles_summary"
}
 2             Total number of articles in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 569e060f31ab028f9dbadae936e3731e 06b85a83e1794d68d47ff5fae9272cbf
954430 Number of citations - Field: Speech recognition citations   2024-07-25 13:04:18 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Number of citations",
    "originalShortName": "num_citations"
}
 2             Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 617b41921b679bb505889df75694e6e3 3dcfb2513ef7b8da677e9f7655a2e55c
954429 Number of articles - Field: Speech recognition articles   2024-07-25 13:04:18 2024-07-30 06:18:29     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Number of articles",
    "originalShortName": "num_articles"
}
 2             English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 3ca731269521bf116b3514b1b547558e 4dc07c989e8e42f5c4eb61bb1d4c8524
954428 Total estimated investment - Field: Speech recognition constant 2021 US$   2024-07-25 13:04:18 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 11d2f545a4e330c341321620f7c7edf4 e14facbd6995dcc568d03c924f8133e3
954427 Total disclosed investment - Field: Speech recognition constant 2021 US$   2024-07-25 13:04:18 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 904e79f1e3e1fcad11ce9d283a5bce96 c141d694547d9563e289609c5d452dfc
954426 Estimated investment - Field: Speech recognition constant 2021 US$   2024-07-25 13:04:18 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 bde18b150fc03ff7a7fb318ea887e1b4 2e14aa30becd7b561ec6ce0640662b37
954425 Disclosed investment - Field: Speech recognition constant 2021 US$   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_speech_recognition grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_speech_recognition 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech recognition"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 8c05245b42d15bdfd6880249ff9dc993 4c608b8ab67c51c5205bb522f9b4ebe4
954424 Patent applications granted per 1 million people - Field: Speech processing granted applications per 1 million people   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_per_mil__field_speech_processing grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_per_mil__field_speech_processing 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech processing"
        }
    ],
    "originalName": "Patent applications granted per 1 million people",
    "originalShortName": "num_patent_granted_per_mil"
}
 2 major           Yearly total number of patents granted per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 200149a4a5c2ab454a1a7712030f30ea f1ee09ef20b2c3f9c82cdc3f3496cc15
954423 Patent applications per 1 million people - Field: Speech processing applications per 1 million people   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_per_mil__field_speech_processing grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_per_mil__field_speech_processing 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech processing"
        }
    ],
    "originalName": "Patent applications per 1 million people",
    "originalShortName": "num_patent_applications_per_mil"
}
 2 major           Yearly total number of patent applications per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 3fa89a2da86f7b5f7ff6de578678f4c5 a3ad02878c5d085d600e1ac256ec03af
954422 Total patent applications granted - Field: Speech processing granted applications   2024-07-25 13:04:17 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_summary__field_speech_processing grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_summary__field_speech_processing 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech processing"
        }
    ],
    "originalName": "Total patent applications granted",
    "originalShortName": "num_patent_granted_summary"
}
 2             Total number of patents granted between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 762b47035f110be6725ab6e9e7d00ff2 f8614c8599c4bb98a5cd038293acb4ff
954421 Total patent applications - Field: Speech processing applications   2024-07-25 13:04:17 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_summary__field_speech_processing grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_summary__field_speech_processing 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech processing"
        }
    ],
    "originalName": "Total patent applications",
    "originalShortName": "num_patent_applications_summary"
}
 2             Total number of patent applications between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 4b95de07fc3008697d2e6fe9cc22799a ecca9f3bbe273e8673f02da42374e043
954420 Patent applications granted - Field: Speech processing granted applications   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted__field_speech_processing grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted__field_speech_processing 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech processing"
        }
    ],
    "originalName": "Patent applications granted",
    "originalShortName": "num_patent_granted"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 b15fae820c63fdee68662f72f23ca5ed 3ebd3ba8641c2ac5d906eaca7b736974
954419 Patent applications - Field: Speech processing applications   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications__field_speech_processing grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications__field_speech_processing 
{
    "filters": [
        {
            "name": "field",
            "value": "Speech processing"
        }
    ],
    "originalName": "Patent applications",
