Invention Indicators: Protecting Useful Ideas

Contributors to U.S. Patent Activity

USPTO patent records provide industry, technology areas, and geographical inventor information for all patents registered in the United States, including patents granted to individuals and foreign entities. Most patent topics in this report cover only inventions protected by utility patents. Design patents are included in this report in the coverage of patenting by gender; plant patents were last covered in Science and Engineering Indicators 2020 (see Indicators 2020 report “Invention, Knowledge Transfer, and Innovation”). More information on the patent data used in this report is available in the Technical Appendix provided with this report, and detailed methodological information is provided in Science-Metrix (2024).

The USPTO awarded 325,000 utility patents in 2022, of which 152,000 (47%) were assigned to domestic owners (Table SINV-1). Obtaining and defending a patent incurs significant costs; among U.S. assignees (the U.S. entities to whom inventors assign the rights of ownership), private owners—which are primarily businesses—receive by far the most patents (86%), while individual filers and those in academia and government account for much smaller shares (Figure INV-1). In the wake of the global pandemic, the total number of USPTO utility patents awarded annually to U.S. owners has declined since 2019, when 179,000 were granted. Patents assigned to U.S. businesses declined 15% between 2019 and 2022, in contrast to a general upward trend from 2000 to 2019 (Table SINV-1).

USPTO utility patents granted to owners, by nationality and U.S. sector: 2002–22
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USPTO utility patents granted to owners, by nationality and U.S. sector: 2002–22

(Number)
Year Foreign U.S. business U.S. government U.S. individual U.S. academic
2002 77,832 70,286 1,122 14,116 3,496
2003 79,037 71,414 1,078 13,535 3,497
2004 78,084 69,385 1,019 12,173 3,261
2005 67,615 61,721 844 10,473 2,876
2006 82,239 74,605 1,008 11,996 3,518
2007 76,192 66,545 946 10,034 3,213
2008 78,216 66,128 905 9,197 3,022
2009 83,055 70,637 931 9,204 3,264
2010 109,149 91,834 1,257 12,546 4,514
2011 113,068 93,750 1,195 11,892 4,413
2012 128,616 105,222 1,359 12,789 5,037
2013 139,354 117,517 1,446 13,903 5,618
2014 150,216 128,655 1,430 14,397 6,079
2015 151,166 125,701 1,376 14,061 6,177
2016 152,731 128,689 1,299 13,875 6,625
2017 159,565 136,447 1,342 14,330 7,000
2018 154,380 131,121 1,312 13,737 6,883
2019 177,043 152,357 1,431 15,157 7,781
2020 176,569 151,063 1,225 14,731 7,834
2021 166,580 137,771 1,231 14,235 7,214
2022 172,529 128,937 1,164 12,864 6,635

USPTO = Patent and Trademark Office.

Note(s):

Patents are allocated according to patent ownership information. Patents are credited on a fractional-count basis (i.e., for patents with collaborating institutions, each institution receives fractional credit on the basis of the proportion of inventors from participating institutions). Unclassified patents are not shown. See Table SINV-1 and the Technical Appendix for additional detail.

Source(s):

National Center for Science and Engineering Statistics; Science-Metrix; PatentsView, USPTO, accessed June 2023.

Science and Engineering Indicators

As commercial activities increasingly cross international borders, rising rates of foreign patenting reflect the desire of foreign firms to seek patent protection in multiple international jurisdictions (Fink, Khan, and Zhou 2015). Foreign owners were assigned rights to 53% of USPTO utility patents in 2022, an increase from 44% in 2000 (Table SINV-1). In contrast with ownership information, the addresses of inventors provide information about where inventors reside. The European Union (EU-27) and Japan continue to account for the largest numbers of foreign inventors (Figure INV-2). In 2020, the number of patents granted to inventors from China exceeded the number of patents granted to inventors from South Korea for the first time ever. Inventors with addresses in China received about 28,000 patents in 2022 (Figure INV-2). According to a USPTO report, the growth in USPTO patents granted to China is driven by nonmarket factors as well as by traditional market factors. The report identifies nonmarket factors such as university and government subsidies for patenting that can exceed the cost of filing the patent. These subsidies are often higher for patents granted in foreign jurisdictions (USPTO 2021).

USPTO utility patents granted to inventors, by selected region, country, or economy: 2000–22
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USPTO utility patents granted to inventors, by selected region, country, or economy: 2000–22

(Number)
Year United States EU-27 China Japan South Korea Taiwan India
2000 84,777 21,533 326 31,362 3,332 4,705 141
2001 87,379 23,349 461 33,279 3,548 5,397 187
2002 86,658 23,383 561 34,913 3,792 5,444 265
2003 87,604 23,311 614 35,567 3,952 5,299 354
2004 83,971 21,591 740 35,441 4,429 5,951 369
2005 74,315 18,146 744 30,381 4,365 5,115 401
2006 89,375 20,966 1,057 36,870 5,901 6,350 511
2007 79,170 18,850 1,193 33,410 6,299 6,104 566
2008 77,160 18,911 1,606 33,725 7,544 6,345 651
2009 81,961 19,148 2,042 35,557 8,776 6,666 709
2010 107,232 26,348 3,215 44,977 11,669 8,235 1,144
2011 108,117 26,552 3,720 46,337 12,254 8,794 1,277
2012 120,490 30,895 5,359 50,899 13,236 10,638 1,756
2013 133,158 35,059 6,681 52,270 14,556 11,077 2,456
2014 144,048 38,393 8,122 54,317 16,529 11,342 3,073
2015 140,518 38,083 9,021 52,809 17,963 11,688 3,457
2016 143,203 38,389 11,439 50,168 19,576 11,576 3,767
2017 150,423 40,713 14,286 50,073 20,815 11,606 4,271
2018 143,807 39,197 15,477 47,904 19,901 10,995 4,315
2019 166,444 44,400 20,378 54,037 21,871 11,569 5,478
2020 164,127 43,496 22,500 52,116 22,204 12,234 5,917
2021 149,869 39,895 24,471 46,841 20,924 11,285 6,009
2022 141,754 39,527 27,769 45,983 22,147 11,782 6,349

EU-27 = European Union; USPTO = Patent and Trademark Office.

Note(s):

Patents are allocated according to patent inventorship information. Patents are fractionally allocated among regions, countries, or economies based on the proportion of residences of all named inventors. China includes Hong Kong. The United States includes Puerto Rico and all other U.S. territories. See Table SINV-4 for additional countries.

Source(s):

National Center for Science and Engineering Statistics; Science-Metrix; PatentsView, USPTO, accessed June 2023.

Science and Engineering Indicators

USPTO utility patents granted in semiconductors make up 5% of total 2022 patents. Inventors who were resident in the United States received the largest number of USPTO patents in semiconductors, which is identified as a critical or emerging category (NSTC 2022) (Figure INV-3). In addition to inventors from the United States, the highest numbers of USPTO utility patents in semiconductors were issued to inventors from Taiwan, Japan, South Korea, and China. Semiconductor utility patents make up more than a quarter of the USPTO patents received by inventors from Taiwan (Figure INV-3). A public-use file contains data on USPTO patents granted by five broad technology areas and tabulated in Table SINV-4 through Table SINV-9 (File USPTO patents, by county and technical field).

USPTO utility patents granted in semiconductors, by selected country or economy: 2022

(Number and percent)

USPTO = Patent and Trademark Office.

Note(s):

Patents are allocated according to patent inventorship information. Patents are fractionally allocated among regions, countries, or economies based on the proportion of residences of all named inventors. China includes Hong Kong. The United States includes Puerto Rico and all other U.S. territories. See Table SINV-10 for additional regions, countries, and economies.

