Facial recognition in brazilian public security
Ethical challenges, regulatory gaps and proposals for a National Legal framework
DOI:
https://doi.org/10.36776/ribsp.v9i23.338Palavras-chave:
Facial Recognition, public security, artificial intelligence, data protection, algorithmic biasResumo
This article critically examines the regulatory and ethical challenges involved in the use of facial recognition (FR) technologies in Brazilian public security. The investigation is based on a systematic literature review and documentary analysis, revealing a significant regulatory gap. This void compromises not only the protection of personal data but also institutional transparency and the legitimacy of the state's use of such technologies. In a country historically marked by deep social and racial inequalities, the risks associated with algorithmic discrimination, indiscriminate surveillance, and violations of fundamental rights become even more concerning. The study seeks to understand how different countries have addressed these issues, drawing on regulatory models adopted in the European Union, the United States, and China. Based on this comparative analysis, the article proposes guidelines for the development of a national regulatory framework that promotes ethical and responsible governance of technology. Key elements include the implementation of audit mechanisms, oversight by independent bodies, and commitment to the operational efficiency of security forces. The conclusion is that Brazil must adopt a flexible regulatory model guided by principles such as proportionality, transparency, and accountability, ensuring a balance between technological innovation and the protection of constitutional rights and guarantees.
Referências
AI ACT. Artificial Intelligence Act. Regulamento da União Europeia (UE), v. 1689, 2024.
ALLEN, G.; CHAN, T. Artificial intelligence and national security. v. 132. Cambridge, MA: Belfer Center for Science and International Affairs, 2017. Disponível em: https://csdsafrica.org/wp-content/uploads/2020/06/AI-NatSec-final.pdf. Acesso em: 19 out. 2024.
ASSOCIAÇÃO BRASILEIRA DE NORMAS TÉCNICAS (ABNT). Inteligência artificial: conceitos e terminologia. NBR ISO 22989. Rio de Janeiro: ABNT, 2023.
AZEVEDO, C. P. G. de; LIMA, E. M. B. de; SILVA, F. R. da; et al. Nota técnica: análise comparativa entre o anteprojeto de LGPD penal e o PL 1515/2022. Instituto de Referência em Internet e Sociedade (IRIS) e Laboratório de Políticas Públicas e Internet (LAPIN), nov. 2022. Disponível em: https://lapin.org.br. Acesso em: 18 out. 2024.
BAUER, M. W.; GASKELL, G. Pesquisa qualitativa com texto, imagem e som: um manual prático. Petrópolis: Vozes Limitada, 2017.
BARROSO, L. R. Inteligência artificial, plataformas digitais e democracia: Direito e tecnologia no mundo atual. Belo Horizonte: Fórum, 2024.
BINNS, R. Fairness in machine learning: Lessons from political philosophy. In: Conference on fairness, accountability and transparency, 2018, New York. Proceedings [...]. New York: PMLR, 2018. p. 149-159.
BRASIL. Lei nº 12.965, de 23 de abril de 2014. Marco Civil da Internet. Brasília, DF, 2014.
BRASIL. Lei nº 13.709, de 14 de agosto de 2018. Lei Geral de Proteção de Dados Pessoais (LGPD). Brasília, DF, 2018.
BRASIL. Câmara dos Deputados. Projeto de Lei nº 4.612/2019. Disponível em: https://www.camara.leg.br. Acesso em: 10 nov. 2025.
BRASIL. Câmara dos Deputados. Projeto de Lei nº 1515/2022. Disponível em: https://www.camara.leg.br. Acesso em: dez. 2024.
BRUNDAGE, M.; AVIN, S.; WANG, J.; BELFIELD, H.; KRUEGER, G.; HADFIELD, G.; ANDERLJUNG, M. Toward trustworthy AI development: mechanisms for supporting verifiable claims. arXiv preprint, arXiv:2004.07213, 2020. Disponível em: https://arxiv.org/abs/2004.07213. Acesso em: 12 dez. 2024.
BUITEN, M. C. Towards intelligent regulation of artificial intelligence. European Journal of Risk Regulation, v. 10, n. 1, p. 41-59, 2019. Disponível em: https://www.cambridge.org/core/services/aop-cambridge-core/content/view/AF1AD1940B70DB88D2B24202EE933F1B/S1867299X19000084a.pdf/towards_intelligent_regulation_of_artificial_intelligence.pdf. Acesso em: 15 fev. 2025.
BUOLAMWINI, J.; GEBRU, T. Gender shades: Intersectional accuracy disparities in commercial gender classification. In: Conference on fairness, accountability and transparency, 2018, New York. Proceedings [...]. New York: PMLR, 2018. p. 77-91.
BRYSON, J. J. The ethics of artificial intelligence. In: DUBBER, M. D.; PASQUALE, F.; DAS, S. (ed.). The Oxford Handbook of Ethics of AI. Oxford: Oxford University Press, 2019.
CAVOUKIAN, A. Privacy by design: the 7 foundational principles. Ontario: Information and Privacy Commissioner of Ontario, 2009.
CÓBE, R. M.; NONATO, L. G.; NOVAES, S. F.; ZIEBARTH, J. A. Rumo a uma política de Estado para inteligência artificial. Revista USP, n. 124, p. 37-48, 2020. DOI: https://doi.org/10.11606/issn.2316-9036.v0i124p37-48.
CRESWELL, J. W.; CRESWELL, J. D. Projeto de pesquisa: métodos qualitativo, quantitativo e misto. Porto Alegre: Penso, 2014.
CRESWELL, J. W.; CLARK, V. L. P. Designing and conducting mixed methods research. Los Angeles: Sage, 2017.
ESTADOS UNIDOS. Executive Order 13859: Maintaining American Leadership in Artificial Intelligence. 2019. Disponível em: https://www.presidency.ucsb.edu/documents/executive-order-13859-maintaining-american-leadership-artificial-intelligence. Acesso em: 15 fev. 2025.
FINANCIAL TIMES. Met police use of facial recognition in London surges. Financial Times, 19 out. 2024. Disponível em: https://www.ft.com/content/c33322a7-eba7-4299-8172-4ce1d4e88908.
FLORIDI, L. Information ethics, its nature and scope. ACM SIGCAS Computers and Society, v. 36, n. 3, p. 21-36, 2006. DOI: https://doi.org/10.1145/1167344.1167352.
FLORIDI, L. The ethics of information. Oxford: Oxford University Press, 2013.
FLORIDI, L. The Fourth Revolution: How the infosphere is reshaping human reality. Oxford: Oxford University Press, 2014.
FLORIDI, L. et al. AI4 People — an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds and Machines, v. 28, p. 689-707, 2018. Disponível em: https://link.springer.com/content/pdf/10.1007/s11023-018-9482-5.pdf. Acesso em: 15 fev. 2025.
FREITAS, H. Câmeras de reconhecimento facial se multiplicam em São Paulo: medida é aposta do governo estadual e da prefeitura para a área da segurança pública. Veja São Paulo, São Paulo, 27 maio 2024. Disponível em: https://vejasp.abril.com.br/cidades/cameras-reconhecimento-facial-sp/. Acesso em: 2 fev. 2025.
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Copyright (c) 2026 Simone Pereira Duarte Ferreira, Luiz Honorato da Silva Júnior

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