    "originalShortName": "num_patent_applications"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 ff901cd6844f7924d60b16b00b4e6570 66aba614b187bbf5998f3035ad2c5abd
954418 Total estimated investment - Field: Software constant 2021 US$   2024-07-25 13:04:17 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_software grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_software 
{
    "filters": [
        {
            "name": "field",
            "value": "Software"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 1fe93210578d64cc4c626fee53cb693a 6699d4b2ab0f6fe880804cdf77a9e537
954417 Total disclosed investment - Field: Software constant 2021 US$   2024-07-25 13:04:17 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_software grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_software 
{
    "filters": [
        {
            "name": "field",
            "value": "Software"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 d935b3c93d95d5a71da4e1be2787e309 8c2c616d028432fbd69cf25e2f0e5d57
954416 Estimated investment - Field: Software constant 2021 US$   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_software grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_software 
{
    "filters": [
        {
            "name": "field",
            "value": "Software"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 0292fdf12985eb0d522b6eae98fff46c 93d5fbaf46d895ae710f2efee6458861
954415 Disclosed investment - Field: Software constant 2021 US$   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_software grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_software 
{
    "filters": [
        {
            "name": "field",
            "value": "Software"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 20e3d335eeb7492d1de5d48ec08827e2 6d6bf5bf64045e68973b2635892888f2
954414 Citations per article, 2013-2023 - Field: Simulation citations per article   2024-07-25 13:04:17 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations per article",
    "numDecimalPlaces": 0
}
 0     citations_per_article__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#citations_per_article__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Citations per article, 2013-2023",
    "originalShortName": "citations_per_article"
}
 2             The total number of citations per article in the AI field between 2013-2023. Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
 Countries that have published fewer than 1,000 articles on AI between 2010-2023 are excluded to prevent distortion in the "citations per publication" metric, which can occur when dividing by a small sample size.     
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 float 
[]
 b5e0fb1666d43d99b3b9f044b7f4c6f7 97260da48a93cf3918700142f8b8bcfe
954413 Number of articles per 1 million people - Field: Simulation articles per 1 million people   2024-07-25 13:04:17 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_articles_per_mil__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_per_mil__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Number of articles per 1 million people",
    "originalShortName": "num_articles_per_mil"
}
 2 major           Yearly number of articles published in AI fields per 1 million people. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "Data for 2022-2023 is incomplete."
}
 float 
[]
 1a1beceaa5ec49d360b3c6062bcf1156 e5c9e91b9fbd2437b855dbeef96f9353
954412 Total number of citations - Field: Simulation citations   2024-07-25 13:04:17 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations_summary__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations_summary__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Total number of citations",
    "originalShortName": "num_citations_summary"
}
 2             Total number of citations in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 0d7e77d939c7e4f964a2b56f2a87809a c419209fde5ceaeab4961de41837ad20
954411 Total number of articles - Field: Simulation articles   2024-07-25 13:04:16 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles_summary__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_summary__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Total number of articles",
    "originalShortName": "num_articles_summary"
}
 2             Total number of articles in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 58863155b795bd8717df56f53f3c73de 7ca7f4c0de50df835256a7244e4e0fb3
954410 Number of citations - Field: Simulation citations   2024-07-25 13:04:16 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Number of citations",
    "originalShortName": "num_citations"
}
 2             Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 9d21bbc53d561f1a58897d9c90580ee7 ca9448ad4db53e4526a4c0619d306e4b
954409 Number of articles - Field: Simulation articles   2024-07-25 13:04:16 2024-07-30 06:18:28     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Number of articles",
    "originalShortName": "num_articles"
}
 2             English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 7907f209c472e62d3b4ca4d8a4d539a9 b74ada07c4187d6e821a185f17496d69
954408 Total estimated investment - Field: Simulation constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 a2d5ee8af70fa83d41975d812ffa4b44 6205bbdd3c730de0233468a59e3ad120
954407 Total disclosed investment - Field: Simulation constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:28     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 e796e60c87c9120ca6af1aea8e4dfe6d 235bfce78cf3186556ab038594825ffd
