MACHINE LEARNING, INOVAÇÕES GOVERNAMENTAIS E NOVOS DESAFIOS PARA A TRANSPARÊNCIA PÚBLICA
Palavras-chave:
Algoritmos. Machine Learning. Transparência. Accountability. Transformação Digital.
Resumo
Governos têm produzido inovações importantes em rotinas administrativas e no processo das políticas públicas com a crescente adoção de sistemas baseados em algoritmos de machine learning. Movidos por uma ideia ampla de transformação digital, a adoção de sistemas de machine learning para tomar decisão e realizar tarefas da administração pública criam uma nova camada de complexidade para as políticas de transparência. Algoritmos de machine learning desafiam as políticas de transparência à medida que o desenho de sistemas e o modo como os algoritmos calculam cursos de ação pública são opacos para a sociedade. Algoritmos de machine learning implementados em diferentes atividades governamentais implicam em desafios para a transparência e accountability. Este artigo discute estes desafios e aponta caminhos com relação à promoção da transparência. Mais do que se concentrar no processo de desenho de arquiteturas algorítmicas, policymakers devem se concentrar também na transparência dos resultados de sistemas aplicados em governos. Processos de autorregulação de IA são insuficientes para enfrentar os desafios conexos do avanço e crescente adoção de algoritmos de machine learning em inovações governamentais.
Referências
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BENJAMIN, Ruha. Race after technology. New York: Polity Press, 2019.
BINNS, Reuben. “Algorithmic accountability and public reason”. Philosophy & Technology, 31(4), 543–556, 2018. DOI: https://doi.org/10.1007/s13347-017-0263-5
BRYSON, Joanna. “AI & global governance: No one should trust AI”, 2018. https://cpr.unu.edu/publications/articles/ai-global-governance-no-one-should-trust-ai.html
CÂMARA DOS DEPUTADOS. “Projeto de Lei 21/2020”. Brasilia: Câmara dos Deputados. Disponível em: https://www.camara.leg.br/propostas-legislativas/2236340
CHAMBERS, Simone. “Behind closed doors: Publicity, secrecy, and the quality of deliberation”. Journal of Political Philosophy, 12, 389-410. https://doi.org/10.1111/j.1467-9760.2004.00206.x
COECKELBERGH, Mark. “Democracy, epistemic agency, and AI: political epistemology in times of artificial intelligence”. AI & Ethics, early view, 2022. Doi: https://doi.org/10.1007/s43681-022-00239-4
COLLINGTON, Rosie. “Disrupting the Welfare State? Digitalisation and the Retrenchment of Public Sector Capacity”, New Political Economy, 27 (2), 312-328, 2022, DOI: https://doi.org/10.1080/13563467.2021.1952559
CRAIN, Matthew. “The limits of transparency: data brokers and commodifcation.” New Media & Society, 20 (1), 88–104, 2018. DOI: https://doi.org/10.1177/1461444816657096
DAI, Xi. “Enforcing law and norms for good citizens: One view of China’s social credit system project”. Development, 63, 38–43, 2020. Doi: https://doi.org/10.1057/s41301-020-00244-2
DIAKOPOULOS, Nick. “Accountability in algorithmic decision making”. Communications of the ACM, 59 (2), 56–62, 2016. DOI: https://doi.org/10.1145/2844110
EISENHARDT, Kathleen M. "Agency Theory: An Assessment and Review", The Academy of Management Review, 14 (1): 57–74, 1989. DOI: https://doi.org/10.5465/amr.1989.4279003
EUBANKS, Virginia. Automating inequality. How high-tech tools profile, police, and punish the poor. New York: St. Martin’s Press, 2018.
FILGUEIRAS, Fernando. “New Pythias of public administration: Ambiguity and choice in AI systems and challenges for governance”. AI & Society, 37 (4), 1473-1486, 2022. DOI: https://doi.org/10.1007/s00146-021-01201-4
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FILGUEIRAS, Fernando. “Transparency and accountability: Principles and rules for the construction of publicity.” Journal of Public Affairs, 16(2), 192-202, 2016. DOI: https://doi.org/10.1002/pa.1575
FINE LICHT, Karl de; FINE LICHT, Jenny de. “Artificial intelligence, transparency, and public decision-making”. AI & Society, 35 (4), 917–926, 2020. DOI: https://doi.org/10.1007/s00146-020-00960-w
FRISCHMANN, Brett; SELINGER, Evan. Re-engineering humanity. Cambridge: Cambridge University Press, 2018.
