A thousand brains: toward biologically constrained AI
Open accessAbstract
This paper reviews the state of artificial intelligence (AI) and the quest to create general AI with human-like cognitive capabilities. Although existing AI methods have produced powerful applications that outperform humans in specific bounded domains, these techniques have fundamental limitations that hinder the creation of general intelligent systems. In parallel, over the last few decades, an explosion of experimental techniques in neuroscience has significantly increased our understanding of the human brain. This review argues that improvements in current AI using mathematical or logical techniques are unlikely to lead to general AI. Instead, the AI community should incorporate neuroscience discoveries about the neocortex, the human brain’s center of intelligence. The article explains the limitations of current AI techniques. It then focuses on the biologically constrained Thousand Brains Theory describing the neocortex’s computational principles. Future AI systems can incorporate these principles to overcome the stated limitations of current systems. Finally, the article concludes that AI researchers and neuroscientists should work together on specified topics to achieve biologically constrained AI with human-like capabilities.
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AI systems can make serious mistakes that no sane human would make.
“These AI systems can make serious mistakes that no sane human would make (Hole and Ahmad, 2021).”
From Towards a <i>Smart Bionic Eye</i> : AI-powered artificial vision for the treatment of incurable blindness (2022) · cites this paper as Hole and Ahmad, 2021
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Cited by
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“These AI systems can make serious mistakes that no sane human would make (Hole and Ahmad 2021).”
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“However, the reality is still far away from this: First, most of the AI systems in use belong to the class of narrow AI, which includes restricted self-learning approaches (Batin et al., 2017; Hole and Ahmad, 2021).”
Background
- Authors
- Hole, K. J., & Ahmad, S.
- Affiliations
- Simula UiB (NO)
- Corresponding author
- Hole, Kjell Jørgen
- Venue
- SN Applied Sciences
- Published
- 2021-07-20
- Volume
- 3
- Issue
- 8
- ISSN
- 2523-3963 (ISSN-L)
- 2523-3971
- OpenAlex
- W3183615570
- Cited by
- 42
- References
- 8
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 7 · 2023: 15 · 2022: 10
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- SN Applied Sciences (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
- Physical Sciences › Computer Science › Artificial Intelligence › Cognitive Computing and Networks
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Keywords
- artificial general intelligence, neocortex, human brain, human-like cognition
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