954406 Estimated investment - Field: Simulation constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 4b541711c777248734c16473f0e5147d 09f4b56cf78174eb801b7522db9a8fc5
954405 Disclosed investment - Field: Simulation constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_simulation grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_simulation 
{
    "filters": [
        {
            "name": "field",
            "value": "Simulation"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 088c5a4f3c0410d1231cb5bcb6d7e611 63f40a97f67a79d74674045215ae0bfc
954404 Total estimated investment - Field: Semiconductor constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_semiconductor grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_semiconductor 
{
    "filters": [
        {
            "name": "field",
            "value": "Semiconductor"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 ca8d594839712ca5e1bafa6e167c35c2 13348f662501c20b9bea744c4582ec9d
954403 Total disclosed investment - Field: Semiconductor constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_semiconductor grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_semiconductor 
{
    "filters": [
        {
            "name": "field",
            "value": "Semiconductor"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 dca3adbca21489f55966fc6c69a3a07d ae717cc42238938ae3cfc01734c6d55c
954402 Estimated investment - Field: Semiconductor constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_semiconductor grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_semiconductor 
{
    "filters": [
        {
            "name": "field",
            "value": "Semiconductor"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 35bc310049d36c19a67e6883f27e4333 bd76529d4261e5201b9556de974ab4fa
954401 Disclosed investment - Field: Semiconductor constant 2021 US$   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_semiconductor grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_semiconductor 
{
    "filters": [
        {
            "name": "field",
            "value": "Semiconductor"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 bf9a16d284ea790bf0b4ea0245e8f0c7 3b4ec2f26315b0e8e51dfbfc3f929527
954400 Patent applications granted per 1 million people - Field: Security granted applications per 1 million people   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_per_mil__field_security grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_per_mil__field_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Security"
        }
    ],
    "originalName": "Patent applications granted per 1 million people",
    "originalShortName": "num_patent_granted_per_mil"
}
 2 major           Yearly total number of patents granted per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 2a77dce78f0edd572cdfc38c17422049 63efb076a19999cee3e27035f81ad290
954399 Patent applications per 1 million people - Field: Security applications per 1 million people   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_per_mil__field_security grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_per_mil__field_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Security"
        }
    ],
    "originalName": "Patent applications per 1 million people",
    "originalShortName": "num_patent_applications_per_mil"
}
 2 major           Yearly total number of patent applications per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 71473c8e7b84657bd0df6cb3b0769f31 acae53d05a7e9e8309035e420f25ed86
954398 Total patent applications granted - Field: Security granted applications   2024-07-25 13:04:16 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_summary__field_security grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_summary__field_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Security"
        }
    ],
    "originalName": "Total patent applications granted",
    "originalShortName": "num_patent_granted_summary"
}
 2             Total number of patents granted between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 e82f80a7f80c16fb554606f714b2be7e c975ff987f59805af59b79dee3712e82
954397 Total patent applications - Field: Security applications   2024-07-25 13:04:16 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_summary__field_security grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_summary__field_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Security"
        }
    ],
    "originalName": "Total patent applications",
    "originalShortName": "num_patent_applications_summary"
}
 2             Total number of patent applications between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 2b461c3f487548cd948d865fc4d55611 3615f5e419a94d3b01a61d8e678a249a
954396 Patent applications granted - Field: Security granted applications   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted__field_security grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted__field_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Security"
        }
    ],
    "originalName": "Patent applications granted",
    "originalShortName": "num_patent_granted"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 f041e062c7078ffb14676e1f8ea1e438 b1ee9386654f3c6cef1a3a4e5f139df6
954395 Patent applications - Field: Security applications   2024-07-25 13:04:16 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications__field_security grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications__field_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Security"
        }
    ],
