Inteligência artificial e injustiça: para além de uma análise ética encantada dos algoritmos
DOI:
https://doi.org/10.14422/rib.i25.y2024.001Palavras-chave:
bioética, inteligência artificial, injustiça algorítmicaResumo
Não há limites para as expectativas em relação às Inteligências Artificiais (IAs). O que não é consenso é se suas promissoras aplicações, caso se realizem, contemplarão a todos. O objetivo deste trabalho é refletir sobre os desafios éticos na utilização de IA, especialmente aqueles relacionados à justiça. Para isso, após apresentar os aspectos mais comumente levantados na discussão ética em relação a IA, será discutida a maneira diversa com que tais tecnologias podem interagir com contextos e corpos periféricos, representando risco de incremento de desigualdades. A partir dessa constatação, pretende-se não apenas descrever tais riscos, mas também vislumbrar possíveis recursos para enfrentar efeitos negativos das IAs em contextos historicamente vulnerados.
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Aru, J., Larkum, M. E., & Shine, J. M. (2023). The feasibility of artificial consciousness through the lens of neuroscience. Trends in Neurosciences, 46(12), 1008-1017. https://doi.org/10.1016/j.tins.2023.09.009
Benjamin, R. (2019). Assessing risk, automating racism. Science, 366(6464), 421-422. https://doi.org/10.1126/science.aaz3873
Birhane, A. (2021). Algorithmic injustice: a relational ethics approach. Patterns, 2(2), 1-9. https://doi.org/10.1016/j.patter.2021.100205
Buolamwini, J., & Gebru, T. (2018). Gender shades: intersectional accuracy disparities in commercial gender classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 81, 77-91. https://proceedings.mlr.press/v81/buolamwini18a.html
Cabitza, F., Rasoini, R., & Gensini, G. F. (2017). Unintended consequences of machine learning in medicine. The Journal of the American Medical Association, 318(6), 517-518. https://doi.org/10.1001/jama.2017.7797
Cambraia, L., Pyrrho, M., & Manchola-Castillo, C. (2023). Big Data e saúde: uma análise bioética. Teseo Press. https://doi.org/10.55778/ts911693147
Cerdeña, J. P., Plaisime, M. V., & Tsai, J. (2020). From race-based to race-conscious medicine: how anti-racist uprisings call us to act. The Lancet, 396(10257), 1125-1128. https://doi.org/10.1016/S0140-6736(20)32076-6
Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148
Dalton-Brown, S. (2020). The ethics of medical AI and the physician-patient relationship. Cambridge Quarterly of Healthcare Ethics, 29(1), 115-121. https://doi.org/10.1017/S0963180119000847
Dastin, J. (2018, October 10). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters. https://www.reuters.com/article/idUSKCN1MK0AG/
Dick, S. (2019). Artificial Intelligence. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.92fe150c
Faustino, D., & Lippold, W. (2023). Colonialismo digital: por uma crítica hacker-fanoniana. Boitempo Editorial.
Floridi, L. (2015). Singularitarians, aitheists, and why the problem with artificial intelligence is HAL (humanity at large), not HAL. Philosophy and Computers, 14(2), 8-11.
Garrafa, V. (2022). Bioética y transdisciplinariedad como puentes de diálogo entre las ciencias de la salud, las ciencias sociales y/o humanas en el contexto de la evaluación ética de investigaciones. Salud colectiva, 18, e4177. https://doi.org/10.18294/sc.2022.4177
Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Iii, H. D., & Crawford, K. (2021). Datasheets for datasets. Communications of the ACM, 64(12), 86-92. https://doi.org/10.1145/3458723
Hottois, G. (2020). ¿Qué es la bioética? Universidad del Bosque.
