mlsanityData to 7 Oct 2026

Is artificial consciousness achievable? Lessons from the human brain

arXiv 2405.04540 ↗First posted 18 Apr 2024q-bio.NC cs.AIcited by 11

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Abstract (arXiv)

We here analyse the question of developing artificial consciousness from an evolutionary perspective, taking the evolution of the human brain and its relation with consciousness as a reference model. This kind of analysis reveals several structural and functional features of the human brain that appear to be key for reaching human-like complex conscious experience and that current research on Artificial Intelligence (AI) should take into account in its attempt to develop systems capable of conscious processing. We argue that, even if AI is limited in its ability to emulate human consciousness for both intrinsic (structural and architectural) and extrinsic (related to the current stage of scientific and technological knowledge) reasons, taking inspiration from those characteristics of the brain that make conscious processing possible and/or modulate it, is a potentially promising strategy towards developing conscious AI. Also, it is theoretically possible that AI research can develop partial or potentially alternative forms of consciousness that is qualitatively different from the human, and that may be either more or less sophisticated depending on the perspectives. Therefore, we recommend neuroscience-inspired caution in talking about artificial consciousness: since the use of the same word consciousness for humans and AI becomes ambiguous and potentially misleading, we propose to clearly specify what is common and what differs in AI conscious processing from full human conscious experience.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 28 of its 189 references that are in the map. First posted on arXiv 18 Apr 2024.

Builds on

28 of 189 references.

References · 28

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  3. 2022Talking About Large Language Modelscited by 174
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  6. 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 99
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16 more
  1. 2022Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical termscited by 21
  2. 2023The feasibility of artificial consciousness through the lens of neurosciencecited by 18
  3. 2016When the map is better than the territorycited by 17
  4. 2020Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate datacited by 16
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  7. 2022Language and Culture Internalisation for Human-Like Autotelic AIcited by 14
  8. 2021Learning cortical representations through perturbed and adversarial dreamingcited by 10
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  12. 2022Need is All You Need: Homeostatic Neural Networks Adapt to Concept Shiftcited by 6
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  16. 2023Learning beyond sensations: how dreams organize neuronal representationscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 7.

11 papers.

  1. 2024The Epistemic Asymmetry of Consciousness Self-Reports: A Formal Analysis of AI Consciousness Denialcited by 1
  2. 2026Just aware enough: Evaluating awareness across artificial systemscited by 1
  3. 2026Intentionality is a Design Decision: Measuring Functional Intentionality for Accountable AI Systemscited by 1
  4. 2026AI and Consciousness: Shifting Focus Towards Tractable Questionscited by 1
  5. 2025Serious Games: Human-AI Interaction, Evolution, and Coevolutioncited by 0
  6. 2025AI and Consciousnesscited by 0
  7. 2025AI Consciousness and Existential Riskcited by 0
  8. 2026Informed Consent for AI Consciousness Research: A Talmudic Framework for Graduated Protectionscited by 0
  9. 2026When Should We Protect AI? A Precautionary Framework for Consciousness Uncertaintycited by 0
  10. 2026The ethics of artificial intelligence in the life sciences: Universality, cultural diversity and an architecture of carecited by 0
  11. 2026Anthropomorphism in the age of Large Language Models: An overview of potential risks and mitigationscited by 0