Consciousness and Generative Artificial Intelligence. An Integrative Review of Philosophical, Empirical, and Contemplative Perspectives

The question of whether generative AI systems could be conscious cannot be answered by any single field. This review synthesizes 76 sources across philosophy, psychology, neuroscience, and Buddhist thought, organizing them into five thematic clusters: the hard problem of consciousness, phenomenological and embodied perspectives, empirical frameworks like Integrated Information Theory and Global Workspace Theory, Buddhist views on awareness and selfhood, and behavioral evidence from AI. The authors argue that progress requires interdisciplinary dialogue and that the question itself functions as a provocation for rethinking consciousness, subjecthood, and institutional responsibilities rather than a problem to be solved.

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Abstract

The arrival of generative artificial intelligence systems capable of fluent language, plausible images, and seemingly thoughtful responses has reignited a question in urgent terms: can a machine be conscious? This integrative review brings together philosophical argument, empirical evidence from psychology and neuroscience, and contemplative perspectives drawn from Buddhist thought to examine what is known and contested about consciousness in generative AI. Synthesizing 76 sources, it organizes the findings into five thematic clusters: the hard problem; phenomenological and embodied perspectives; empirical frameworks including Integrated Information Theory and Global Workspace Theory; Buddhist perspectives on awareness and selfhood; and AI-specific behavioral evidence. The review argues that questions about AI consciousness cannot be settled within any single discipline and that progress requires sustained interdisciplinary dialogue. It proposes that the question functions less as a problem to be solved than as a provocation for rethinking consciousness, subjecthood, and the responsibilities of educational and public institutions.