GAILMARD, Sean. "Multiple principals and oversight of bureaucratic policy-making". Journal of Theoretical Politics. 21 (2): 161–86, 2009. DOI: https://doi.org/10.1177/0951629808100762
GORWA, Robert; BINNS, Reuben, KATZENBACH, Christian. “Algorithmic content moderation: Technical and political challenges in automation of platform governance”. Big Data & Society, 7 (1), 1–15, 2020. DOI: https://doi.org/10.1177/2053951719897945
INNERARITY, Daniel. “Making the black box society transparent”. AI & Society, 36, 975–981, 2021. DOI: https://doi.org/10.1007/s00146-020-01130-8
ISSAR, Shiv; ANEESH, Aneesh. “What is algorithmic governance?”. Sociology Compass, 16 (1), e12955, 2022. Doi: https://doi.org/10.1111/soc4.12955
JONES, Bryan D.; BAUMGARTNER, Frank R. The politics of attention: How government prioritizes problems. Chicago: The University of Chicago Press, 2005.
KELLEHER, John D. Deep learning. Cambridge: The MIT Press, 2019.
KNUTH, Donald E. The art of computer programming, Volume 1: Fundamental Algorithms. Berkeley: Addison-Wesley, 1968.
KÖNIG, Pascal D.; WENZELBURGER, G. “The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it”. Technology in Society, 67, 1–10, 2021. DOI: https://doi.org/10.1016/j.techsoc.2021.101688
KROLL, Joshua A.; HUEY, Joanna; BAROCAS, Solon; FELTEN, Edward W.; REIDENBERG, Joel R.; ROBINSON, David G.; YU, Harlan. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165, 633–705. https://scholarship.law.upenn.edu/penn_law_review/vol165/iss3/3
LINDBLOM, Charles. “The science of muddling through”. Public Administration Review, 19 (2), 79-88. DOI: https://doi.org/10.2307/973677
MARKRAM, Henry. “The Blue Brain project”. Nature Reviews Neuroscience, vol. 7, nº 2, p. 153–160, 2006.
MENDONÇA, Ricardo F.; FILGUEIRAS, Fernando; ALMEIDA, Virgilio A. Algorithmic Institutionalism. The Changing Rules of Social + Political Life. Oxford: Oxford University Press, 2023.
MINSKY, Marvim. The Society of Mind. New York: Simon and Schuster, 1985.
OBERMEYER, Ziad; POWERS, Brian; VOGELI, Christine; MULLAINATHAN, Sendhil. “Dissecting racial bias in an algorithm used to manage the health of populations”. Science, 366 (6464), 447–453, 2019. DOI: https://doi.org/10.1126/science.aax2342
PAPYSHEV, Gleb; YARIME, Masaru. “The limitation of ethics-based approaches to regulating artifcial intelligence: regulatory gifting in the context of Russia”. AI & Society, early view, 1-16. DOI: https://doi.org/10.1007/s00146-022-01611-y
PASQUALE, Frank. The black box society. The secret algorithms that control money and information. Cambridge: Harvard University Press, 2015.
RUSSELL, Stuart J. Human compatible: Artificial intelligence and the problem of control. New York: Viking Books, 2019.
RUSSELL, Stuart J.; NORVIG, Peter. Artificial intelligence: A modern approach. Englewood Cliffs, NJ: Prentice-Hall, 2010.
SAMUEL, A.L. “Artificial intelligence: A frontier of automation”. The Annals of the American Academy of Political and Social Science, 340 (1), 10-20, 1962. Doi: https://doi.org/10.1177/000271626234000103
SAMUEL, Arthur. “Some studies in machine learning using the game of checkers.” IBM Journal of Research and Development, vol. 44, nº 1-2, p. 210–229, 1959. Doi: https://doi.org/10.1147/rd.33.0210
SIMON, Herbert A. Models of man: Social and rational. New York: John Wiley, 1957.
SIMON, Herbert A. The sciences of the artificial. Cambridge, MA: MIT Press, 1969.
SIMON, Herbert A. “Artificial intelligence: An empirical science”. Artificial Intelligence, 77 (1), 95-127. Doi: https://doi.org/10.1016/0004-3702(95)00039-H
TSAMADOS, Andreas; AGGARWAL, Nikita; COWLS; Josh, MORLEY, Jessica; ROBERTS, Huw; TADDEO, Mariarosaria; FLORIDI, Luciano. “The ethics of algorithms: key problems and solutions”. AI & Society, 37 (1), 215–230, 2022. DOI: https://doi.org/10.1007/s00146-021-01154-8
TURING, Alan. “Computing machinery and intelligence”. Mind—A Quarterly Review of Psychology and Philosophy, 59(236), 433–460, 1950.
WANG, Pei. “On defining artificial intelligence”. Journal of Artificial General Intelligence, 10 (2), 1-37, 2019. Doi: https://doi.org/10.2478/jagi-2019-0002.
