Consciousness in Artificial Intelligence? A Framework for Classifying Objections and Constraints
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Abstract (arXiv)
We develop a taxonomical framework for classifying challenges to the possibility of consciousness in digital artificial intelligence systems. This framework allows us to identify the level of granularity at which a given challenge is intended (the levels we propose correspond to Marr's levels) and to disambiguate its degree of force: is it a challenge to computational functionalism that leaves the possibility of digital consciousness open (degree 1), a practical challenge to digital consciousness that suggests improbability without claiming impossibility (degree 2), or an argument claiming that digital consciousness is strictly impossible (degree 3)? We apply this framework to 14 prominent examples from the scientific and philosophical literature. Our aim is not to take a side in the debate, but to provide structure and a tool for disambiguating between challenges to computational functionalism and challenges to digital consciousness, as well as between different ways of parsing such challenges.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 10 of its 75 references that are in the map. First posted on arXiv 20 Nov 2025.
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10 of 75 references.
References · 10
- 2022The Forward-Forward Algorithm: Some Preliminary Investigationscited by 266
- 2018Deep Learning: A Critical Appraisalcited by 217
- 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 104
- 2024Taking AI Welfare Seriouslycited by 31
- 2022Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical termscited by 21
- 2023The feasibility of artificial consciousness through the lens of neurosciencecited by 18
- 2023Sources of Richness and Ineffability for Phenomenally Conscious Statescited by 7
- 2016The Singularity May Never Be Nearcited by 4
- 2024Report on Candidate Computational Indicators for Conscious Valenced Experiencecited by 2
- 2025The assumptions that restrain us from understanding consciousnesscited by 1
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1 paper.