    "originalName": "Patent applications",
    "originalShortName": "num_patent_applications"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 64070eac17644ad4da80a22bc277e1c6 b3c5c137d0b1bffe500c3af3600252b3
954394 Total estimated investment - Field: Sales, retail, commerce, marketing constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_sales__retail__commerce__marketing grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_sales__retail__commerce__marketing 
{
    "filters": [
        {
            "name": "field",
            "value": "Sales, retail, commerce, marketing"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 beca30658e64848177d631a0b2e1721c a81709d41e12944d2379ec836e4864f1
954393 Total disclosed investment - Field: Sales, retail, commerce, marketing constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_sales__retail__commerce__marketing grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_sales__retail__commerce__marketing 
{
    "filters": [
        {
            "name": "field",
            "value": "Sales, retail, commerce, marketing"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 38ef8df4434286736e614e92009c73bd 680d8161ce2e368cdc76ff5f4338c20b
954392 Estimated investment - Field: Sales, retail, commerce, marketing constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_sales__retail__commerce__marketing grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_sales__retail__commerce__marketing 
{
    "filters": [
        {
            "name": "field",
            "value": "Sales, retail, commerce, marketing"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 f5b3a013994317368bbc4c48ea83a312 bfc5d9d866efcb60e334fb6a12b5b45d
954391 Disclosed investment - Field: Sales, retail, commerce, marketing constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_sales__retail__commerce__marketing grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_sales__retail__commerce__marketing 
{
    "filters": [
        {
            "name": "field",
            "value": "Sales, retail, commerce, marketing"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 f48bfc665eab7d92e873af1556fe9039 adbcd8665c407cb5c482dba5be8204e0
954390 Total estimated investment - Field: Robotics constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_robotics grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_robotics 
{
    "filters": [
        {
            "name": "field",
            "value": "Robotics"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 e4b1d263f307ded2131580bec6c9a458 94a6fba130c870b0021bc8362e439836
954389 Total disclosed investment - Field: Robotics constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_robotics grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_robotics 
{
    "filters": [
        {
            "name": "field",
            "value": "Robotics"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 cc3e45d48cb6d4918e99a83da26fb79c 5b014152a5961dcc70a8b579d8d4eb71
954388 Estimated investment - Field: Robotics constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_robotics grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_robotics 
{
    "filters": [
        {
            "name": "field",
            "value": "Robotics"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 57f4248bf67d1aca3740cddbff9415fb 91c0322d18bec24eb64fcc62969d3aa6
954387 Disclosed investment - Field: Robotics constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_robotics grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_robotics 
{
    "filters": [
        {
            "name": "field",
            "value": "Robotics"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 96212bb526d0952d72deb6cbf0f52533 4a4c9f32f4e16e58e42d5361ffe23fff
954386 Citations per article, 2013-2023 - Field: Real-time computing citations per article   2024-07-25 13:04:15 2024-07-30 06:18:27     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations per article",
    "numDecimalPlaces": 0
}
 0     citations_per_article__field_real_time_computing grapher/artificial_intelligence/2024-07-16/cset/cset#citations_per_article__field_real_time_computing 
{
    "filters": [
        {
            "name": "field",
            "value": "Real-time computing"
        }
    ],
    "originalName": "Citations per article, 2013-2023",
    "originalShortName": "citations_per_article"
}
 2             The total number of citations per article in the AI field between 2013-2023. Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
 Countries that have published fewer than 1,000 articles on AI between 2010-2023 are excluded to prevent distortion in the "citations per publication" metric, which can occur when dividing by a small sample size.     
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 float 
[]
 27c0cc086d317a170f00512abe5065c9 b38682f0f8a4fcb332eab94326cd04bb
954385 Number of articles per 1 million people - Field: Real-time computing articles per 1 million people   2024-07-25 13:04:15 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_articles_per_mil__field_real_time_computing grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_per_mil__field_real_time_computing 
{
    "filters": [
        {
            "name": "field",
            "value": "Real-time computing"
        }
    ],
    "originalName": "Number of articles per 1 million people",
    "originalShortName": "num_articles_per_mil"
}
 2 major           Yearly number of articles published in AI fields per 1 million people. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "Data for 2022-2023 is incomplete."
