arXiv:2608.05436q-bio.NCcs.AI2026-08

用人类脑科学原理重构AI伦理,强调关怀比控制更重要

The ethics of artificial intelligence in the life sciences: Universality, cultural diversity and an architecture of care

  • 以人类大脑的全局工作空间和奖赏循环为蓝本设计AI伦理架构
  • 指出当前AI追求奖励最大化是昂贵且非人性的,应转向培育式治理
  • 适合关注科技伦理、神经科学与人工智能交叉的学者与政策制定者

生命科学与健康研究正受益于人工智能,但其引发的伦理问题并非特殊。任何科学都应基于人类大脑的构建与社会化机制,而非人工智能的独特性。人脑采用低能耗的计算架构,通过全局工作空间协调神经网络,并以持续的渴望、喜好与满足构成奖赏机制。这导致伦理判断的普遍性与道德多样性的深层张力:全球工作空间与情感网络具有普遍性,但内容受表观遗传对物理、社会与文化世界的摄取影响,使每个人独特。若未来机器基于此原则构建,而非现有高成本的奖励最大化模型,治理将从限制转为养育。本文提出此类未来所需制度,并保留待解问题。

原文摘要 · Abstract (English)

The life sciences and health research have started to benefit from artificial intelligence, which raises ethical concerns that are real but, we argue, not special. Any science should be governed by values that rest on how the human brain is built and socialised rather than anything distinct to artificial intelligence. Importantly, the human brain has a different, much less costly computational architecture than these machines. This is achieved through the orchestration of a global neuronal workspace, and through reward best described not as a quantity to be maximised but as a continuous cycle of wanting, liking and satiety. As such, this creates the deep tension running through the ethics of the human person, between the universality of ethical judgement and the diversity of morals. The brain networks of the global workspace and emotion are universally shared, but the diversity of content is shaped by epigenetic appropriation of the particulars of the physical, social and cultural world, which makes every person unique. Still, if we were to build machines on these principles rather than the present unaffordable reward maximisers, the question of their governance would change from restraint to upbringing. We set out the institutions such a future would require, together with the questions that remain open.

AI伦理神经科学认知架构关怀治理

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