Artificial Intelligence, Human Consciousness, and Legal Personhood: A Multidisciplinary Exploration of Ethics, Philosophy and Law
Bhavyya Sharma
Natural Resources for Human Health September 19, 2026 DOI: 10.53365/nrfhh.2111 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Review Peer reviewed |
|---|---|
| Key findings | Argues that current behavioral sophistication in AI does not establish machine consciousness, and that granting AI legal personhood prematurely could obscure accountability and weaken victim remedies. Proposes a graded governance model separating operational agency, legal capacity, liability allocation, and moral status, with liability remaining traceable to accountable human or organizational persons unless compelling evidence and safeguards justify otherwise. |
Abstract
Artificial intelligence (AI) increasingly performs tasks associated with language, reasoning, creativity, prediction and autonomous decision-making, reviving old questions about consciousness, moral status and legal personhood. This review develops a multidisciplinary framework connecting philosophy of mind, cognitive science, AI ethics, jurisprudence, human rights, health governance and environmental sustainability. It distinguishes intelligence from consciousness, functional agency from phenomenal experience, and moral patiency from legal personality. The analysis examines computational functionalism, biological naturalism, global workspace theories, integrated information approaches, higher-order theories and embodied cognition, while emphasizing that current behavioral sophistication does not establish machine consciousness. It then evaluates legal personhood as an institutional construct historically extended to corporations and other non-human entities, and asks whether comparable techniques should ever apply to AI. Recent scholarship shows renewed debate over AI legal personality, while major governance frameworks continue to place responsibility on human and organizational actors rather than autonomous systems. The review argues that premature AI personhood could obscure accountability, weaken victim remedies and anthropomorphize systems whose subjective experience remains unverified. A graded governance model is proposed that separates operational agency, legal capacity, liability allocation and moral status. The paper also develops a human-health and natural-resources dimension: AI can improve healthcare, environmental monitoring and resource stewardship, yet computational infrastructure consumes energy, water and materials and may affect health through labor conditions, misinformation, bias and environmental burdens. A precautionary, human-rights-centred and sustainability-aware approach is therefore recommended. Legal status should track demonstrable capacities and governance needs, while liability should remain traceable to accountable natural or juridical persons unless compelling evidence and institutional safeguards justify a different model.