Source(s):

National Center for Science and Engineering Statistics; Science-Metrix; PatentsView, USPTO, accessed September 2023.

Science and Engineering Indicators

As presented above, these data provide rich geographic and technological detail; however, patent data represent just a portion of all the ways that economically valuable ideas and inventions are protected by their owners. Nondisclosure agreements, trade secrets, trademarks, and copyrights are used by U.S. businesses in addition to utility and design patents (Shackelford and Kindlon 2021).

The Geography of U.S. Patenting

Invention is a market-driven activity and tends to take place where skilled human capital and other inputs are relatively abundant. As new knowledge spreads, it produces localized growth benefits or spillovers that drive additional growth (Grossman and Helpman 1991). States that have relatively high proportions of workers with a bachelor’s degree or higher in science, technology, engineering, and mathematics (STEM) are located primarily on the East Coast and West Coast of the United States and in the U.S. Midwest (see Indicators 2022 report “The STEM Labor Force of Today: Scientists, Engineers, and Skilled Technical Workers”). As skilled labor and other inputs accumulate, a location’s initial advantages grow over time relative to other locations, leading to different growth rates and economic outcomes. Because patent documents include the addresses of both the inventor and the patent owner, patent data provide an indicator of the location of inventive activity.

County-level patenting intensity is measured in this thematic report by the location of the inventor of utility patents granted per 1,000 population. Counties with high patenting intensity are concentrated in the United States along the coasts and in parts of the Great Lakes region, Texas, and the Rocky Mountains (Figure INV-4). This geographic distribution corresponds to indicators of knowledge- and technology-intensive (KTI) industries, in which California is the single largest producer of KTI industry output, followed by Texas, Washington, and New York (see Indicators 2022 report “Production and Trade of Knowledge- and Technology-Intensive Industries”). In 2022, Santa Clara County in California’s Silicon Valley region had the highest patenting intensity. Three of the country’s top five counties in patenting intensity were in the San Jose–San Francisco–Oakland combined statistical area. The top three counties in 2022 for patenting intensity are Santa Clara in California, followed by Fairfax City in Virginia and San Mateo County in California (Figure INV-4).

USPTO utility patents granted to inventors per 1,000 residents, by U.S. county: 2022
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USPTO utility patents granted to inventors per 1,000 residents, by U.S. county: 2022

