Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence

Detalhes bibliográficos
Autor(a) principal: Possati, Luca
Data de Publicação: 2021
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/138353
Resumo: The core hypothesis of this paper is that neuropsychoanalysis provides a new paradigm for artificial general intelligence (AGI). The AGI agenda could be greatly advanced if it were grounded in affective neuroscience and neuropsychoanalysis rather than cognitive science. Research in AGI has so far remained too cortical-centric; that is, it has privileged the activities of the cerebral cortex, the outermost part of our brain, and the main cognitive functions. Neuropsychoanalysis and affective neuroscience, on the other hand, affirm the centrality of emotions and affects-i.e., the subcortical area that represents the deepest and most ancient part of the brain in psychic life. The aim of this paper is to define some general design principles of an AGI system based on the brain/mind relationship model formulated in the works of Mark Solms and Jaak Panksepp. In particular, the paper analyzes Panksepp's seven effective systems and how they can be embedded into an AGI system through Judea Pearl's causal analysis. In the conclusions, the author explains why building a sub-cortical AGI is the best way to solve the problem of AI control. This paper is intended to be an original contribution to the discussion on AGI by elaborating positive arguments in favor of it.
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spelling Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligenceThe core hypothesis of this paper is that neuropsychoanalysis provides a new paradigm for artificial general intelligence (AGI). The AGI agenda could be greatly advanced if it were grounded in affective neuroscience and neuropsychoanalysis rather than cognitive science. Research in AGI has so far remained too cortical-centric; that is, it has privileged the activities of the cerebral cortex, the outermost part of our brain, and the main cognitive functions. Neuropsychoanalysis and affective neuroscience, on the other hand, affirm the centrality of emotions and affects-i.e., the subcortical area that represents the deepest and most ancient part of the brain in psychic life. The aim of this paper is to define some general design principles of an AGI system based on the brain/mind relationship model formulated in the works of Mark Solms and Jaak Panksepp. In particular, the paper analyzes Panksepp's seven effective systems and how they can be embedded into an AGI system through Judea Pearl's causal analysis. In the conclusions, the author explains why building a sub-cortical AGI is the best way to solve the problem of AI control. This paper is intended to be an original contribution to the discussion on AGI by elaborating positive arguments in favor of it.2021-05-312021-05-31T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/138353eng10.1057/s41599-021-00812-yPossati, Lucainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T12:34:26Zoai:repositorio-aberto.up.pt:10216/138353Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:22:48.178975Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
title Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
spellingShingle Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
Possati, Luca
title_short Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
title_full Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
title_fullStr Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
title_full_unstemmed Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
title_sort Freud and the algorithm: neuropsychoanalysis as a framework to understand artificial general intelligence
author Possati, Luca
author_facet Possati, Luca
author_role author
dc.contributor.author.fl_str_mv Possati, Luca
description The core hypothesis of this paper is that neuropsychoanalysis provides a new paradigm for artificial general intelligence (AGI). The AGI agenda could be greatly advanced if it were grounded in affective neuroscience and neuropsychoanalysis rather than cognitive science. Research in AGI has so far remained too cortical-centric; that is, it has privileged the activities of the cerebral cortex, the outermost part of our brain, and the main cognitive functions. Neuropsychoanalysis and affective neuroscience, on the other hand, affirm the centrality of emotions and affects-i.e., the subcortical area that represents the deepest and most ancient part of the brain in psychic life. The aim of this paper is to define some general design principles of an AGI system based on the brain/mind relationship model formulated in the works of Mark Solms and Jaak Panksepp. In particular, the paper analyzes Panksepp's seven effective systems and how they can be embedded into an AGI system through Judea Pearl's causal analysis. In the conclusions, the author explains why building a sub-cortical AGI is the best way to solve the problem of AI control. This paper is intended to be an original contribution to the discussion on AGI by elaborating positive arguments in favor of it.
publishDate 2021
dc.date.none.fl_str_mv 2021-05-31
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