}
 float 
[]
 c5a1bd063ff142bd7721326e7c8b4954 3f9d56957482b476116bf129981e9a68
954384 Total number of citations - Field: Real-time computing citations   2024-07-25 13:04:15 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations_summary__field_real_time_computing grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations_summary__field_real_time_computing 
{
    "filters": [
        {
            "name": "field",
            "value": "Real-time computing"
        }
    ],
    "originalName": "Total number of citations",
    "originalShortName": "num_citations_summary"
}
 2             Total number of citations in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 ce0c89dc04556a3a3d41bfdfa69cca0d 8ec192487cfeb8efccb2b0dae9367e6c
954383 Total number of articles - Field: Real-time computing articles   2024-07-25 13:04:15 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles_summary__field_real_time_computing grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles_summary__field_real_time_computing 
{
    "filters": [
        {
            "name": "field",
            "value": "Real-time computing"
        }
    ],
    "originalName": "Total number of articles",
    "originalShortName": "num_articles_summary"
}
 2             Total number of articles in the AI field between 2013-2023. English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 69505d47b262b7b552730300536bff3c 20d11dccfc2cc6434dc9ce2b547ac5d5
954382 Number of citations - Field: Real-time computing citations   2024-07-25 13:04:15 2024-07-30 06:18:27     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "citations",
    "numDecimalPlaces": 0
}
 0     num_citations__field_real_time_computing grapher/artificial_intelligence/2024-07-16/cset/cset#num_citations__field_real_time_computing 
{
    "filters": [
        {
            "name": "field",
            "value": "Real-time computing"
        }
    ],
    "originalName": "Number of citations",
    "originalShortName": "num_citations"
}
 2             Citations take time to accumulate so recent years may have fewer citations, and the measure for these years may not completely reflective of their eventual total.   
[]
       
{
    "note": "The citation counts for papers published in a specific year are subject to a time lag, as papers often accrue most citations in subsequent years. Data for 2022-2023 is therefore incomplete."
}
 int 
[]
 0c1b56766b8a97b373ea680bd00a3614 997f19b8747494bb89ad1fd7b615c9ca
954381 Number of articles - Field: Real-time computing articles   2024-07-25 13:04:15 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "articles",
    "numDecimalPlaces": 0
}
 0     num_articles__field_real_time_computing grapher/artificial_intelligence/2024-07-16/cset/cset#num_articles__field_real_time_computing 
{
    "filters": [
        {
            "name": "field",
            "value": "Real-time computing"
        }
    ],
    "originalName": "Number of articles",
    "originalShortName": "num_articles"
}
 2             English- and Chinese-language scholarly publications related to the development and application of AI. This includes journal articles, conference papers, repository publications (such as arXiv), books, and theses.   
[]
       
{
    "note": "Data for 2022-2023 is incomplete."
}
 int 
[]
 abf71d03102336ebe932b8733f1914a2 8e654a2ca35b1d7c0efa8162c7640b72
954380 Total estimated investment - Field: Real estate constant 2021 US$   2024-07-25 13:04:15 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_real_estate grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_real_estate 
{
    "filters": [
        {
            "name": "field",
            "value": "Real estate"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 14b281c7c18415730dba605c95b48d10 32b5dc92f6179fec96377f6cc7e80c0f
954379 Total disclosed investment - Field: Real estate constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_real_estate grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_real_estate 
{
    "filters": [
        {
            "name": "field",
            "value": "Real estate"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 9507df5a7db6370ddf175619b4e28fd0 5a78cca3cced1543365a03539f896ec6
954378 Estimated investment - Field: Real estate constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_real_estate grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_real_estate 
{
    "filters": [
        {
            "name": "field",
            "value": "Real estate"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 cb6b86a1b8b87880a62abd700422d9e2 c4d5eeb03d9d595988dd068fe3badbb0
954377 Disclosed investment - Field: Real estate constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_real_estate grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_real_estate 
{
    "filters": [
        {
            "name": "field",
            "value": "Real estate"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 a26af7e277221aa140bca315c38d07eb 387c6e03338d020e21a2430e38d79a7f
954376 Total estimated investment - Field: Professional services constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_professional_services grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_professional_services 