(Number)
County code County State Patents per 1,000 population
us-ca-085 Santa Clara County California 7.513
us-va-600 Fairfax City Virginia 6.684
us-ca-081 San Mateo County California 4.512
us-va-610 Falls Church City Virginia 4.251
us-ca-075 San Francisco County California 4.170
us-ia-077 Guthrie County Iowa 3.569
us-ks-019 Chautauqua County Kansas 2.928
us-nm-028 Los Alamos County New Mexico 2.762
us-or-003 Benton County Oregon 2.745
us-co-013 Boulder County Colorado 2.709
us-ma-017 Middlesex County Massachusetts 2.514
us-wa-033 King County Washington 2.411
us-ny-101 Steuben County New York 2.138
us-ca-001 Alameda County California 2.087
us-mi-161 Washtenaw County Michigan 1.968
us-va-540 Charlottesville City Virginia 1.939
us-id-001 Ada County Idaho 1.894
us-oh-071 Highland County Ohio 1.867
us-mi-127 Oceana County Michigan 1.817
us-nj-035 Somerset County New Jersey 1.652
us-ca-073 San Diego County California 1.612
us-or-051 Multnomah County Oregon 1.600
us-tx-453 Travis County Texas 1.587
us-co-014 Broomfield County Colorado 1.484
us-ny-093 Schenectady County New York 1.468
us-wi-089 Ozaukee County Wisconsin 1.430
us-ca-087 Santa Cruz County California 1.426
us-in-005 Bartholomew County Indiana 1.389
us-oh-165 Warren County Ohio 1.385
us-in-157 Tippecanoe County Indiana 1.378
us-mn-109 Olmsted County Minnesota 1.329
us-nc-135 Orange County North Carolina 1.303
us-ct-013 Tolland County Connecticut 1.292
us-mi-125 Oakland County Michigan 1.256
us-or-067 Washington County Oregon 1.245
us-ny-109 Tompkins County New York 1.241
us-vt-007 Chittenden County Vermont 1.223
us-ok-147 Washington County Oklahoma 1.221
us-nj-021 Mercer County New Jersey 1.219
us-nc-063 Durham County North Carolina 1.181
us-mn-135 Roseau County Minnesota 1.177
us-mt-039 Granite County Montana 1.142
us-ks-083 Hodgeman County Kansas 1.140
us-in-137 Ripley County Indiana 1.135
us-mn-163 Washington County Minnesota 1.134
us-nj-019 Hunterdon County New Jersey 1.133
us-tx-085 Collin County Texas 1.129
us-ok-137 Stephens County Oklahoma 1.121
us-ca-041 Marin County California 1.090
us-in-085 Kosciusko County Indiana 1.064
us-mi-111 Midland County Michigan 1.064
us-ia-169 Story County Iowa 1.053
us-ny-091 Saratoga County New York 1.043
us-tx-491 Williamson County Texas 1.041
us-ia-095 Iowa County Iowa 1.032
us-mn-053 Hennepin County Minnesota 1.026
us-ut-043 Summit County Utah 1.022
us-nc-183 Wake County North Carolina 1.015
us-il-019 Champaign County Illinois 0.997
us-il-143 Peoria County Illinois 0.987
us-il-113 McLean County Illinois 0.982
us-ny-015 Chemung County New York 0.970
us-ny-061 New York County New York 0.954
us-mo-510 St. Louis City Missouri 0.949
us-mi-021 Berrien County Michigan 0.942
us-tx-211 Hemphill County Texas 0.933
us-ma-025 Suffolk County Massachusetts 0.929
us-ny-027 Dutchess County New York 0.924
us-wa-075 Whitman County Washington 0.924
us-ny-119 Westchester County New York 0.924
us-nh-011 Hillsborough County New Hampshire 0.924
us-ct-003 Hartford County Connecticut 0.915
us-in-159 Tipton County Indiana 0.911
us-ma-021 Norfolk County Massachusetts 0.908
us-ga-121 Fulton County Georgia 0.894
us-in-011 Boone County Indiana 0.890
us-mn-123 Ramsey County Minnesota 0.884
us-ia-049 Dallas County Iowa 0.870
us-ca-013 Contra Costa County California 0.870
us-ny-001 Albany County New York 0.864
us-wi-139 Winnebago County Wisconsin 0.855
us-mn-019 Carver County Minnesota 0.854
us-ca-083 Santa Barbara County California 0.847
us-ne-185 York County Nebraska 0.836
us-mn-151 Swift County Minnesota 0.820
us-ia-113 Linn County Iowa 0.808
us-ne-149 Rock County Nebraska 0.803
us-ia-127 Marshall County Iowa 0.802
us-vt-013 Grand Isle County Vermont 0.801
us-in-131 Pulaski County Indiana 0.801
us-wi-025 Dane County Wisconsin 0.795
us-nh-009 Grafton County New Hampshire 0.779
us-nj-027 Morris County New Jersey 0.769
us-ia-051 Davis County Iowa 0.767
us-co-069 Larimer County Colorado 0.763
us-va-059 Fairfax County Virginia 0.763
us-mn-129 Renville County Minnesota 0.757
us-tx-259 Kendall County Texas 0.756
us-va-830 Williamsburg City Virginia 0.754
us-ca-059 Orange County California 0.746
us-va-013 Arlington County Virginia 0.744
us-ct-007 Middlesex County Connecticut 0.739
us-ok-103 Noble County Oklahoma 0.734
us-mn-113 Pennington County Minnesota 0.722
us-wi-133 Waukesha County Wisconsin 0.719
us-pa-029 Chester County Pennsylvania 0.709
us-il-203 Woodford County Illinois 0.708
us-va-510 Alexandria City Virginia 0.707
us-va-683 Manassas City Virginia 0.704
us-ma-027 Worcester County Massachusetts 0.703
us-mn-139 Scott County Minnesota 0.692
us-ks-131 Nemaha County Kansas 0.692
us-wy-039 Teton County Wyoming 0.687
us-mt-031 Gallatin County Montana 0.681
us-wi-109 St. Croix County Wisconsin 0.677
us-oh-061 Hamilton County Ohio 0.669
us-il-147 Piatt County Illinois 0.658
us-co-035 Douglas County Colorado 0.652
us-tn-001 Anderson County Tennessee 0.646
us-ks-091 Johnson County Kansas 0.643
us-md-031 Montgomery County Maryland 0.642
us-wa-011 Clark County Washington 0.639
us-ca-017 El Dorado County California 0.638
us-ia-061 Dubuque County Iowa 0.638
us-pa-003 Allegheny County Pennsylvania 0.637
us-nh-015 Rockingham County New Hampshire 0.629
us-va-121 Montgomery County Virginia 0.627
us-mi-139 Ottawa County Michigan 0.625
us-mn-003 Anoka County Minnesota 0.624
us-ut-029 Morgan County Utah 0.623
us-mi-077 Kalamazoo County Michigan 0.616
us-il-179 Tazewell County Illinois 0.616
us-ne-169 Thayer County Nebraska 0.614
us-wi-117 Sheboygan County Wisconsin 0.611
us-ma-009 Essex County Massachusetts 0.609
us-in-077 Jefferson County Indiana 0.607
us-fl-001 Alachua County Florida 0.606
us-ky-185 Oldham County Kentucky 0.605
us-va-107 Loudoun County Virginia 0.597
us-oh-017 Butler County Ohio 0.592
us-ks-079 Harvey County Kansas 0.592
us-il-097 Lake County Illinois 0.587
us-mi-093 Livingston County Michigan 0.586
us-nj-025 Monmouth County New Jersey 0.582
us-wy-001 Albany County Wyoming 0.578
us-pa-027 Centre County Pennsylvania 0.574
us-wi-087 Outagamie County Wisconsin 0.573
us-in-057 Hamilton County Indiana 0.570
us-il-043 DuPage County Illinois 0.565
us-ny-055 Monroe County New York 0.561
us-co-031 Denver County Colorado 0.561
us-ct-009 New Haven County Connecticut 0.560
us-pa-091 Montgomery County Pennsylvania 0.556
us-ca-111 Ventura County California 0.554
us-mn-025 Chisago County Minnesota 0.552
us-md-027 Howard County Maryland 0.552
us-ut-049 Utah County Utah 0.551
us-az-005 Coconino County Arizona 0.548
us-ut-005 Cache County Utah 0.542
us-or-027 Hood River County Oregon 0.541
us-wi-131 Washington County Wisconsin 0.537
us-ri-001 Bristol County Rhode Island 0.536
us-ct-001 Fairfield County Connecticut 0.535
us-tx-201 Harris County Texas 0.533
us-mn-067 Kandiyohi County Minnesota 0.525
us-ny-083 Rensselaer County New York 0.519
us-mi-163 Wayne County Michigan 0.513
