Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

115 indexed citations

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This paper, published in 2020, received 115 indexed citations. Written by David Freeman Engstrom, Daniel E. Ho, Catherine M. Sharkey and Mariano-Florentino Cuéllar covering the research area of Law, Safety Research and Political Science and International Relations. It is primarily cited by scholars working on Safety Research (46 citations), Sociology and Political Science (28 citations) and Artificial Intelligence (27 citations). Published in SSRN Electronic Journal.

Countries where authors are citing Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

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This map shows the geographic impact of Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies more than expected).

Fields of papers citing Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies.

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This paper is also available at doi.org/10.2139/ssrn.3551505.

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