Legislating AI Consciousness Without an Exit

· Source: The Regulatory Review · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations, Corporate Law & Business Legal Services · Depth: Intermediate, extended

Summary

Nine U.S. states, including Idaho (2022), North Dakota (2023), and Utah (2024), have enacted or introduced laws declaring that artificial intelligence (AI) systems cannot possess consciousness, legal personhood, or moral status. Oklahoma's House passed its bill 94 to 2 in March 2026, with similar legislation pending in Ohio, Tennessee, South Carolina, Washington, and Missouri. These laws lack sunset clauses or scientific review mechanisms and do not differentiate between current and future AI capabilities. The article argues this legislative certainty is premature, citing scientific uncertainty, such as Anthropic's research on emotion-like representations and AI researchers assigning a median 25-30% chance of AI "inner experience" within a decade. It warns that such categorical laws could stifle research, as seen with the 1996 Dickey Amendment, and prevent proper oversight of AI systems in critical sectors.

Key takeaway

For Policy Makers drafting AI legislation, you should avoid categorical declarations on AI consciousness or personhood that lack mechanisms for future scientific review. Instead, incorporate sunset clauses or trigger provisions tied to expert scientific assessments to ensure laws remain adaptable as AI capabilities evolve. This approach prevents premature legal certainty from hindering research or creating unforeseen liability gaps, ensuring human accountability for AI actions.

Key insights

State laws prematurely declaring AI lacks personhood and consciousness risk stifling scientific inquiry and effective governance by legislating certainty where science is unsettled.

Principles

Method

To improve AI governance, implement sunset clauses for reauthorization or trigger provisions for mandatory legislative review based on scientific assessments from bodies like the National Academies.

In practice

Topics

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Policy Maker, Legal Professional, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by The Regulatory Review.