us-nd-093 Stutsman County North Dakota 0.512
us-sc-045 Greenville County South Carolina 0.507
us-va-760 Richmond City Virginia 0.501
us-mn-171 Wright County Minnesota 0.500
us-co-059 Jefferson County Colorado 0.500
us-co-113 San Miguel County Colorado 0.500
us-pa-017 Bucks County Pennsylvania 0.499
us-nc-035 Catawba County North Carolina 0.496
us-sd-045 Edmunds County South Dakota 0.492
us-ne-175 Valley County Nebraska 0.491
us-ca-113 Yolo County California 0.491
us-ut-035 Salt Lake County Utah 0.491
us-ia-023 Butler County Iowa 0.491
us-ca-069 San Benito County California 0.488
us-ne-101 Keith County Nebraska 0.484
us-oh-055 Geauga County Ohio 0.482
us-nv-031 Washoe County Nevada 0.479
us-va-145 Powhatan County Virginia 0.476
us-ca-097 Sonoma County California 0.468
us-wa-061 Snohomish County Washington 0.464
us-nd-013 Burke County North Dakota 0.464
us-ri-005 Newport County Rhode Island 0.462
us-mi-113 Missaukee County Michigan 0.460
us-il-013 Calhoun County Illinois 0.459
us-nj-023 Middlesex County New Jersey 0.457
us-mn-127 Redwood County Minnesota 0.456
us-il-111 McHenry County Illinois 0.455
us-az-019 Pima County Arizona 0.455
us-mn-147 Steele County Minnesota 0.455
us-nc-037 Chatham County North Carolina 0.451
us-oh-109 Miami County Ohio 0.444
us-oh-035 Cuyahoga County Ohio 0.443
us-co-119 Teller County Colorado 0.443
us-md-510 Baltimore City Maryland 0.440
us-id-057 Latah County Idaho 0.439
us-ri-009 Washington County Rhode Island 0.437
us-ia-017 Bremer County Iowa 0.435
us-or-005 Clackamas County Oregon 0.435
us-sd-097 Miner County South Dakota 0.434
us-oh-169 Wayne County Ohio 0.429
us-mn-037 Dakota County Minnesota 0.429
us-in-063 Hendricks County Indiana 0.427
us-ca-037 Los Angeles County California 0.424
us-ct-005 Litchfield County Connecticut 0.419
us-il-139 Moultrie County Illinois 0.419
us-mo-183 St. Charles County Missouri 0.418
us-tx-113 Dallas County Texas 0.417
us-co-005 Arapahoe County Colorado 0.416
us-ia-125 Marion County Iowa 0.416
us-tx-483 Wheeler County Texas 0.416
us-id-003 Adams County Idaho 0.415
us-mn-149 Stevens County Minnesota 0.415
us-co-097 Pitkin County Colorado 0.415
us-ia-109 Kossuth County Iowa 0.415
us-ks-011 Bourbon County Kansas 0.414
us-de-003 New Castle County Delaware 0.414
us-az-013 Maricopa County Arizona 0.413
us-ks-179 Sheridan County Kansas 0.412
us-mn-079 Le Sueur County Minnesota 0.412
us-sd-127 Union County South Dakota 0.410
us-co-065 Lake County Colorado 0.409
us-ne-139 Pierce County Nebraska 0.409
us-tx-039 Brazoria County Texas 0.407
us-co-001 Adams County Colorado 0.406
us-va-678 Lexington City Virginia 0.402
us-wi-093 Pierce County Wisconsin 0.400
us-ia-179 Wapello County Iowa 0.400
us-wi-079 Milwaukee County Wisconsin 0.399
us-tx-339 Montgomery County Texas 0.399
us-oh-153 Summit County Ohio 0.399
us-nj-003 Bergen County New Jersey 0.399
us-ga-085 Dawson County Georgia 0.398
us-mn-059 Isanti County Minnesota 0.398
us-va-735 Poquoson City Virginia 0.397
us-ia-103 Johnson County Iowa 0.396
us-va-840 Winchester City Virginia 0.394
us-nc-119 Mecklenburg County North Carolina 0.394
us-ks-017 Chase County Kansas 0.392
us-oh-103 Medina County Ohio 0.392
us-nc-067 Forsyth County North Carolina 0.391
us-oh-159 Union County Ohio 0.389
us-ny-079 Putnam County New York 0.388
us-wa-039 Klickitat County Washington 0.387
us-oh-057 Greene County Ohio 0.386
us-ga-113 Fayette County Georgia 0.385
us-ma-007 Dukes County Massachusetts 0.383
us-pa-095 Northampton County Pennsylvania 0.383
us-nv-005 Douglas County Nevada 0.383
us-dc-001 District of Columbia District of Columbia 0.383
us-va-630 Fredericksburg City Virginia 0.383
us-ny-067 Onondaga County New York 0.382
us-mn-039 Dodge County Minnesota 0.381
us-tx-041 Brazos County Texas 0.380
us-ct-011 New London County Connecticut 0.380
us-al-089 Madison County Alabama 0.379
us-wa-035 Kitsap County Washington 0.378
us-pa-077 Lehigh County Pennsylvania 0.377
us-tx-221 Hood County Texas 0.377
us-in-183 Whitley County Indiana 0.375
us-ny-069 Ontario County New York 0.373
us-ok-067 Jefferson County Oklahoma 0.371
us-ky-111 Jefferson County Kentucky 0.371
us-mt-087 Rosebud County Montana 0.371
us-il-031 Cook County Illinois 0.371
us-ky-239 Woodford County Kentucky 0.370
us-ri-003 Kent County Rhode Island 0.368
us-nm-001 Bernalillo County New Mexico 0.367
us-in-071 Jackson County Indiana 0.367
us-nj-017 Hudson County New Jersey 0.367
us-ks-045 Douglas County Kansas 0.367
us-sd-011 Brookings County South Dakota 0.366
us-tn-093 Knox County Tennessee 0.366
us-wi-039 Fond du Lac County Wisconsin 0.366
us-nh-013 Merrimack County New Hampshire 0.365
us-il-201 Winnebago County Illinois 0.365
us-tx-157 Fort Bend County Texas 0.364
us-nh-003 Carroll County New Hampshire 0.364
us-tx-171 Gillespie County Texas 0.364
us-ia-097 Jackson County Iowa 0.362
us-ga-067 Cobb County Georgia 0.361
us-co-107 Routt County Colorado 0.360
us-pa-019 Butler County Pennsylvania 0.360
us-mn-141 Sherburne County Minnesota 0.357
us-oh-009 Athens County Ohio 0.356
us-nd-073 Ransom County North Dakota 0.355
us-ut-011 Davis County Utah 0.354
us-ne-135 Perkins County Nebraska 0.353
us-pa-045 Delaware County Pennsylvania 0.353
us-va-580 Covington City Virginia 0.352
us-tx-385 Real County Texas 0.352
us-in-105 Monroe County Indiana 0.351
us-ks-123 Mitchell County Kansas 0.349
us-ne-017 Brown County Nebraska 0.348
us-in-007 Benton County Indiana 0.344
us-ga-125 Glascock County Georgia 0.340
us-mi-157 Tuscola County Michigan 0.340
us-mi-145 Saginaw County Michigan 0.340
us-ia-013 Black Hawk County Iowa 0.338
us-wi-049 Iowa County Wisconsin 0.335
us-il-011 Bureau County Illinois 0.335
us-fl-011 Broward County Florida 0.335
us-fl-009 Brevard County Florida 0.335
us-va-019 Bedford County Virginia 0.334
us-mn-049 Goodhue County Minnesota 0.333
us-ga-117 Forsyth County Georgia 0.333
us-wi-071 Manitowoc County Wisconsin 0.333
us-il-157 Randolph County Illinois 0.333
us-oh-085 Lake County Ohio 0.332
us-ks-151 Pratt County Kansas 0.331
us-ar-147 Woodruff County Arkansas 0.331
us-il-047 Edwards County Illinois 0.329
us-sc-019 Charleston County South Carolina 0.329
us-mo-049 Clinton County Missouri 0.328
us-mi-081 Kent County Michigan 0.328
us-ut-051 Wasatch County Utah 0.328
us-oh-133 Portage County Ohio 0.328
us-wy-029 Park County Wyoming 0.328
us-me-031 York County Maine 0.328
us-co-117 Summit County Colorado 0.327
us-ia-063 Emmet County Iowa 0.327
us-mn-045 Fillmore County Minnesota 0.327
us-fl-099 Palm Beach County Florida 0.325
us-wa-005 Benton County Washington 0.324
us-al-087 Macon County Alabama 0.324
us-tx-053 Burnet County Texas 0.324
us-ok-039 Custer County Oklahoma 0.323
us-ks-125 Montgomery County Kansas 0.323
us-oh-041 Delaware County Ohio 0.323
us-pa-071 Lancaster County Pennsylvania 0.322
us-mo-075 Gentry County Missouri 0.320
us-mn-055 Houston County Minnesota 0.319
