machinetoperson

Machinetoperson is a term in the philosophy of artificial intelligence and ethics referring to a framework for analyzing when and whether machine intelligence and autonomous systems should be treated as persons in moral, legal, or social terms. It focuses on mapping machine capabilities to criteria traditionally associated with personhood, without assuming actual consciousness or rights.

The concept arises in debates about accountability, responsibility, and rights in AI governance, and is used in thought experiments about attributing duties to agents, determining liability, and exploring the limits of moral agency granted to machines.

Core components include autonomy, agency, deliberative capacity, and social embodiment, as well as the normative status conferred by human institutions. It emphasizes that any ascription of personhood is often a political or legal decision, not a purely technical one.

Methodologically, machinetoperson draws on legal philosophy, moral psychology, and AI safety research. It employs criteria-based assessments, comparative analyses with existing legal persons, and scenario testing to evaluate thresholds for rights or duties.

Criticisms highlight the risk of anthropomorphism, slippery slopes toward granting rights prematurely, and potential neglect of human-centered governance. Critics also warn that the framework can obscure accountability by focusing on status rather than behavior.

It relates to machine ethics, AI governance, and the broader discourse around moral agency, legal personhood for nonhuman entities, and the design of responsible, transparent AI systems.

Related concepts include legal personhood, moral agency, AI rights, corporate personhood, and robot ethics.