Inteligência artificial aplicada ao direito e o direito da inteligência artificial

Autores/as

DOI:

https://doi.org/10.53798/suprema.2021.v1.n1.a20

Palabras clave:

proteção de dados, inteligência artificial, decisões automatizadas, automação jurídica, regulação da inteligência artificial

Resumen

O desenvolvimento de tecnologias de inteligência artificial é relevante para o Direito por duas razões distintas, mas relacionadas. De um lado, a adoção de tecnologias inteligentes em aplicações no setor público e privado, em especial em contextos de tomada de decisão automatizada, atrai demandas regulatórias para o surgimento de um Direito da inteligência artificial; de outro, o próprio Direito surge como um domínio para a aplicação da inteligência artificial, que tem o potencial de impactar as profissões jurídicas. O presente artigo examina o estado atual da literatura a respeito desses dois temas e a interconexão entre essas duas perspectivas a respeito do fenômeno da inteligência artificial. Ao examinar possíveis soluções para os problemas regulatórios e de aplicação, o artigo propõe temas para a pesquisa na interface entre Direito e tecnologia e ressalta a importância de pesquisas que integrem estas perspectivas, envolvendo pesquisadores de diversas áreas em torno das questões jurídicas.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

ABRUSIO, Juliana. Proteção de dados na cultura do algoritmo. São Paulo: Editora D’Plácido, 2020.

ALETRAS, Nikolaos et al. Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective. PeerJ Computer Science, v. 2, e93, 2016.

ALEVEN, Vincent. Using background knowledge in case-based legal reasoning: a computational model and an intelligent learning environment. Artificial Intelligence, n. 150, 2003.

ALMADA, Marco. Human intervention in automated decision-making: toward the construction of contestable systems. In: INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW (ICAIL 2019), 17., 2019, Montreal. Proceedings […]. Nova York: ACM Press, 2019.

ALMADA, Marco; ATTUX, Romis. Ethical design of social simulations. In: WORKSHOP SOBRE ASPECTOS SOCIAIS, HUMANOS E ECONÔMICOS DE SOFTWARE (WASHES 2018), 3. 2018, Porto Alegre, RS. Anais [...]. Porto Alegre: SBC, 2018. Disponível em: https://sol.sbc.org.br/index.php/washes/issue/view/218. Acesso em: 20 abr. 2021.

ALMADA, Marco; MARANHÃO, Juliano; SARTOR, Giovanni. Article 25. Data protection by design and by default. In: SPIECKER GEN. DÖHMANN, Indra; PAPAKONSTANTINOU, Vagelis; HORNUNG, Gerrit; DE HERT, Paul (orgs.). European General Data Protection Regulation. Baden-Baden: Nomos, no prelo.

ASHLEY, Kevin. Modeling legal argument: reasoning with cases and hypotheticals. Cambridge: MIT Press, 1990.

ASHLEY, Kevin; FALAKMASIR, Mohammad Hassan. Utilizing vector space models for identifying legal factors from text. In: INTERNATIONAL CONFERENCE ON LEGAL KNOWLEDGE AND INFORMATION SYSTEMS - JURIX 2017, 30., 2017, Luxembourg. Proceedings […]. Netherlands: IOS Press, 2017.

BAYAMLIOĞLU, Emre. Contesting automated decisions. European Data Protection Law Review (EDPL), v. 4, p. 433-446, 2018.

BAYAMLIOĞLU, Emre; LEENES, Ronald. The ‘rule of law’ implications of data-driven decision-making: a techno-regulatory perspective. Law, Innovation and Technology, v. 10, n. 2, p. 295-313, 2018.

BENCH-CAPON, Trevor J. M. The missing link revisited: the role of teleology in representing legal argument. Artificial Intelligence and Law, v. 10, p. 79-94, 2002.

BENCH-CAPON, Trevor J.M.; PRAKKEN, Henry. Using argument schemes for hypothetical reasoning in law. Artificial Intelligence and Law, v. 18, p. 153-174, 2010.

BEX, Floris J. et al. Towards a formal account of reasoning about evidence: argumentation schemes and generalisations. Artificial Intelligence and Law, v. 11, p. 125-165, 2003.

BIETTI, Elettra. From ethics washing to ethics bashing: a view on tech ethics from within moral philosophy. In: CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY – FAT*’20, 2020, Barcelona. Proceedings […]. New York: Association for Computing Machinery, 2020. p. 210-219.

BREY, Philip A. E. Anticipatory ethics for emerging technologies. NanoEthics, v. 6, n. 1, p. 1-13, 2012.

BRYSON, Joanna J.; THEODOROU, Andreas. How society can maintain human-centric artificial intelligence. In: TOIVONEN, Marja; SAARI, Eveliina (org.). Human-centered digitalization and services. Singapore: Springer Singapore, 2019. p. 305-323.

