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
This paper proposes a structured, philosophical framework for ethically evaluating AI consciousness, emphasizing human interests and uncertainty, to guide responsible AI development.
Contribution
It introduces a three-level, uncertainty-based framework grounded in philosophical analysis, addressing limitations of current AI ethics approaches.
Findings
Establishes five factual determinations about AI consciousness.
Defines three operational principles for ethical evaluation.
Derives default ethical positions through transparent logical processes.
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…
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Taxonomy
TopicsEthics and Social Impacts of AI · Neuroethics, Human Enhancement, Biomedical Innovations · Embodied and Extended Cognition