us-nh-019 Sullivan County New Hampshire 0.318
us-nj-037 Sussex County New Jersey 0.315
us-sc-077 Pickens County South Carolina 0.315
us-ia-089 Howard County Iowa 0.315
us-or-017 Deschutes County Oregon 0.315
us-ny-007 Broome County New York 0.315
us-tn-187 Williamson County Tennessee 0.314
us-tn-157 Shelby County Tennessee 0.314
us-ma-015 Hampshire County Massachusetts 0.314
us-va-775 Salem City Virginia 0.313
us-oh-173 Wood County Ohio 0.312
us-in-067 Howard County Indiana 0.311
us-md-029 Kent County Maryland 0.311
us-ia-161 Sac County Iowa 0.310
us-ia-071 Fremont County Iowa 0.309
us-ks-161 Riley County Kansas 0.309
us-il-089 Kane County Illinois 0.309
us-ky-067 Fayette County Kentucky 0.309
us-tn-167 Tipton County Tennessee 0.308
us-nd-055 McLean County North Dakota 0.305
us-in-047 Franklin County Indiana 0.304
us-ma-023 Plymouth County Massachusetts 0.304
us-wi-055 Jefferson County Wisconsin 0.303
us-mn-041 Douglas County Minnesota 0.303
us-mn-085 McLeod County Minnesota 0.300
us-or-035 Klamath County Oregon 0.299
us-ny-053 Madison County New York 0.298
us-ak-195 Petersburg Borough Alaska 0.298
us-mi-005 Allegan County Michigan 0.297
us-wi-101 Racine County Wisconsin 0.296
us-mt-081 Ravalli County Montana 0.296
us-tx-121 Denton County Texas 0.296
us-in-081 Johnson County Indiana 0.296
us-ia-181 Warren County Iowa 0.295
us-oh-063 Hancock County Ohio 0.294
us-ia-153 Polk County Iowa 0.293
us-nv-510 Carson City Nevada 0.292
us-vt-027 Windsor County Vermont 0.292
us-tn-163 Sullivan County Tennessee 0.292
us-fl-103 Pinellas County Florida 0.292
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us-nc-041 Chowan County North Carolina 0.000
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us-nd-087 Slope County North Dakota 0.000
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us-oh-067 Harrison County Ohio 0.000
us-oh-105 Meigs County Ohio 0.000
us-oh-115 Morgan County Ohio 0.000
us-oh-121 Noble County Ohio 0.000
us-oh-145 Scioto County Ohio 0.000
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us-ok-001 Adair County Oklahoma 0.000
us-ok-003 Alfalfa County Oklahoma 0.000
us-ok-005 Atoka County Oklahoma 0.000
us-ok-007 Beaver County Oklahoma 0.000
us-ok-011 Blaine County Oklahoma 0.000
us-ok-021 Cherokee County Oklahoma 0.000
us-ok-023 Choctaw County Oklahoma 0.000
us-ok-025 Cimarron County Oklahoma 0.000
us-ok-033 Cotton County Oklahoma 0.000
us-ok-035 Craig County Oklahoma 0.000
us-ok-041 Delaware County Oklahoma 0.000
us-ok-043 Dewey County Oklahoma 0.000
us-ok-045 Ellis County Oklahoma 0.000
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us-ok-061 Haskell County Oklahoma 0.000
us-ok-063 Hughes County Oklahoma 0.000
us-ok-065 Jackson County Oklahoma 0.000
us-ok-069 Johnston County Oklahoma 0.000
us-ok-073 Kingfisher County Oklahoma 0.000
us-ok-075 Kiowa County Oklahoma 0.000
us-ok-077 Latimer County Oklahoma 0.000
us-ok-085 Love County Oklahoma 0.000
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us-sd-105 Perkins County South Dakota 0.000
us-sd-107 Potter County South Dakota 0.000
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us-sd-117 Stanley County South Dakota 0.000
us-sd-119 Sully County South Dakota 0.000
us-sd-121 Todd County South Dakota 0.000
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us-sd-125 Turner County South Dakota 0.000
us-sd-129 Walworth County South Dakota 0.000
us-sd-137 Ziebach County South Dakota 0.000
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us-tn-021 Cheatham County Tennessee 0.000
us-tn-023 Chester County Tennessee 0.000
us-tn-027 Clay County Tennessee 0.000
us-tn-029 Cocke County Tennessee 0.000
us-tn-033 Crockett County Tennessee 0.000
us-tn-041 DeKalb County Tennessee 0.000
us-tn-039 Decatur County Tennessee 0.000
us-tn-049 Fentress County Tennessee 0.000
us-tn-051 Franklin County Tennessee 0.000
us-tn-053 Gibson County Tennessee 0.000
us-tn-061 Grundy County Tennessee 0.000
us-tn-067 Hancock County Tennessee 0.000
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us-tn-081 Hickman County Tennessee 0.000
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us-tn-111 Macon County Tennessee 0.000
us-tn-115 Marion County Tennessee 0.000
us-tn-117 Marshall County Tennessee 0.000
us-tn-109 McNairy County Tennessee 0.000
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us-tn-127 Moore County Tennessee 0.000
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us-tn-143 Rhea County Tennessee 0.000
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us-tn-159 Smith County Tennessee 0.000
us-tn-161 Stewart County Tennessee 0.000
us-tn-169 Trousdale County Tennessee 0.000
us-tn-171 Unicoi County Tennessee 0.000
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us-tn-181 Wayne County Tennessee 0.000
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us-tx-007 Aransas County Texas 0.000
us-tx-009 Archer County Texas 0.000
us-tx-011 Armstrong County Texas 0.000
us-tx-017 Bailey County Texas 0.000
us-tx-023 Baylor County Texas 0.000
us-tx-025 Bee County Texas 0.000
us-tx-033 Borden County Texas 0.000
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us-tx-047 Brooks County Texas 0.000
us-tx-049 Brown County Texas 0.000
us-tx-059 Callahan County Texas 0.000
us-tx-063 Camp County Texas 0.000
us-tx-065 Carson County Texas 0.000
us-tx-067 Cass County Texas 0.000
us-tx-069 Castro County Texas 0.000
us-tx-075 Childress County Texas 0.000
us-tx-079 Cochran County Texas 0.000
us-tx-081 Coke County Texas 0.000
us-tx-087 Collingsworth County Texas 0.000
us-tx-095 Concho County Texas 0.000
us-tx-101 Cottle County Texas 0.000
us-tx-103 Crane County Texas 0.000
us-tx-105 Crockett County Texas 0.000
us-tx-107 Crosby County Texas 0.000
us-tx-109 Culberson County Texas 0.000
us-tx-111 Dallam County Texas 0.000
us-tx-117 Deaf Smith County Texas 0.000
us-tx-125 Dickens County Texas 0.000
us-tx-127 Dimmit County Texas 0.000
us-tx-129 Donley County Texas 0.000
us-tx-137 Edwards County Texas 0.000
us-tx-145 Falls County Texas 0.000
us-tx-151 Fisher County Texas 0.000
us-tx-155 Foard County Texas 0.000
us-tx-159 Franklin County Texas 0.000
us-tx-163 Frio County Texas 0.000
us-tx-169 Garza County Texas 0.000
us-tx-173 Glasscock County Texas 0.000
us-tx-175 Goliad County Texas 0.000
us-tx-191 Hall County Texas 0.000
us-tx-193 Hamilton County Texas 0.000
us-tx-197 Hardeman County Texas 0.000
us-tx-205 Hartley County Texas 0.000
us-tx-207 Haskell County Texas 0.000
us-tx-229 Hudspeth County Texas 0.000
us-tx-233 Hutchinson County Texas 0.000
us-tx-235 Irion County Texas 0.000
us-tx-237 Jack County Texas 0.000
us-tx-239 Jackson County Texas 0.000
us-tx-243 Jeff Davis County Texas 0.000
us-tx-247 Jim Hogg County Texas 0.000
us-tx-253 Jones County Texas 0.000
us-tx-261 Kenedy County Texas 0.000
us-tx-263 Kent County Texas 0.000
us-tx-267 Kimble County Texas 0.000
us-tx-269 King County Texas 0.000
