Augmenting Human Selves Through Artificial Agents – Lessons From the Brain
Northoff, G., Fraser, M., Griffiths, J. , Pinotsis, D. A.
ORCID: 0000-0002-6865-8103, Panangaden, P., Moran, R. & Friston, K. (2022).
Augmenting Human Selves Through Artificial Agents – Lessons From the Brain.
Frontiers in Computational Neuroscience, 16,
article number 892354.
doi: 10.3389/fncom.2022.892354
Abstract
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.
| Publication Type: | Article |
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| Additional Information: | Copyright © 2022 Northoff, Fraser, Griffiths, Pinotsis, Panangaden, Moran and Friston. 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. |
| Publisher Keywords: | intelligence augmentation (IA), spatio – temporal dynamics, free energy principle, free energy principle and active inference (FEP-AI) framework, human self, hierarchical learning, agent-environment interaction |
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology H Social Sciences > HM Sociology H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
| Departments: | School of Health & Medical Sciences School of Health & Medical Sciences > Department of Psychology & Neuroscience |
| SWORD Depositor: |
Available under License Creative Commons: Attribution International Public License 4.0.
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