AMOORE, Louise. “Machine learning political orders”. Review of International Studies, 49 (1), 20-36, 2022. Doi: https://doi.org/10.1017/S0260210522000031
AMOORE, Louise. “The deep border”. Political Geography, 96, 1–9, 2021. Doi: https://doi.org/10.1016/j.polgeo.2021.102547
ANANNY, Mark; CRAWFORD, Kate. “Seeing without knowing: limitations of the transparency ideal and its application to algorithmic accountability”. New Media & Society, 20 (3), 973–989, 2018. DOI: https://doi.org/10.1177/1461444816676645
ANSELL, Chris. “Ecological explanation”. In: Berk, G.; Galvan, D.C.; Hattam, V. (org.). Political creativity. Reconfiguring institutional order and change. Philadelphia: University of Pennsylvania Press, pp. 55–77, 2013.
BENJAMIN, Ruha. Race after technology. New York: Polity Press, 2019.
BINNS, Reuben. “Algorithmic accountability and public reason”. Philosophy & Technology, 31(4), 543–556, 2018. DOI: https://doi.org/10.1007/s13347-017-0263-5
BRYSON, Joanna. “AI & global governance: No one should trust AI”, 2018. https://cpr.unu.edu/publications/articles/ai-global-governance-no-one-should-trust-ai.html
CÂMARA DOS DEPUTADOS. “Projeto de Lei 21/2020”. Brasilia: Câmara dos Deputados. Disponível em: https://www.camara.leg.br/propostas-legislativas/2236340
CHAMBERS, Simone. “Behind closed doors: Publicity, secrecy, and the quality of deliberation”. Journal of Political Philosophy, 12, 389-410. https://doi.org/10.1111/j.1467-9760.2004.00206.x
COECKELBERGH, Mark. “Democracy, epistemic agency, and AI: political epistemology in times of artificial intelligence”. AI & Ethics, early view, 2022. Doi: https://doi.org/10.1007/s43681-022-00239-4
COLLINGTON, Rosie. “Disrupting the Welfare State? Digitalisation and the Retrenchment of Public Sector Capacity”, New Political Economy, 27 (2), 312-328, 2022, DOI: https://doi.org/10.1080/13563467.2021.1952559
CRAIN, Matthew. “The limits of transparency: data brokers and commodifcation.” New Media & Society, 20 (1), 88–104, 2018. DOI: https://doi.org/10.1177/1461444816657096
DAI, Xi. “Enforcing law and norms for good citizens: One view of China’s social credit system project”. Development, 63, 38–43, 2020. Doi: https://doi.org/10.1057/s41301-020-00244-2
DIAKOPOULOS, Nick. “Accountability in algorithmic decision making”. Communications of the ACM, 59 (2), 56–62, 2016. DOI: https://doi.org/10.1145/2844110
EISENHARDT, Kathleen M. "Agency Theory: An Assessment and Review", The Academy of Management Review, 14 (1): 57–74, 1989. DOI: https://doi.org/10.5465/amr.1989.4279003
EUBANKS, Virginia. Automating inequality. How high-tech tools profile, police, and punish the poor. New York: St. Martin’s Press, 2018.
FILGUEIRAS, Fernando. “New Pythias of public administration: Ambiguity and choice in AI systems and challenges for governance”. AI & Society, 37 (4), 1473-1486, 2022. DOI: https://doi.org/10.1007/s00146-021-01201-4
FILGUEIRAS, Fernando. “The silent reform: Digital governance as a strategy for state reform in Brazil”. In: LISBOA, Erika; GOMES, Ricardo C.; MARTINS, Humberto F. (eds.). The Brazilian way of doing public administration. Bingley: Emerald, 2023, p. 83-95. DOI: https://doi.org/10.1108/978-1-80262-655-120231008
FILGUEIRAS, Fernando. “Transparency and accountability: Principles and rules for the construction of publicity.” Journal of Public Affairs, 16(2), 192-202, 2016. DOI: https://doi.org/10.1002/pa.1575
FINE LICHT, Karl de; FINE LICHT, Jenny de. “Artificial intelligence, transparency, and public decision-making”. AI & Society, 35 (4), 917–926, 2020. DOI: https://doi.org/10.1007/s00146-020-00960-w
FRISCHMANN, Brett; SELINGER, Evan. Re-engineering humanity. Cambridge: Cambridge University Press, 2018.
