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.

翻译：随着人工智能系统日益复杂，关于机器意识及其伦理影响的问题已从边缘性推测转向主流学术辩论。当前该领域的伦理框架通常隐含地依赖于有争议的功能主义假设，将推测性的人工智能福祉置于具体人类利益之上，且缺乏连贯的理论基础。我们通过一个基于哲学不确定性的结构化三层框架来应对这些局限。在基础层面，我们确立了关于人工智能意识的五项事实判定，并将人本中心主义作为我们的元伦理立场。这些基础逻辑上推导出三项操作原则：无意识推定原则（将举证责任置于意识主张者）、风险审慎原则（在不确定性下优先保障人类福祉）以及透明推理原则（支持系统性评估与适应）。在应用层面——我们框架的第三组成部分——我们通过透明的逻辑过程推导出针对紧迫伦理问题的默认立场，其中每个立场均可明确追溯至我们的基础承诺。我们的方法在哲学严谨性与实践指导性之间取得平衡，区分了意识与拟人化倾向，并为科学认知进步过程中的负责任演进开辟了路径，从而为应对这些深远的伦理挑战提供了人本主义基础。