Modelos Dinâmicos Aplicados à Aprendizagem de Valores em Inteligência Artificial

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DOI:

https://doi.org/10.15448/1984-6746.2020.2.37439

Palavras-chave:

Inteligência Artificial, Aprendizagem de Valores, Ciência Cognitiva, Sistemas Dinâmicos.

Resumo

Especialistas em desenvolvimento de Inteligência Artificial (IA) prevêem que o avanço no desenvolvimento de sistemas e agentes inteligentes irá remodelar áreas vitais em nossa sociedade. Contudo, se tal avanço não for realizado de maneira prudente e crítico-reflexiva, pode resultar em desfechos negativos para a humanidade. Por este motivo, diversos pesquisadores na área têm desenvolvido uma concepção de IA robusta, benéfica e segura para a preservação da humanidade e do meio-ambiente. Atualmente, diversos dos problemas em aberto no campo de pesquisa em IA advêm da dificuldade de evitar comportamentos indesejados de agentes e sistemas inteligentes, e ao mesmo tempo especificar o que realmente  queremos que tais sistemas façam, especialmente quando prospectamos a possibilidade de agentes inteligentes atuarem em vários domínios ao longo prazo. É de suma importância que agentes inteligentes artificiais tenham seus valores alinhados com os valores humanos, dado ao fato de que não podemos esperar que uma IA desenvolva valores morais humanos por conta de sua inteligência, conforme é discutido na Tese da Ortogonalidade. Talvez tal dificuldade venha da maneira que estamos abordando o problema de expressar objetivos, valores e metas, utilizando de métodos cognitivos representacionais.  Uma solução para este problema seria a abordagem dinâmica proposta por Dreyfus, que com base na filosofia fenomenológica mostra que a experiência humana do ser-no-mundo em diversos aspectos não é bem representada pelo método cognitivo simbólico ou conexionista, especialmente na questão de aprendizagem de valores. Uma possível abordagem para esse problema seria a utilização de modelos téoricos como SED (situated embodied dynamics) para abordar o porblema de aprendizagem de valores em IA.

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Biografia do Autor

Nicholas Kluge Corrêa, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS.

Mestre em Engenharia Elétrica pela Pontifícia Universidade Católica do Rio Grande do Sul (Escola Politécnica, PUCRS, Porto Alegre, RS, Brasil) e doutorando em Filosofia (PUCRS) Porto Alegre, RS, Brasil. Bolsista CAPES/PROEX.

Nythamar de Oliveira, Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS.

Ph.D. in Philosophy (State University of New York). Professor titular da Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, RS.

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2020-07-27

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Corrêa, N. K., & de Oliveira, N. (2020). Modelos Dinâmicos Aplicados à Aprendizagem de Valores em Inteligência Artificial. Veritas (Porto Alegre), 65(2), e37439. https://doi.org/10.15448/1984-6746.2020.2.37439

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