us-tx-271 Kinney County Texas 0.000
us-tx-275 Knox County Texas 0.000
us-tx-283 La Salle County Texas 0.000
us-tx-279 Lamb County Texas 0.000
us-tx-289 Leon County Texas 0.000
us-tx-293 Limestone County Texas 0.000
us-tx-295 Lipscomb County Texas 0.000
us-tx-301 Loving County Texas 0.000
us-tx-305 Lynn County Texas 0.000
us-tx-313 Madison County Texas 0.000
us-tx-315 Marion County Texas 0.000
us-tx-317 Martin County Texas 0.000
us-tx-321 Matagorda County Texas 0.000
us-tx-323 Maverick County Texas 0.000
us-tx-307 McCulloch County Texas 0.000
us-tx-311 McMullen County Texas 0.000
us-tx-327 Menard County Texas 0.000
us-tx-335 Mitchell County Texas 0.000
us-tx-341 Moore County Texas 0.000
us-tx-345 Motley County Texas 0.000
us-tx-351 Newton County Texas 0.000
us-tx-353 Nolan County Texas 0.000
us-tx-357 Ochiltree County Texas 0.000
us-tx-359 Oldham County Texas 0.000
us-tx-369 Parmer County Texas 0.000
us-tx-377 Presidio County Texas 0.000
us-tx-383 Reagan County Texas 0.000
us-tx-387 Red River County Texas 0.000
us-tx-389 Reeves County Texas 0.000
us-tx-393 Roberts County Texas 0.000
us-tx-395 Robertson County Texas 0.000
us-tx-399 Runnels County Texas 0.000
us-tx-405 San Augustine County Texas 0.000
us-tx-407 San Jacinto County Texas 0.000
us-tx-413 Schleicher County Texas 0.000
us-tx-415 Scurry County Texas 0.000
us-tx-417 Shackelford County Texas 0.000
us-tx-419 Shelby County Texas 0.000
us-tx-421 Sherman County Texas 0.000
us-tx-425 Somervell County Texas 0.000
us-tx-427 Starr County Texas 0.000
us-tx-429 Stephens County Texas 0.000
us-tx-431 Sterling County Texas 0.000
us-tx-433 Stonewall County Texas 0.000
us-tx-435 Sutton County Texas 0.000
us-tx-437 Swisher County Texas 0.000
us-tx-443 Terrell County Texas 0.000
us-tx-445 Terry County Texas 0.000
us-tx-447 Throckmorton County Texas 0.000
us-tx-455 Trinity County Texas 0.000
us-tx-457 Tyler County Texas 0.000
us-tx-461 Upton County Texas 0.000
us-tx-475 Ward County Texas 0.000
us-tx-487 Wilbarger County Texas 0.000
us-tx-489 Willacy County Texas 0.000
us-tx-495 Winkler County Texas 0.000
us-tx-501 Yoakum County Texas 0.000
us-tx-505 Zapata County Texas 0.000
us-tx-507 Zavala County Texas 0.000
us-ut-009 Daggett County Utah 0.000
us-ut-017 Garfield County Utah 0.000
us-ut-027 Millard County Utah 0.000
us-ut-031 Piute County Utah 0.000
us-ut-033 Rich County Utah 0.000
us-ut-037 San Juan County Utah 0.000
us-ut-055 Wayne County Utah 0.000
us-vt-009 Essex County Vermont 0.000
us-vt-019 Orleans County Vermont 0.000
us-va-001 Accomack County Virginia 0.000
us-va-011 Appomattox County Virginia 0.000
us-va-017 Bath County Virginia 0.000
us-va-021 Bland County Virginia 0.000
us-va-025 Brunswick County Virginia 0.000
us-va-027 Buchanan County Virginia 0.000
us-va-029 Buckingham County Virginia 0.000
us-va-530 Buena Vista City Virginia 0.000
us-va-035 Carroll County Virginia 0.000
us-va-037 Charlotte County Virginia 0.000
us-va-045 Craig County Virginia 0.000
us-va-049 Cumberland County Virginia 0.000
us-va-053 Dinwiddie County Virginia 0.000
us-va-595 Emporia City Virginia 0.000
us-va-620 Franklin City Virginia 0.000
us-va-640 Galax City Virginia 0.000
us-va-071 Giles County Virginia 0.000
us-va-073 Gloucester County Virginia 0.000
us-va-077 Grayson County Virginia 0.000
us-va-079 Greene County Virginia 0.000
us-va-081 Greensville County Virginia 0.000
us-va-083 Halifax County Virginia 0.000
us-va-091 Highland County Virginia 0.000
us-va-095 James City County Virginia 0.000
us-va-101 King William County Virginia 0.000
us-va-097 King and Queen County Virginia 0.000
us-va-103 Lancaster County Virginia 0.000
us-va-105 Lee County Virginia 0.000
us-va-111 Lunenburg County Virginia 0.000
us-va-690 Martinsville City Virginia 0.000
us-va-115 Mathews County Virginia 0.000
us-va-119 Middlesex County Virginia 0.000
us-va-125 Nelson County Virginia 0.000
us-va-131 Northampton County Virginia 0.000
us-va-720 Norton City Virginia 0.000
us-va-141 Patrick County Virginia 0.000
us-va-143 Pittsylvania County Virginia 0.000
us-va-149 Prince George County Virginia 0.000
us-va-155 Pulaski County Virginia 0.000
us-va-159 Richmond County Virginia 0.000
us-va-161 Roanoke County Virginia 0.000
us-va-163 Rockbridge County Virginia 0.000
us-va-169 Scott County Virginia 0.000
us-va-173 Smyth County Virginia 0.000
us-va-175 Southampton County Virginia 0.000
us-va-181 Surry County Virginia 0.000
us-va-183 Sussex County Virginia 0.000
us-va-193 Westmoreland County Virginia 0.000
us-va-195 Wise County Virginia 0.000
us-va-197 Wythe County Virginia 0.000
us-wa-019 Ferry County Washington 0.000
us-wa-023 Garfield County Washington 0.000
us-wa-043 Lincoln County Washington 0.000
us-wa-047 Okanogan County Washington 0.000
us-wa-069 Wahkiakum County Washington 0.000
us-wv-001 Barbour County West Virginia 0.000
us-wv-005 Boone County West Virginia 0.000
us-wv-007 Braxton County West Virginia 0.000
us-wv-013 Calhoun County West Virginia 0.000
us-wv-017 Doddridge County West Virginia 0.000
us-wv-021 Gilmer County West Virginia 0.000
us-wv-023 Grant County West Virginia 0.000
us-wv-031 Hardy County West Virginia 0.000
us-wv-041 Lewis County West Virginia 0.000
us-wv-043 Lincoln County West Virginia 0.000
us-wv-045 Logan County West Virginia 0.000
us-wv-047 McDowell County West Virginia 0.000
us-wv-055 Mercer County West Virginia 0.000
us-wv-063 Monroe County West Virginia 0.000
us-wv-067 Nicholas County West Virginia 0.000
us-wv-071 Pendleton County West Virginia 0.000
us-wv-073 Pleasants County West Virginia 0.000
us-wv-075 Pocahontas County West Virginia 0.000
us-wv-083 Randolph County West Virginia 0.000
us-wv-085 Ritchie County West Virginia 0.000
us-wv-089 Summers County West Virginia 0.000
us-wv-091 Taylor County West Virginia 0.000
us-wv-093 Tucker County West Virginia 0.000
us-wv-095 Tyler County West Virginia 0.000
us-wv-097 Upshur County West Virginia 0.000
us-wv-101 Webster County West Virginia 0.000
us-wv-103 Wetzel County West Virginia 0.000
us-wv-109 Wyoming County West Virginia 0.000
us-wi-001 Adams County Wisconsin 0.000
us-wi-011 Buffalo County Wisconsin 0.000
us-wi-023 Crawford County Wisconsin 0.000
us-wi-029 Door County Wisconsin 0.000
us-wi-037 Florence County Wisconsin 0.000
us-wi-041 Forest County Wisconsin 0.000
us-wi-051 Iron County Wisconsin 0.000
us-wi-057 Juneau County Wisconsin 0.000
us-wi-067 Langlade County Wisconsin 0.000
us-wi-078 Menominee County Wisconsin 0.000
us-wi-099 Price County Wisconsin 0.000
us-wi-103 Richland County Wisconsin 0.000
us-wi-107 Rusk County Wisconsin 0.000
us-wi-119 Taylor County Wisconsin 0.000
us-wy-003 Big Horn County Wyoming 0.000
us-wy-009 Converse County Wyoming 0.000
us-wy-015 Goshen County Wyoming 0.000
us-wy-017 Hot Springs County Wyoming 0.000
us-wy-027 Niobrara County Wyoming 0.000
us-wy-031 Platte County Wyoming 0.000
us-wy-045 Weston County Wyoming 0.000

