The Sentience Readiness Index: Measuring National Preparedness for the Possibility of Artificial Sentience

TL;DR

The findings suggest that if AI sentience becomes scientifically plausible, no society currently possesses adequate institutional, professional, or cultural infrastructure to respond, and the Sentience Readiness Index is introduced, a composite index measuring national-level preparedness across six weighted categories for 31 jurisdictions.

Abstract

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 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. 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 findings suggest that if AI sentience becomes scientifically plausible, no society currently possesses adequate institutional, professional, or cultural infrastructure to respond. The SRI provides a diagnostic baseline and identifies specific capacity deficits that policy can address.

Figures (4)

• Figure 1: SRI Score Distribution. Horizontal lollipop chart showing overall SRI scores for all 31 jurisdictions. Color indicates readiness tier. Vertical dashed lines mark tier boundaries at 20, 40, and 60. The global mean (33.0) is shown as a solid gray line. No jurisdiction exceeds the Partially Prepared tier.
• Figure 2: Category Performance Heatmap. 31 $\times$ 6 matrix showing jurisdiction scores by category, color-coded from low (dark) to high (light). Jurisdictions sorted by overall SRI score.
• Figure 3: Research Environment vs. Professional Readiness Gap. Dumbbell chart showing Research Environment and Professional Readiness scores for all 31 jurisdictions, sorted by gap size. Every jurisdiction shows Research Environment exceeding Professional Readiness. Mean gap = 33.65 points, Cohen's $d = 2.88$.
• Figure 4: Category-level SRI score comparison between democracies ($n = 24$) and hybrid/authoritarian regimes ($n = 7$). All six categories show higher mean scores for democracies, with the largest differentials in Research Environment (+22.35), Adaptive Capacity (+18.37), and Public Discourse (+13.37). Mann-Whitney $U = 156.0$, $p < .001$, rank-biserial $r = -0.857$.