{
    "filters": [
        {
            "name": "field",
            "value": "Professional services"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 fcb54afd687bfab67a6363cceff07c22 70756f6a1ce6600c0841d8f1d887b71b
954375 Total disclosed investment - Field: Professional services constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_professional_services grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_professional_services 
{
    "filters": [
        {
            "name": "field",
            "value": "Professional services"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 de7b7c213462e67e2992d1e71c7abce1 7d223c46de148d1caebc2270e2c39b84
954374 Estimated investment - Field: Professional services constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     investment_estimated__field_professional_services grapher/artificial_intelligence/2024-07-16/cset/cset#investment_estimated__field_professional_services 
{
    "filters": [
        {
            "name": "field",
            "value": "Professional services"
        }
    ],
    "originalName": "Estimated investment",
    "originalShortName": "investment_estimated"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 8391b144d827ccca7a0193fddca26c99 b8e41e3c8866f29d30f9c9b41cbec4fa
954373 Disclosed investment - Field: Professional services constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment__field_professional_services grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment__field_professional_services 
{
    "filters": [
        {
            "name": "field",
            "value": "Professional services"
        }
    ],
    "originalName": "Disclosed investment",
    "originalShortName": "disclosed_investment"
}
 2             Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 24ca3a50ad319a5531182ac539ef1ece 552c65390a93487ea6e7729bc9c68a73
954372 Patent applications granted per 1 million people - Field: Probabilistic reasoning granted applications per 1 million people   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_per_mil__field_probabilistic_reasoning grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_per_mil__field_probabilistic_reasoning 
{
    "filters": [
        {
            "name": "field",
            "value": "Probabilistic reasoning"
        }
    ],
    "originalName": "Patent applications granted per 1 million people",
    "originalShortName": "num_patent_granted_per_mil"
}
 2 major           Yearly total number of patents granted per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 46b0511361798c126f91e095fd7a0081 c8b38217c4de88f3f3dec761c97a82d1
954371 Patent applications per 1 million people - Field: Probabilistic reasoning applications per 1 million people   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications per 1 million people",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_per_mil__field_probabilistic_reasoning grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_per_mil__field_probabilistic_reasoning 
{
    "filters": [
        {
            "name": "field",
            "value": "Probabilistic reasoning"
        }
    ],
    "originalName": "Patent applications per 1 million people",
    "originalShortName": "num_patent_applications_per_mil"
}
 2 major           Yearly total number of patent applications per 1 million people. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
   
[
    {
        "url": "https://docs.google.com/document/d/1-RmthhS2EPMK_HIpnPctcXpB0n7ADSWnXa5Hb3PxNq4/edit?usp=sharing",
        "name": "Creative Commons BY 4.0"
    }
]
   
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 float 
[]
 4557f5f180eb0559c981a44148a91190 2d297dab146296f735287bf34f49beea
954370 Total patent applications granted - Field: Probabilistic reasoning granted applications   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted_summary__field_probabilistic_reasoning grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted_summary__field_probabilistic_reasoning 
{
    "filters": [
        {
            "name": "field",
            "value": "Probabilistic reasoning"
        }
    ],
    "originalName": "Total patent applications granted",
    "originalShortName": "num_patent_granted_summary"
}
 2             Total number of patents granted between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 cae3b7d4a69cee48b2c893fbf97b10e1 05ebfbfedabba25af2108cdf8b9958b2
954369 Total patent applications - Field: Probabilistic reasoning applications   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications_summary__field_probabilistic_reasoning grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications_summary__field_probabilistic_reasoning 
{
    "filters": [
        {
            "name": "field",
            "value": "Probabilistic reasoning"
        }
    ],
    "originalName": "Total patent applications",
    "originalShortName": "num_patent_applications_summary"
}
 2             Total number of patent applications between 2013-2023. Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 8c26acee432b6251ffe67624f3b5893a 69aaaca4341e6ec04bf62bb06ed0819e