USPTO = Patent and Trademark Office.

Note(s):

USPTO patents are allocated to counties according to the address for each inventor listed on a patent. U.S. addresses were geocoded to 3,143 U.S. counties according to U.S. states, U.S. cities, and ZIP Codes appearing in these addresses. Because of the absence of ZIP Codes for most U.S. addresses in the patent data, coassignment to multiple U.S. counties occurred for addresses accounting for about 14% of all U.S. patent counts, mostly in populous cities encompassing multiple counties. Further manual disambiguation was performed based on information available to assign some of the ambiguous addresses to a single county. When more than one county remained for an address on a patent, the fraction of the patent associated to this address was split equally across all the counties. See File USPTO patents, by county and technical field and the Technical Appendix for additional detail.

Source(s):

National Center for Science and Engineering Statistics; Science-Metrix; PatentsView, USPTO, accessed June 2023. Population data from the Census Bureau, https://www2.census.gov/programs-surveys/popest/tables/2020-2022/counties/totals/co-est2022-pop.xlsx, accessed June 2023.

Science and Engineering Indicators

The county patenting data files released with this report provide additional detail by technology area, showing, for example, the high rate of transportation technology patenting in Oakland and Wayne Counties in Michigan (File USPTO patents, by region, country, economy, and technical field). In 2022, 64% of all counties had at least one patent granted to inventors in that county. Beyond geography, the technological detail in the patent documents makes it possible for new insights into environmental management and mitigation. The sidebar Patenting That Addresses Environmental Sustainability provides country and U.S. state data on the patents granted and geographic specialization in these technologies. A supplemental workbook released with this report provides annual country-, state-, and county-level data for 1998–2022 (File USPTO environmental and critical technology patent data).

Patenting That Addresses Environmental Sustainability

International Patents, by Broad Technology Category

Chemistry, electrical engineering, instruments, mechanical engineering, and other fields are broad categories for the technology areas of utility patents (Table SINV-3). At the national level, both chemistry and instruments were technology areas with greatest participation by U.S. inventors. In 2022, inventors from the United States were granted 27% of chemistry patents and 27% of instruments patents; inventors from China had 37% of the PCT patents granted in electrical engineering (Figure INV-6).

PCT applications for selected technology areas, by selected region, country, or economy: 2022
Keyboard instructions

PCT applications for selected technology areas, by selected region, country, or economy: 2022

(Percent)
Technology area United States China EU-27 Japan South Korea Rest of world
Chemistry 27.3 16.9 21.4 18.6 7.2 8.8
Electrical engineering 19.6 37.4 12.0 17.3 9.8 3.8
Instruments 27.0 19.8 19.5 19.2 6.6 7.9
Mechanical engineering 14.7 19.2 31.0 21.7 4.9 8.5
Other fields 22.4 23.9 21.7 11.3 9.3 11.3

EU-27 = European Union; PCT = Patent Cooperation Treaty.

Note(s):

Figures are based on publication year of PCT applications. China includes Hong Kong. Technology areas are derived from the World Intellectual Property Organization (WIPO) concordance of International Patent Classifications to technology categories available at https://www.wipo.int/ipstats/en/. Countries are allocated using the receiving office for each PCT application, which is the location of the inventors. In cases where PCT applications are filed directly with WIPO via its international bureau, the priority country of the earliest document in the same patent family is used (i.e., where the first application in the patent family was filed). See Table SINV-11 through Table SINV-16.

Source(s):

National Center for Science and Engineering Statistics; EP Bibliographic Data (EBD), European Patent Office; 1790 Analytics, accessed July 2023.

Science and Engineering Indicators

Global Patenting Activity in Artificial Intelligence

This section examines trends over time in AI patenting across regions, countries, and economies. AI is identified as a critical or emerging technology (NSTC 2022). The technology-level analysis of international patent family data from the European Patent Office’s Global Patent Index database covers years since 2000 with AI patents granted, rather than applications, as the unit of measurement.

This presentation contains 13 categories based on 3 distinct dimensions of AI patents that are categorized using a taxonomy developed by the Association for Computing Machinery and employed in previous studies of AI patenting by WIPO (WIPO 2019). AI techniques are defined by how the invention works, with categories such as machine learning, logic models, and fuzzy logic. Functional applications reflect what the invention does, with categories including computer vision, control systems, measurement and testing, and knowledge representation (Table SINV-18). Application fields reflect where the invention is designed to be used, with categories of life sciences, transportation, energy management, and industrial and manufacturing applications.

Based on this taxonomy, about 190,000 AI patents were granted worldwide between 2000 and 2022 (Table SINV-17). In 2022, about 40,000 AI patents were granted to inventors with addresses from China; the comparable figure for the United States was about 9,000 (Figure INV-7). Machine learning, personal devices and computing, and computer vision were categories that had the highest number of patents received, based on technology, application, or field. Among the United States, China, Japan, and South Korea, inventors with addresses in China had the highest number of patents in all three categories (Figure INV-8). Within the United States, inventors received the highest number of patents in machine learning, followed by personal devices and telecommunications applications (Figure INV-8).

Worldwide utility patents in AI granted to inventors, by selected country or economy: 2000–22
Keyboard instructions

Worldwide utility patents in AI granted to inventors, by selected country or economy: 2000–22

(Number)
Year China United States South Korea Japan Australia India Germany Taiwan United Kingdom Israel France Canada Russia
2000 11 262 33 252 1 0 45 13 14 4 16 11 4
2001 14 258 26 306 8 1 54 20 18 1 13 8 5
2002 24 274 32 246 3 1 48 12 21 8 11 10 8
2003 37 411 28 219 2 3 59 29 31 11 19 12 11
2004 33 379 41 175 6 5 47 22 22 6 22 13 8
2005 51 300 51 174 11 4 40 26 21 7 24 17 14
2006 53 400 45 186 11 5 53 22 29 8 28 22 17
2007 74 388 76 163 7 4 39 26 29 10 21 19 20
2008 116 457 62 167 9 7 60 18 17 14 31 13 19
2009 170 546 58 212 9 9 43 27 27 22 23 19 31
2010 292 690 63 230 10 14 68 39 21 17 26 31 24
2011 457 719 70 210 15 14 50 29 43 21 33 31 44
2012 650 924 84 316 12 22 78 51 39 34 46 38 49
2013 695 1,066 161 353 15 34 67 77 51 40 42 58 32
2014 720 1,071 141 275 16 46 68 76 56 42 37 46 30
2015 942 1,128 139 207 23 45 83 55 39 44 52 42 52
2016 1,236 1,294 187 331 28 61 82 72 52 47 49 49 53
2017 2,098 1,483 339 395 34 64 84 90 67 55 59 54 89
2018 2,819 1,666 639 460 69 123 111 124 80 98 70 64 111
2019 4,600 3,548 1,313 940 90 244 243 180 167 173 118 149 174
2020 12,573 6,518 3,254 1,701 320 543 589 464 380 281 238 272 199
2021 23,511 7,882 4,934 2,160 874 758 702 585 449 393 382 340 229
2022 40,261 9,412 5,449 2,963 255 1,036 1,042 735 493 447 399 443 105

AI = artificial intelligence.

Note(s):

Granted patents for all patent authorities are allocated according to patent inventorship information. AI patents are identified and divided into categories using filters consisting of Cooperative Patent Classifications and International Patent Classifications plus keywords and phrases. Details of these filters can be found at https://github.com/georgetown-cset/1790-ai-patent-data/. Only the first granted patent in each patent family is counted so as to avoid double counting the same invention. Patent families containing no granted patents are excluded. Country assignments are based on fractional counting of countries of residence of inventors as listed in the associated record from the Global Patent Index. If no inventor countries are listed, the priority country is used (i.e., where the first application in the patent family was filed). China includes Hong Kong.

Source(s):

National Center for Science and Engineering Statistics; European Patent Office Global Patent Index; 1790 Analytics, accessed June 2023.