GAILMARD, Sean. "Multiple principals and oversight of bureaucratic policy-making". Journal of Theoretical Politics. 21 (2): 161–86, 2009. DOI: https://doi.org/10.1177/0951629808100762
GORWA, Robert; BINNS, Reuben, KATZENBACH, Christian. “Algorithmic content moderation: Technical and political challenges in automation of platform governance”. Big Data & Society, 7 (1), 1–15, 2020. DOI: https://doi.org/10.1177/2053951719897945
INNERARITY, Daniel. “Making the black box society transparent”. AI & Society, 36, 975–981, 2021. DOI: https://doi.org/10.1007/s00146-020-01130-8
ISSAR, Shiv; ANEESH, Aneesh. “What is algorithmic governance?”. Sociology Compass, 16 (1), e12955, 2022. Doi: https://doi.org/10.1111/soc4.12955
JONES, Bryan D.; BAUMGARTNER, Frank R. The politics of attention: How government prioritizes problems. Chicago: The University of Chicago Press, 2005.
KELLEHER, John D. Deep learning. Cambridge: The MIT Press, 2019.
KNUTH, Donald E. The art of computer programming, Volume 1: Fundamental Algorithms. Berkeley: Addison-Wesley, 1968.
KÖNIG, Pascal D.; WENZELBURGER, G. “The legitimacy gap of algorithmic decision-making in the public sector: Why it arises and how to address it”. Technology in Society, 67, 1–10, 2021. DOI: https://doi.org/10.1016/j.techsoc.2021.101688
KROLL, Joshua A.; HUEY, Joanna; BAROCAS, Solon; FELTEN, Edward W.; REIDENBERG, Joel R.; ROBINSON, David G.; YU, Harlan. (2017). Accountable algorithms. University of Pennsylvania Law Review, 165, 633–705. https://scholarship.law.upenn.edu/penn_law_review/vol165/iss3/3
LINDBLOM, Charles. “The science of muddling through”. Public Administration Review, 19 (2), 79-88. DOI: https://doi.org/10.2307/973677
MARKRAM, Henry. “The Blue Brain project”. Nature Reviews Neuroscience, vol. 7, nº 2, p. 153–160, 2006.
MENDONÇA, Ricardo F.; FILGUEIRAS, Fernando; ALMEIDA, Virgilio A. Algorithmic Institutionalism. The Changing Rules of Social + Political Life. Oxford: Oxford University Press, 2023.
MINSKY, Marvim. The Society of Mind. New York: Simon and Schuster, 1985.
OBERMEYER, Ziad; POWERS, Brian; VOGELI, Christine; MULLAINATHAN, Sendhil. “Dissecting racial bias in an algorithm used to manage the health of populations”. Science, 366 (6464), 447–453, 2019. DOI: https://doi.org/10.1126/science.aax2342
PAPYSHEV, Gleb; YARIME, Masaru. “The limitation of ethics-based approaches to regulating artifcial intelligence: regulatory gifting in the context of Russia”. AI & Society, early view, 1-16. DOI: https://doi.org/10.1007/s00146-022-01611-y
PASQUALE, Frank. The black box society. The secret algorithms that control money and information. Cambridge: Harvard University Press, 2015.
RUSSELL, Stuart J. Human compatible: Artificial intelligence and the problem of control. New York: Viking Books, 2019.
RUSSELL, Stuart J.; NORVIG, Peter. Artificial intelligence: A modern approach. Englewood Cliffs, NJ: Prentice-Hall, 2010.
SAMUEL, A.L. “Artificial intelligence: A frontier of automation”. The Annals of the American Academy of Political and Social Science, 340 (1), 10-20, 1962. Doi: https://doi.org/10.1177/000271626234000103
SAMUEL, Arthur. “Some studies in machine learning using the game of checkers.” IBM Journal of Research and Development, vol. 44, nº 1-2, p. 210–229, 1959. Doi: https://doi.org/10.1147/rd.33.0210
SIMON, Herbert A. Models of man: Social and rational. New York: John Wiley, 1957.
SIMON, Herbert A. The sciences of the artificial. Cambridge, MA: MIT Press, 1969.
SIMON, Herbert A. “Artificial intelligence: An empirical science”. Artificial Intelligence, 77 (1), 95-127. Doi: https://doi.org/10.1016/0004-3702(95)00039-H
TSAMADOS, Andreas; AGGARWAL, Nikita; COWLS; Josh, MORLEY, Jessica; ROBERTS, Huw; TADDEO, Mariarosaria; FLORIDI, Luciano. “The ethics of algorithms: key problems and solutions”. AI & Society, 37 (1), 215–230, 2022. DOI: https://doi.org/10.1007/s00146-021-01154-8
TURING, Alan. “Computing machinery and intelligence”. Mind—A Quarterly Review of Psychology and Philosophy, 59(236), 433–460, 1950.
WANG, Pei. “On defining artificial intelligence”. Journal of Artificial General Intelligence, 10 (2), 1-37, 2019. Doi: https://doi.org/10.2478/jagi-2019-0002.
Publicado
2023-12-12
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