Dynamic models applied to learning values in artificial intelligence

Authors

DOI:

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

Keywords:

Artificial Intelligence, Learning values., Cognitive science, Dynamical systems.

Abstract

experts in Artificial Intelligence (AI) development predict that advances in the development of intelligent systems and agents will reshape vital areas in our society. Nevertheless, if such an advance is not made prudently and critically-reflexively, it can result in negative outcomes for humanity. For this reason, several researchers in the area have developed a robust, beneficial, and safe concept of AI for the preservation of humanity and the environment. Currently, several of the open problems in the field of AI research arise from the difficulty of avoiding unwanted behaviors of intelligent agents and systems, and at the same time specifying what we really want such systems to do, especially when we look for the possibility of intelligent agents acting in several domains over the long term. It is of utmost importance that artificial intelligent agents have their values aligned with human values, given the fact that we cannot expect an AI to develop
human moral values simply because of its intelligence, as discussed in the Orthogonality Thesis. Perhaps this difficulty comes from the way we are addressing the problem of expressing objectives, values, and ends, using representational cognitive methods. A solution to this problem would be the dynamic approach proposed by Dreyfus, whose phenomenological philosophy shows that the human experience of being-in-the-world in several aspects is not well represented by the symbolic or connectionist cognitive method, especially in regards to the question of learning values. A possible approach to this problem would be to use theoretical models such as SED (situated embodied dynamics) to address the values learning problem in AI.

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Author Biographies

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). Dynamic models applied to learning values in artificial intelligence. Veritas (Porto Alegre), 65(2), e37439. https://doi.org/10.15448/1984-6746.2020.2.37439

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Vol. 65 No. 2 (2020)

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Varia

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