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. https://doi.org/10.1038/s42256-019-0088-2
Khazanchi, R., Soled, D. R., & Yearby, R. (2023). Racism-conscious praxis: a framework to materialize anti-oppression in medicine, public health, and health policy. The American Journal of Bioethics, 23(4), 31-34. https://doi.org/10.1080/15265161.2023.2186521
McArthur, N. (2023a). AI worship as a new form of religion. PhilPapers. https://philarchive.org/rec/MCAAWA
McArthur, N. (2023b, March 15). Gods in the machine? The rise of Artificial Intelligence may result in new religions. The Conversation. https://theconversation.com/gods-in-the-machine-the-rise-of-artificial-intelligence-may-result-in-new-religions-201068
McLean, S., Read, G. J., Thompson, J., Baber, C., Stanton, N. A., & Salmon, P. M. (2023). The risks associated with Artificial General Intelligence: a systematic review. Journal of Experimental & Theoretical Artificial Intelligence, 35(5), 649-663. https://doi.org/10.1080/0952813X.2021.1964003
Mittelstadt, B. D., & Floridi, L. (2016). The ethics of Big Data: current and foreseeable issues in biomedical contexts. Science and Engineering Ethics, 22(2), 303-341.
Mohamed, S., Png, M. T., & Isaac, W. (2020). Decolonial AI: decolonial theory as sociotechnical foresight in artificial intelligence. Philosophy & Technology, 33, 659-684. https://doi.org/10.1007/s13347-020-00405-8
Munn, L. (2023). The uselessness of AI ethics. AI and Ethics, 3, 869-877. https://doi.org/10.1007/s43681-022-00209-w
Neff, G. (2013). Why Big Data won’t cure us. Big Data, 1(3), 117-123. https://doi.org/10.1089/big.2013.0029
Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. https://doi.org/10.1126/science.aax2342
Pyrrho, M., Cambraia, L., & de Vasconcelos, V. F. (2022a). Privacy and health practices in the digital age. The American Journal of Bioethics, 22(7), 50-59. https://doi.org/10.1080/15265161.2022.2040648
Pyrrho, M., Cambraia, L., & de Vasconcelos, V. F. (2022b). Response to open peer commentaries on “Privacy and health practices in the digital age”. The American Journal of Bioethics, 22(12), W5-W8. https://doi.org/10.1080/15265161.2022.2127972
Quijano, A. (2000). Colonialidad del poder, eurocentrismo y América Latina. En E. Lander (Ed.), La colonialidad del saber: eurocentrismo y ciencias sociales. Perspectivas Latinoamericanas (p. 118). CLACSO.
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J. F., Breazeal, C., ... & Wellman, M. (2019). Machine behaviour. Nature, 568(7753), 477-486. https://doi.org/10.1038/s41586-019-1138-y
Russell, S., & Norvig, P. (2013). Inteligência Artificial. Elsevier.
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of Artificial Intelligence in healthcare: a structured literature review. BMC Medical Informatics and Decision Making, 21, 125. https://doi.org/10.1186/s12911-021-01488-9
Siau, K., & Wang, W. (2020). Artificial Intelligence (AI) ethics: ethics of AI and ethical AI. Journal of Database Management, 31(2), 74-87. https://doi.org/10.4018/JDM.2020040105
Silva, T. (2020). Racismo algorítmico em plataformas digitais: microagressões e discriminação em código. Em T. Silva (Ed.), Comunidades, algoritmos e ativismos digitais: olhares afrodiaspóricos (pp. 121-135). LiteraRUA.
Sjoding, M. W., Dickson, R. P., Iwashyna, T. J., Gay, S. E., & Valley, T. S. (2020). Racial bias in pulse oximetry measurement. New England Journal of Medicine, 383(25), 2477-2478. https://doi.org/10.1056/NEJMc2029240
Vayena, E., Blasimme, A., & Cohen, I. G. (2018). Machine learning in medicine: addressing ethical challenges. PLoS Medicine, 15(11), e1002689. https://doi.org/10.1371/journal.pmed.1002689
Wilson, B., Hoffman, J., & Morgenstern, J. (2019). Predictive inequity in object detection. arXiv preprint arXiv:1902.11097. https://doi.org/10.48550/arXiv.1902.11097
Zuboff, S. (2019). A era do capitalismo de vigilância. Intrínseca.
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Copyright (c) 2024 Leonardo Cambraia, Monique Pyrrho
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