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Augmenting Human Selves Through Artificial Agents – Lessons From the Brain

Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI – but typically these tasks do not targe...

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Autores principales: Northoff, Georg, Fraser, Maia, Griffiths, John, Pinotsis, Dimitris A., Panangaden, Prakash, Moran, Rosalyn, Friston, Karl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260143/
https://www.ncbi.nlm.nih.gov/pubmed/35814345
http://dx.doi.org/10.3389/fncom.2022.892354
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author Northoff, Georg
Fraser, Maia
Griffiths, John
Pinotsis, Dimitris A.
Panangaden, Prakash
Moran, Rosalyn
Friston, Karl
author_facet Northoff, Georg
Fraser, Maia
Griffiths, John
Pinotsis, Dimitris A.
Panangaden, Prakash
Moran, Rosalyn
Friston, Karl
author_sort Northoff, Georg
collection PubMed
description Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI – but typically these tasks do not target higher-level human cognitive abilities, such as consciousness or morality; these are left to the realm of so-called “strong AI” or “artificial consciousness.” In this paper, we focus on how a machine can augment humans rather than do what they do, and we extend this beyond AGI-style tasks to augmenting peculiarly personal human capacities, such as wellbeing and morality. We base this proposal on associating such capacities with the “self,” which we define as the “environment-agent nexus”; namely, a fine-tuned interaction of brain with environment in all its relevant variables. We consider richly adaptive architectures that have the potential to implement this interaction by taking lessons from the brain. In particular, we suggest conjoining the free energy principle (FEP) with the dynamic temporo-spatial (TSD) view of neuro-mental processes. Our proposed integration of FEP and TSD – in the implementation of artificial agents – offers a novel, expressive, and explainable way for artificial agents to adapt to different environmental contexts. The targeted applications are broad: from adaptive intelligence augmenting agents (IA’s) that assist psychiatric self-regulation to environmental disaster prediction and personal assistants. This reflects the central role of the mind and moral decision-making in most of what we do as humans.
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spelling pubmed-92601432022-07-08 Augmenting Human Selves Through Artificial Agents – Lessons From the Brain Northoff, Georg Fraser, Maia Griffiths, John Pinotsis, Dimitris A. Panangaden, Prakash Moran, Rosalyn Friston, Karl Front Comput Neurosci Neuroscience Much of current artificial intelligence (AI) and the drive toward artificial general intelligence (AGI) focuses on developing machines for functional tasks that humans accomplish. These may be narrowly specified tasks as in AI, or more general tasks as in AGI – but typically these tasks do not target higher-level human cognitive abilities, such as consciousness or morality; these are left to the realm of so-called “strong AI” or “artificial consciousness.” In this paper, we focus on how a machine can augment humans rather than do what they do, and we extend this beyond AGI-style tasks to augmenting peculiarly personal human capacities, such as wellbeing and morality. We base this proposal on associating such capacities with the “self,” which we define as the “environment-agent nexus”; namely, a fine-tuned interaction of brain with environment in all its relevant variables. We consider richly adaptive architectures that have the potential to implement this interaction by taking lessons from the brain. In particular, we suggest conjoining the free energy principle (FEP) with the dynamic temporo-spatial (TSD) view of neuro-mental processes. Our proposed integration of FEP and TSD – in the implementation of artificial agents – offers a novel, expressive, and explainable way for artificial agents to adapt to different environmental contexts. The targeted applications are broad: from adaptive intelligence augmenting agents (IA’s) that assist psychiatric self-regulation to environmental disaster prediction and personal assistants. This reflects the central role of the mind and moral decision-making in most of what we do as humans. Frontiers Media S.A. 2022-06-23 /pmc/articles/PMC9260143/ /pubmed/35814345 http://dx.doi.org/10.3389/fncom.2022.892354 Text en Copyright © 2022 Northoff, Fraser, Griffiths, Pinotsis, Panangaden, Moran and Friston. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Northoff, Georg
Fraser, Maia
Griffiths, John
Pinotsis, Dimitris A.
Panangaden, Prakash
Moran, Rosalyn
Friston, Karl
Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
title Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
title_full Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
title_fullStr Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
title_full_unstemmed Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
title_short Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
title_sort augmenting human selves through artificial agents – lessons from the brain
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260143/
https://www.ncbi.nlm.nih.gov/pubmed/35814345
http://dx.doi.org/10.3389/fncom.2022.892354
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