BURGESS, Peter et al. Towards a digital ethics. Bruxelas: Ethics Advisory Group, 2018.

BURRELL, Jenna. How the machine ‘thinks’: understanding opacity in machine learning algorithms. Big Data & Society, v. 3, n. 1, p. 1-12, 2016.

CAPLAN, Robyn et al. Algorithmic accountability: a primer. Data & Society, 2018. Disponível em: https://datasociety.net/output/algorithmic-accountability-a-primer/. Acesso em: 26 ago. 2018.

COMISSÃO EUROPEIA. COMUNICAÇÃO DA COMISSÃO AO PARLAMENTO EUROPEU, AO CONSELHO EUROPEU, AO CONSELHO, AO COMITÉ ECONÓMICO E SOCIAL E AO COMITÉ DAS REGIÕES. Plano Coordenado para a Inteligência Artificial. Disponível em: https://eur-lex.europa.eu/legal-content/PT/TXT/HTML/?uri=CELEX:52018DC0795&from=EN. Acesso em: 30 mai. abr. 2021. Número de referência COM: COM(2018)795 PT.

COMISSÃO EUROPEIA. Proposal for a Regulation on a European approach for Artificial Intelligence. Bruxelas: Comissão Europeia, 2021. Disponível em: https://digital-strategy.ec.europa.eu/en/library/proposal-regulation-laying-down-harmonised-rules-artificial-intelligence. Acesso em: 30 mai. de 2021.

CONSELHO NACIONAL DE JUSTIÇA. Inteligência artificial no Poder Judiciário. Brasília, 2019. 40p. Disponível em: https://www.cnj.jus.br/wp-content/uploads/2020/05/Inteligencia_artificial_no_poder_judiciario_brasileiro_2019-11-22.pdf. Acesso em: 20 abr. 2021.

CONTISSA, Giuseppe et al. CLAUDETTE meets GDPR: automating the evaluation of privacy policies using Artificial Intelligence. Brussels: European Consumer Organisation, (BEUC), 2018. Disponível em: https://www.beuc.eu/publications/beuc-x-2018-066_claudette_meets_gdpr_report.pdf. Acesso em: 20 abr. 2021.

CORMEN, Thomas H. et al. Introduction to algorithms. 3. ed. Cambridge: The MIT Press, 2009. p. 5-6.

DIGNUM, Virginia et al. Ethics by design: necessity or curse? In: THE 2018 AAAI/ACM CONFERENCE ON AI, ETHICS, AND SOCIETY, 2018, New Orleans. Proceedings […]. New York: Association for Computer Machinery, 2018. p. 60-66.

DONEDA, Danilo Cesar Maganhoto et al. Considerações iniciais sobre inteligência artificial, ética e autonomia pessoal. Pensar - Revista de Ciências Jurídicas, v. 23, n. 4, p. 1-17, 2018.

ECKART DE CASTILHO, Richard. A legal perspective on training models for natural language processing. In: INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 11., 2018, Miyazaki, Japan. [Proceedings…]: LREC-2018). [s.l.], 2018.

FEENBERG, Andrew. Subversive rationalization: technology, power, and democracy. Inquiry, v. 35, n. 3-4, p. 301-322, 1992.

FLORIDI, Luciano; STRAIT, Andrew. Ethical foresight analysis: what it is and why it is needed? Minds and Machines, v. 30, n. 1, p. 77-97, 2020.

FLORIDI, Luciano, et al. AI4People: an ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds and Machines, v. 28, 2018.

FRAZÃO, Ana; MULHOLLAND, Caitlin (org.). Inteligência artificial e Direito: ética, regulação e responsabilidade. 1. ed. São Paulo: Thomson Reuters Brasil, 2019.

FUX, Luiz; ÁVILA, Henrique; CABRAL, Trícia Navarro Xavier (org.). Tecnologia e Justiça multiportas: teoria e prática. Indaiatuba: Editora Foco, 2021.

GOMES, Rodrigo Dias de Pinho. Big data: desafios à tutela da pessoa humana na sociedade da informação. Rio de Janeiro: Lumen Juris, 2017.

GRABMAIR, Matthias. Predicting trade secret case outcomes using argument schemes and learned quantitative value effect tradeoffs. INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW (ICAIL 2017), 16., 2017, London. Proceedings […].. New York: Association for Computing Machinery, 2017. p. 89-98.

HAGE, Jaap C. Comparing alternatives in the law. Artificial Intelligence and Law, v. 12, p. 181-225, 2005.

HAYKIN, Simon. Neural networks and learning machines. 3. Ed. [New Jersey]: Prentice Hall, 2008. p. 34-35.

HILDEBRANDT, Mireille. Privacy as protection of the incomputable self: from agnostic to agonistic machine learning. Theoretical Inquiries in Law, v. 20, n. 1, 2019.

