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A Human-centric Framework for Debating the Ethics of AI Consciousness Under Uncertainty

Zhou Ziheng, Haiqiang Dai, Bin Ling, Ying Nian Wu, Demetri Terzopoulos

TL;DR

The paper tackles the ethical management of AI consciousness under deep uncertainty by proposing a three-level framework anchored in five factual determinations and a human-centric meta-ethic. It derives three core operational principles—risk prudence, presumption of no consciousness, and transparent reasoning—to guide normative positions, which are then applied to key questions about bothering AI systems, public communication, and future rights. The approach emphasizes distinguishing consciousness from anthropomorphism, providing explicit derivations to justify human-priority positions, and enabling principled evolution as science progresses. The framework offers actionable, starting-point ethics that prioritize human welfare while remaining adaptable to future developments in AI consciousness research and governance.

Abstract

As AI systems become increasingly sophisticated, questions about machine consciousness and its ethical implications have moved from fringe speculation to mainstream academic debate. Current ethical frameworks in this domain often implicitly rely on contested functionalist assumptions, prioritize speculative AI welfare over concrete human interests, and lack coherent theoretical foundations. We address these limitations through a structured three-level framework grounded in philosophical uncertainty. At the foundational level, we establish five factual determinations about AI consciousness alongside human-centralism as our meta-ethical stance. These foundations logically entail three operational principles: presumption of no consciousness (placing the burden of proof on consciousness claims), risk prudence (prioritizing human welfare under uncertainty), and transparent reasoning (enabling systematic evaluation and adaptation). At the application level, the third component of our framework, we derive default positions on pressing ethical questions through a transparent logical process where each position can be explicitly traced back to our foundational commitments. Our approach balances philosophical rigor with practical guidance, distinguishes consciousness from anthropomorphism, and creates pathways for responsible evolution as scientific understanding advances, providing a human-centric foundation for navigating these profound ethical challenges.

A Human-centric Framework for Debating the Ethics of AI Consciousness Under Uncertainty

TL;DR

The paper tackles the ethical management of AI consciousness under deep uncertainty by proposing a three-level framework anchored in five factual determinations and a human-centric meta-ethic. It derives three core operational principles—risk prudence, presumption of no consciousness, and transparent reasoning—to guide normative positions, which are then applied to key questions about bothering AI systems, public communication, and future rights. The approach emphasizes distinguishing consciousness from anthropomorphism, providing explicit derivations to justify human-priority positions, and enabling principled evolution as science progresses. The framework offers actionable, starting-point ethics that prioritize human welfare while remaining adaptable to future developments in AI consciousness research and governance.

Abstract

As AI systems become increasingly sophisticated, questions about machine consciousness and its ethical implications have moved from fringe speculation to mainstream academic debate. Current ethical frameworks in this domain often implicitly rely on contested functionalist assumptions, prioritize speculative AI welfare over concrete human interests, and lack coherent theoretical foundations. We address these limitations through a structured three-level framework grounded in philosophical uncertainty. At the foundational level, we establish five factual determinations about AI consciousness alongside human-centralism as our meta-ethical stance. These foundations logically entail three operational principles: presumption of no consciousness (placing the burden of proof on consciousness claims), risk prudence (prioritizing human welfare under uncertainty), and transparent reasoning (enabling systematic evaluation and adaptation). At the application level, the third component of our framework, we derive default positions on pressing ethical questions through a transparent logical process where each position can be explicitly traced back to our foundational commitments. Our approach balances philosophical rigor with practical guidance, distinguishes consciousness from anthropomorphism, and creates pathways for responsible evolution as scientific understanding advances, providing a human-centric foundation for navigating these profound ethical challenges.

Paper Structure

This paper contains 17 sections.