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This paper argues that ethical frameworks in AI-driven life sciences should be grounded in the biological architecture of human cognition rather than treating current reward-maximization models as unique problems requiring special restraint. The authors propose shifting governance from mere limitation to "upbringing" by designing machines based on universal neuronal workspace principles while accommodating cultural diversity through epigenetic-like adaptations.
The ethics of artificial intelligence in the life sciences: Universality, cultural diversity and an architecture of care
arXiv:2608.05436v1 Announce Type: cross Abstract: 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.
Abstract: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.
Neurons and Cognition (q-bio.NC); Artificial Intelligence (cs.AI)
arXiv:2608.05436 [q-bio.NC]
(or arXiv:2608.05436v1 [q-bio.NC] for this version)
https://doi.org/10.48550/arXiv.2608.05436 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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