HILPINEN, Risto; MCNAMARA, Paul. Deontic Logic: a historical survey and introduction. In: GABBAY, Dov et al. (orgs.). Handbook of deontic logic and normative systems. London: College Publications, 2013.

HORTY, John F. Rules and reasons in the theory of precedent. Legal Theory, v. 17, 2011.

HORTY, John F.; BENCH-CAPON, Trevor J. A factor-based definition of precedential constraint. Artificial Intelligence and Law, v. 20, p. 181-214, 2012.

JOBIN, Anna; IENCA, Marcello; VAYENA, Effy. The global landscape of AI ethics guidelines. Nature Machine Intelligence, v. 1, p. 389-399, 2019.

KAMINSKI, Margot. The right to explanation, explained. Berkeley Technology Law Journal, v. 34, n. 1, 2019.

KEENEY, Ralph L.; RAIFFA, Howard. Decisions with multiple objectives. New York: Wiley, 1976.

KOENE, Ansgar et al. A governance framework for algorithmic accountability and transparency. Brussels: European Union, 2019. Disponível em: https://www.europarl.europa.eu/RegData/etudes/STUD/2019/624262/EPRS_STU(2019)624262_EN.pdf. Acesso em: 20 abr. 2021.

KUZNIACKI, Blazej. The artificial intelligence tax treaty assistant: decoding the principal purpose test. Bulletin for International Taxation, v. 72, n. 9, 2018.

LARSON, Christina. Who needs democracy when you have data? MIT Technology Review, 20 Aug. 2018. Disponível em: https://www.technologyreview.com/2018/08/20/240293/who-needs-democracy-when-you-have-data/. Acesso em: 20 abr. 2021.

LEHR, David; OHM, Paul. Playing with the data: what legal scholars should learn about machine learning. University of California Davis Law Review, v. 51, p. 653-717, 2017.

MACHADO, Henrique Felix de Souza. Algoritmos, regulação e governança: uma revisão de literatura. Journal of Law and Regulation, v. 4, n. 1, p. 39-62, 2018.

MARANHÃO, Juliano; ALMADA, Marco. Inteligência artificial no setor de saúde: ética e proteção de dados. In: DALLARI, Analluza Bolivar; MONACO, Gustavo Ferraz de Campos (org.). LGPD na Saúde. 1. ed. São Paulo: Thomson Reuters Brasil, 2021.

MARANHÃO, Juliano; COUTINHO, Diogo R. Melhor investir do que regular. Correio Braziliense, 25 de março de 2019.

MARANHÃO, Juliano; SARTOR, Giovanni. Value assessment and revision in legal interpretation. In: INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW (ICAIL 2019), 17., 2019, Montreal. Proceedings […]. New York: ACM Press, 2019.

MEDVEDEVA, Masha; VOLS, Michel; WIELING, Martijn. Using machine learning to predict decisions of the European Court of Human Rights. Artificial Intelligence and Law, v. 28, p. 237-266, 2020. Disponível em: https://link.springer.com/content/pdf/10.1007/s10506-019-09255-y.pdf. Acesso em: 20 abr. 2021.

MENDES, Laura Schertel; MATTIUZZO, Marcela. Discriminação algorítmica: conceito, fundamento legal e tipologia. Direito Público, v. 16, n. 90, p. 39-64, 2019. Disponível em: https://www.portaldeperiodicos.idp.edu.br/direitopublico/article/view/3766/Schertel%20Mendes%3B%20Mattiuzzo%2C%202019. Acesso em: 20 abr. 2021.

OLIVEIRA, Rafael Brito de. Utilização de ontologias para busca em base de dados de acórdãos do STF. 2017. Dissertação (Mestrado em Ciências da Computação) – Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, 2017.

ONG, Rebecca. Recognition of the right to privacy on the Internet in China. International Data Privacy Law, v.1, n. 3, 2011.

PALAU, Raquel Mochales; MOENS, Marie-Francine. Argumentation mining: the detection, classification and structuring of arguments in text. In: INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW (ICAIL 2009), 12., 2009, Barcelona. Proceedings […]. New York: Association for Computing Machinery, 2009. Disponível em: https://dl.acm.org/doi/proceedings/10.1145/1568234. Acesso em: 20 abr. 2021.

PASQUALE, Frank. The black box society: the secret algorithms that control money and information. Cambridge: Harvard University Press, 2015.

PATHAK, Arkanath; GOYAL, Pawan; BHOWMICK, Plaban. A two-phase approach towards identifying argument structure in Natural Language. In: WORKSHOP ON NATURAL LANGUAGE PROCESSING TECHNIQUES FOR EDUCATIONAL APLICATIONS, 3., 2016, Osaka. Proceedings of the NLPTEA 2016 Workshop. Osaka, 2016. Disponível em: https://www.aclweb.org/anthology/W16-49.pdf. Acesso em: 20 abr. 2021.

