The Sentience Readiness Index: A Preliminary Framework for Measuring National Preparedness for the Possibility of Artificial Sentience
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Abstract (arXiv)
The scientific study of consciousness has begun to generate testable predictions about artificial systems. A landmark collaborative assessment evaluated current AI architectures against six leading theories of consciousness and found that none currently qualifies as a strong candidate, but that future systems might. A precautionary approach to AI sentience, which holds that credible possibility of sentience warrants governance action even without proof, has gained philosophical and institutional traction. Yet existing AI readiness indices, including the Oxford Insights Government AI Readiness Index, the IMF AI Preparedness Index, and the Stanford AI Index, measure economic, technological, and governance preparedness without assessing whether societies are prepared for the possibility that AI systems might warrant moral consideration. This paper introduces the Sentience Readiness Index (SRI), a preliminary composite index measuring national-level preparedness across six weighted categories for 31 jurisdictions. The SRI was constructed following the OECD/JRC framework for composite indicators and employs LLM-assisted expert scoring with iterative expert review to generate an initial dataset. No jurisdiction exceeds ``Partially Prepared'' (the United Kingdom leads at 49/100). Research Environment scores are universally the strongest category; Professional Readiness is universally the weakest. These exploratory findings suggest that if AI sentience becomes scientifically plausible, no society currently possesses adequate institutional, professional, or cultural infrastructure to respond. As a preliminary framework, the SRI provides an initial diagnostic baseline and highlights areas for future methodological refinement, including expanded expert validation, improved measurement instruments, and longitudinal data collection.
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References · 14
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
- 2023ChatGPT Outperforms Crowd-Workers for Text-Annotation Taskscited by 849
- 2023Consciousness in Artificial Intelligence: Insights from the Science of Consciousnesscited by 99
- 2023Could a Large Language Model be Conscious?cited by 70
- 2024Taking AI Welfare Seriouslycited by 28
- 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Surveycited by 15
- 2025A Pragmatic View of AI Personhoodcited by 12
- 2024A Case for AI Consciousness: Language Agents and Global Workspace Theorycited by 7
- 2025Principles for Responsible AI Consciousness Researchcited by 6
- 2026Initial results of the Digital Consciousness Modelcited by 5
- 2025The Societal Response to Potentially Sentient AIcited by 4
- 2025Subjective Experience in AI Systems: What Do AI Researchers and the Public Believe?cited by 4
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