CONTROVERSIAS SOBRE DAÑO ALGORÍTMIC: discursos corporativos sobre discriminación codificada
DOI:
https://doi.org/10.20873/uft.2447-4266.2020v6n4a1ptPalabras clave:
Algoritmos; Auditoría algorítmica; Explicabilidad; Periodismo Tecnológico; Plataformas.Resumen
Los impactos y daños discriminatorios por sistemas algorítmicos han abierto discusiones sobre el alcance de responsabilidad de las empresas de tecnología de la comunicación e inteligencia artificial. El artículo presenta controversias públicas desencadenadas por ocho casos públicos de daño y discriminación algorítmica que generaron respuestas públicas por parte de las empresas, abordando los esfuerzos realizados por ellas en enmarcar el debate sobre la responsabilidad en el transcurso de la planeamento, alimentación con dadtos e implementación de sistemas. A continuación, se analiza cómo la opacidad de los sistemas es defendida por las empresas comerciales que los desarrollan, alegando prerrogativas como los “secretos de la industria” y la inescrutabilidad algorítmica.
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BROCK, Andre. Análise Crítica Tecnocultural do Discurso. In: SILVA, T. Comunidades, Algoritmos e Ativismos Digitais: olhares afrodiaspóricos. São Paulo, LiteraRUA, 2020.
BUCHER, Taina. The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms. Information, Communication & Society, v. 20, n. 1, p. 30-44, 2016b.
BUCHER, Taina. Neither black nor box: ways of knowing algorithms. In: KUBITSCHKO, S. & KAUN, A. (orgs.) Innovative methods in media and communication research. Palgrave Macmillan, Cham, 2016b. p. 81-98.
BUOLAMWINI, Joy; GEBRU, Timnit. Gender shades: Intersectional accuracy disparities in commercial gender classification. In: Proceeedings of Conference on fairness, accountability and transparency, 2018. pp. 77-91.
DIAKOPOULOS, Nicholas. Accountability in algorithmic decision making. Communications of the ACM, v. 59, n. 2, p. 56-62, 2016.
EPSTEIN, Ziv et al. Closing the AI Knowledge Gap. arXiv preprint arXiv:1803.07233, 2018.
ESLAMI, Motahhare et al. I always assumed that I wasn't really that close to [her]: Reasoning about Invisible Algorithms in News Feeds. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems. ACM, 2015. p. 153-162
FRANCE PRESS. (2019). San Francisco proíbe a polícia de usar reconhecimento facial Oito dos nove conselheiros municipais são contrários à tecnologia. G1, 16/05/2019, online. Disponível em: https://g1.globo.com/pop-arte/noticia/2019/05/16/san-francisco-proibe-a-policia-de-usar-reconhecimento-facial.ghtml Acesso em 22/04/2020.
GILLESPIE, Tarleton. A relevância dos algoritmos. Parágrafo, 6(1), 2018, pp. 95-121.
GUNNING, D. Broad Agency Announcement Explainable Artificial Intelligence (XAI). Technical report, 2016.
GUNNING, David. Explainable artificial intelligence (xai) Program. AI Magazine, v. 40, n. 2, 2019. pp.44-58.
LATOUR, Bruno. Why has critique run out of steam? From matters of fact to matters of concern. Critical inquiry, v. 30, n. 2, p. 225-248, 2004.
LATOUR, Bruno. Reassembling the Social: An Introduction to Actor-Network-Theory. New York: Oxford University Press, 2005..
NOBLE, Safiya Umoja. Searching for Black Girls: Ranking Race and Gender in Commercial Search Engines. Tese de Doutorado defenfida na Urbana-Champaign: University of Illinois at Urbana-Champaign, 2011.
NOBLE, Safiya Umoja. Algorithms of oppression: How search engines reinforce racism. New York: NYU Press, 2018.
PASQUALE, Frank. The black box society. Harvard University Press, 2015.
PASQUALE, Frank. Toward a Fourth Law of Robotics: Preserving Attribution, Responsibility, and Explainability in an Algorithmic Society. Ohio St. LJ, v. 78, p. 1243, 2017.
RAJI, Inioluwa Deborah; BUOLAMWINI, Joy. Actionable auditing: Investigating the impact of publicly naming biased performance results of commercial ai products. In: AAAI/ACM Conf. on AI Ethics and Society, 2019.
RIBEIRO, Manoel Horta et al. Auditing radicalization pathways on youtube. arXiv preprint arXiv:1908.08313, 2019.
RIEDER, Bernhard; MATAMOROS-FERNÁNDEZ, Ariadna; COROMINA, Òscar. From ranking algorithms to ‘ranking cultures’ Investigating the modulation of visibility in YouTube search results. Convergence, v. 24, n. 1, p. 50-68, 2018.
ROMANI, Cristóbal C.; KUKLINSKI, Hugo P. Planeta Web 2.0: Inteligencia colectiva o medios fast food. Barcelona: Grup de Recerca d’Interaccions Digitals, Universitat de Vic. Flacso, 2007.
RUBEL, Alan; PHAM, Adam; CASTRO, Clinton. Agency Laundering and Algorithmic Decision Systems. In: International Conference on Information. Springer, Cham, 2019. p. 590-598.
SANDVIG, Christian et al. Auditing algorithms: Research methods for detecting discrimination on internet platforms. Data and discrimination: converting critical concerns into productive inquiry, v. 22, 2014.
SEAVER, N. Knowing Algorithms. In: VERTESI, J.; RIBES, D. (orgs.) digitalSTS: A Field Guide for Science & Technology Studies. Princeton Univrsity Press, 2019. pp.412-422.
SILVEIRA, S. A. Democracia e os códigos invisíveis: como os algoritmos estão modulando comportamentos e escolhas políticas. São Paulo: Edições SESC-SP, 2019.
SRNICEK, Nick. Platform capitalism. John Wiley & Sons, 2017.
SWEENEY, Latanya. Discrimination in online ad delivery. arXiv preprint arXiv:1301.6822, 2013.
VAN DIJCK, José. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society, 12(2), 2014. pp. 197-208.
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