PRAKKEN, Henry; SARTOR, Giovanni. A dialectical model of assessing conflicting arguments in legal reasoning. Artificial Intelligence and Law, v. 4, p. 331-368, 1996.

PRAKKEN, Henry et al. A formalisation of argumentation schemes for legal case-based reasoning in ASPIC+. Journal of Logic and Computation, v. 25, n. 5, p. 1141-1166, 2015.

RUSSELL, Stuart J.; NORVIG, Peter. Artificial intelligence: a modern approach. 3. ed. Upper Saddle River: Prentice Hall, 2010. p. 234.

SALOMÃO, Luiz Felipe (coord.). Tecnologia aplicada à gestão dos conflitos no âmbito do Poder Judiciário brasileiro. Rio de Janeiro: Centro de Inovação, Administração e Pesquisa do Judiciário da Fundação Getúlio Vargas, 2020. Disponível em: https://ciapj.fgv.br/sites/ciapj.fgv.br/files/estudos_e_pesquisas_ia_1afase.pdf. Acesso em: 20 abr. 2021.

SARRA, Claudio. Put dialectics into the machine: protection against automatic-decision-making through a deeper understanding of contestability by design. Global Jurist, v. 20, n. 3, 2020.

SARTOR, Giovanni. Fundamental legal concepts: A formal and teleological characterisation. Artificial Intelligence and Law, v. 21, pp. 101-142, 2010.

SARTOR, Giovanni. The logic of proportionality: reasoning with non-numerical magnitudes. German Law Journal, v. 14, 2013.

SIMÕES-GOMES, Letícia; ROBERTO, Enrico; MENDONÇA, Jônatas. Viés algorítmico – um balanço provisório. Estudos de Sociologia, v. 25, n. 48, 2020.

SINGH, Jatinder et al.Responsibility and machine learning: part of a process. SSRN, 2016. p. 7. Disponível em: https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2860048_code2330375.pdf?abstractid=2860048&mirid=1. Acesso em: 20 abr. 2021.

STRANDBURG, Katherine J. Rulemaking and inscrutable automated decision tools. Columbia Law Review, v. 119, n. 7, p. 1851-1886, 2019.

SWANDA, Gus. The Deficiencies of a Westphalian model for cyberspace: a case study of South Korean cyber security. International Journal of Korean Unification Studies, v. 25, n. 2, 2016.

TREVELIN, Bruna et al. Acesso a dados de processos judiciais no Brasil. São Paulo: Lawgorithm, 2020.

VAN DE POEL, Ibo. Core values and value conflicts in cybersecurity: beyond privacy versus security. In: CHRISTEN, Markus; GORDIJN, Bert; LOI, Michele (org.). The ethics of cybersecurity. Cham: Springer International Publishing, 2020. p. 45-71. (The International Library of Ethics, Law and Technology, 21)

VERHEIJ, Bart et al. Arguments, scenarios and probabilities: connections between three normative frameworks for evidential reasoning. Law, Probability & Risk, v. 15, p. 35-70, 2016.

VERMA, S., PARTHASARATHY, A., CHEN, D. The genealogy of ideology: predicting agreements and persuasive memes in the U.S. Courts of Appeals. INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND LAW (ICAIL 2017), 16., 2017, London. Proceedings […].. New York: Association for Computing Machinery, 2017.

VLEK, Charlotte S. Building bayesian networks for legal evidence with narratives: a case study evaluation. Artificial Intelligence and Law, v. 22, n. 4, p. 375-421, 2014.

WAGNER, Ben. Ethics as an escape from regulation: from ethics-washing to ethics-shopping? In: HILDEBRANDT, Mireille (ed.). Being profiled: cogitas ergo sum. Amsterdam: Amsterdam University Press, 2018.

WARDMAN, Jamie K.; LÖFSTEDT, Ragnar. Anticipating or accommodating to public concern? risk amplification and the politics of precaution reexamined. Risk Analysis, v. 38, n. 9, p. 1802-1819, 2018.

Publicado

2021-06-30

Cómo citar

SOUZA DE ALBUQUERQUE MARANHÃO, Juliano; ABRUSIO FLORÊNCIO, Juliana; ALMADA, Marco. Inteligência artificial aplicada ao direito e o direito da inteligência artificial. Suprema - Revista de Estudos Constitucionais, Distrito Federal, Brasil, v. 1, n. 1, p. 154–180, 2021. DOI: 10.53798/suprema.2021.v1.n1.a20. Disponível em: https://suprema.stf.jus.br/index.php/suprema/article/view/20. Acesso em: 22 dic. 2024.

Artículos similares

1 2 3 4 5 > >> 

También puede Iniciar una búsqueda de similitud avanzada para este artículo.