Science and Engineering Indicators

Worldwide granted utility patents in AI techniques, functional applications, and application fields, by selected country: 2000–22
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Worldwide granted utility patents in AI techniques, functional applications, and application fields, by selected country: 2000–22

(Number)
Category United States China Japan South Korea
Machine learning 31,676 77,615 10,518 14,351
Personal devices and computing 23,207 34,074 5,761 5,266
Logic programming 10,380 2,744 2,252 904
Telecommunications 11,070 11,318 1,807 3,861
Computer vision 10,287 34,044 3,169 4,754
Knowledge representation 5,723 1,051 763 419
Control 6,244 5,940 3,137 1,749
Life sciences 5,676 5,098 1,192 2,339
Probabilistic reasoning 4,484 5,840 1,027 699
Measuring or testing 5,050 8,835 1,756 1,992
Transportation 4,538 3,767 1,763 1,415
Industrial and manufacturing 1,565 5,431 1,232 1,151
Energy management 1,177 5,834 810 1,120

AI = artificial intelligence.

Note(s):

Granted patents for all patent authorities are allocated according to patent inventorship information. AI patents are identified and divided into categories using filters consisting of Cooperative Patent Classifications and International Patent Classifications plus keywords and phrases. Details of these filters can be found at https://github.com/georgetown-cset/1790-ai-patent-data/. Only the first granted patent in each patent family is counted so as to avoid double-counting the same invention. Patent families containing no granted patents are excluded. Country assignments are based on fractional counting of inventor locations as listed in the associated record from the Global Patent Index. If no inventor countries are listed, the priority country is used (i.e., where the first application in the patent family was filed). China includes Hong Kong.

Source(s):

National Center for Science and Engineering Statistics; European Patent Office Global Patent Index; 1790 Analytics, accessed June 2023.

Science and Engineering Indicators

In addition to AI, there are critical or otherwise important technologies within the technologies such as chemistry, electrical engineering, or instruments. USPTO patenting activity for the technologies funded by Congress in recent legislation is described in the sidebar Patenting That Addresses CHIPS and Science Act Technologies.

Patenting That Addresses CHIPS and Science Act Technologies

Counting Women as Patented Inventors

The information required to register a patent generally includes an inventor’s name but not their gender. Thus, comprehensive longtime sources of information on patenting by gender are scarce. Computer matching of inventor names to their most likely gender is often used along with verification against data sets of known inventors and their gender. Analyses like these have shown that patenting activity is unevenly distributed among men and women, with men much more likely to be inventors named on granted patents (USPTO, Office of the Chief Economist 2020; WIPO 2020).

This section reports on the prevalence of women as inventors in design patents and utility patents in broad technology areas. The analysis is based on USPTO data and uses the WIPO Gender Name Dictionary drawn from a data set of worldwide patents to assign inventors to a gender (Martinez et al. 2021). The methodology is further described in the Technical Appendix to this report. For all patents granted from 2000 through 2022, the share of inventors who are women is highest in chemistry-related utility patents and design patents (based on female names) on patents granted (14% each), and mechanical engineering has the smallest share (5%) over the 22-year period (Figure INV-9). Across all fields, women have increased their participation in patenting, with the fastest increase in electrical engineering, where the share of women inventors increased from 5% in 2000 to 10% in 2022. The category with the highest share in 2022 is chemistry (18%), followed closely by design patents (16%) (Figure INV-10).

Inventors with female names on granted USPTO patents, by technology area: 2000–22
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Inventors with female names on granted USPTO patents, by technology area: 2000–22

(Percent)
Technology area Inventors
Chemistry (utility patents) 14.3
Design patents 14.0
Other fields (utility patents) 8.7
Electrical engineering (utility patents) 8.0
Instruments (utility patents) 7.9
Mechanical engineering (utility patents) 5.3

USPTO = Patent and Trademark Office.

Note(s):

The analysis of patenting by gender is based on patents granted by USPTO. Fractional counting of inventors is used, with the credit for each patent divided equally between the inventors. The gender of inventors is determined using the World Intellectual Property Organization (WIPO) World Gender-Name Dictionary Version 2.0, available at https://dataverse.harvard.edu/dataverse/WGND. The process for matching inventor names to genders is based on the WIPO guidelines described at https://tind.wipo.int/record/45020?ln=en. Technology areas are based on the WIPO concordance of International Patent Classifications to technology categories available at https://www.wipo.int/ipstats/en/.

Source(s):

National Center for Science and Engineering Statistics; USPTO Bulk Data Storage System (BDSS); 1790 Analytics, accessed June 2023.

Science and Engineering Indicators

Inventors with female names on granted USPTO patents, by technology area and issue year: 2000–22
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Inventors with female names on granted USPTO patents, by technology area and issue year: 2000–22

(Percent)
Year Chemistry Design patents Electrical engineering Other fields Instruments Mechanical engineering All patents
2000 10.8 12.2 5.4 8.6 6.6 3.8 7.2
2001 11.2 12.1 5.4 8.5 6.4 4.2 7.3
2002 12.0 11.1 5.6 8.2 6.5 4.4 7.4
2003 11.9 11.3 5.9 7.8 6.5 4.4 7.4
2004 11.5 11.3 6.0 8.4 6.5 4.6 7.3
2005 12.0 11.4 6.3 7.8 6.7 4.8 7.4
2006 12.7 11.5 6.6 8.5 6.6 5.2 7.8
2007 13.1 12.4 6.7 8.6 6.9 5.1 8.3
2008 13.4 13.4 7.0 8.3 6.8 5.3 8.6
2009 13.5 13.0 7.1 8.2 6.7 5.2 8.4
2010 13.7 14.1 7.5 8.1 7.3 5.7 8.8
2011 13.5 14.5 7.6 8.6 7.6 5.6 8.8
2012 14.3 14.1 7.6 8.3 7.7 5.1 8.8
2013 14.5 14.9 8.0 8.3 7.8 5.0 9.0
2014 14.9 14.3 8.1 8.7 8.0 5.1 9.1
2015 14.9 14.3 8.2 8.3 7.9 5.2 9.2
2016 15.4 15.9 8.5 8.9 8.2 5.2 9.6
2017 15.8 15.6 8.6 8.9 8.4 5.4 9.7
2018 16.3 15.1 8.7 8.9 8.6 5.5 9.8
2019 16.4 15.1 8.9 8.9 8.9 5.7 9.9
2020 16.6 15.2 9.3 9.4 9.0 5.9 10.1
2021 17.1 15.4 9.8 9.5 9.4 6.1 10.5
2022 17.6 16.3 10.0 10.3 9.6 6.4 10.9

USPTO = Patent and Trademark Office.

Note(s):

The analysis of patenting by gender is based on patents granted by USPTO. Fractional counting of inventors is used, with the credit for each patent divided equally between the inventors. The gender of inventors is determined using the World Intellectual Property Organization (WIPO) World Gender-Name Dictionary Version 2.0, available at https://dataverse.harvard.edu/dataverse/WGND. The process for matching inventor names to genders is based on the WIPO guidelines described at https://tind.wipo.int/record/45020?ln=en. Technology areas are based on the WIPO concordance of International Patent Classifications to technology categories available at https://www.wipo.int/ipstats/en/.

Source(s):

National Center for Science and Engineering Statistics; USPTO Bulk Data Storage System (BDSS); 1790 Analytics, accessed June 2023.

Science and Engineering Indicators

Academic research on the share of women as inventors has highlighted factors outside of the technology field. Once women are in the science and engineering (S&E) workforce, factors that are associated with the increased participation of women as patented inventors include collaboration with university advisors in graduate programs. This collaboration is associated with higher rates of first-time patenting by women, identifying a role for mentorship at universities in the invention process (Delgado and Murray 2021, 2022).