954368 Patent applications granted - Field: Probabilistic reasoning granted applications   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "granted applications",
    "numDecimalPlaces": 0
}
 0     num_patent_granted__field_probabilistic_reasoning grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_granted__field_probabilistic_reasoning 
{
    "filters": [
        {
            "name": "field",
            "value": "Probabilistic reasoning"
        }
    ],
    "originalName": "Patent applications granted",
    "originalShortName": "num_patent_granted"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 ae39e2a9a849dafcbcad0caa28cd9aec 10b5a1d188b31e9b733486bc73d7ffc9
954367 Patent applications - Field: Probabilistic reasoning applications   2024-07-25 13:04:14 2024-07-30 06:18:26     2013-2023 Country Activity Tracker: Artificial Intelligence 6633     
{
    "unit": "applications",
    "numDecimalPlaces": 0
}
 0     num_patent_applications__field_probabilistic_reasoning grapher/artificial_intelligence/2024-07-16/cset/cset#num_patent_applications__field_probabilistic_reasoning 
{
    "filters": [
        {
            "name": "field",
            "value": "Probabilistic reasoning"
        }
    ],
    "originalName": "Patent applications",
    "originalShortName": "num_patent_applications"
}
 2             Patents related to artificial intelligence first submitted in the selected country's patent office. Subsequent granting of that patent could be by any country's patent office.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Bermuda, Armenia, Belarus, Georgia, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Iceland, Albania, Andorra, Bosnia and Herzegovina, Malta, Montenegro, San Marino, North Macedonia, Liechtenstein, Monaco, Vatican City, Guernsey, Afghanistan, Kyrgyzstan, Bahrain, Laos, Bangladesh, Lebanon, Bhutan, Maldives, Cambodia, Syria, Tajikistan, Cyprus, Mongolia, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Pakistan, Palestine, Iraq, United Arab Emirates, Uzbekistan, Kazakhstan, Qatar, Vietnam, Yemen, Kuwait, Algeria, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Nigeria, Botswana, Gambia, Rwanda, Burkina Faso, Ghana, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Senegal, Guinea-Bissau, Seychelles, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Madagascar, Sudan, C\u00f4te d'Ivoire, Malawi, Togo, Mali, Djibouti, Mauritania, Uganda, Egypt, Mauritius, Tanzania, Zambia, Eritrea, Mozambique, Zimbabwe, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Dominican Republic, Bahamas, Ecuador, Paraguay, Barbados, Saint Vincent and the Grenadines, El Salvador, Belize, Grenada, Saint Kitts and Nevis, Guatemala, Guyana, Haiti, Honduras, Trinidad and Tobago, Jamaica, Venezuela, Puerto Rico, Cayman Islands (the), Turks and Caicos Islands, Saint Lucia, and Dominica."
]
       
{
    "note": "According to calculations by CSET, the median time for a patent to be granted is 826 days from its initial filing date, while the average time is 860 days.  Data for 2021-2023 is incomplete."
}
 int 
[]
 a713fd6104e3d0427d63159d65a50df4 6f325c2fb100473382ca26c034958c71
954366 Total estimated investment - Field: Privacy and security constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     estimated_investment_summary__field_privacy_and_security grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_privacy_and_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Privacy and security"
        }
    ],
    "originalName": "Total estimated investment",
    "originalShortName": "estimated_investment_summary"
}
 2             Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 3a05dcf79f1844f5ce4477380f082609 2aaba7e8276550fbbe43e5d8ddc5b150
954365 Total disclosed investment - Field: Privacy and security constant 2021 US$   2024-07-25 13:04:14 2024-07-30 06:18:26     2023-2023 Country Activity Tracker: Artificial Intelligence 6633   $ 
{
    "unit": "constant 2021 US$",
    "shortUnit": "$",
    "numDecimalPlaces": 0
}
 0     disclosed_investment_summary__field_privacy_and_security grapher/artificial_intelligence/2024-07-16/cset/cset#disclosed_investment_summary__field_privacy_and_security 
{
    "filters": [
        {
            "name": "field",
            "value": "Privacy and security"
        }
    ],
    "originalName": "Total disclosed investment",
    "originalShortName": "disclosed_investment_summary"
}
 2             Total disclosed investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation.   
[
    "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica."
]
 - Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased.     
{
    "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete."
}
 int 
[]
 8e869527235f14eb4250c3712c5b9525 973609a6e73ddf0f49758c6ce891af95

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CREATE UNIQUE INDEX "idx_catalogPath" ON "variables" ("catalogPath");
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CREATE UNIQUE INDEX "variables_code_fk_dst_id_7bde8c2a_uniq" ON "variables" ("code", "datasetId");
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