Neuroscience and biobehavioral reviews
March 1, 2025
Liad Mudrik, Melanie Boly, Stanislas Dehaene et al.
68 citations
In a structured public debate at the 2022 meeting of the Association for the Scientific Study of Consciousness, proponents of five major theories—Global Neuronal Workspace Theory, Higher-Order Theories, Integrated Information Theory, Recurrent Processing Theory, and Predictive Processing—clarified their theories' core mechanisms, foundational premises, and what each theory aims to explain. The discussion revealed more controversy than agreement, particularly on the most basic questions: what consciousness is, how to identify conscious states, and what any adequate theory must account for. Addressing these foundational disagreements is essential for advancing the field and enabling meaningful comparison of competing theories.
PsyArXiv
February 23, 2021
Maxwell James Ramstead, Anil Seth, Casper Hesp et al.
21 citations
preprint
A new approach called computational phenomenology uses generative modeling techniques from computational neuroscience to study conscious experience. The paper reviews efforts to naturalize phenomenology, addresses philosophical objections, and explains how generative models can simulate the inferential processes underlying specific types of lived experience. This differs from prior uses of generative modeling for consciousness by focusing on modeling the interpretive process that best accounts for particular phenomenal experiences.
April 22, 2025
Anil Seth
1 citation
preprint
Consciousness in artificial intelligence is unlikely on current technological trajectories because computation alone is insufficient to generate it. Instead, consciousness depends on our nature as living organisms—a view called biological naturalism. People may mistakenly think AI could become conscious due to cognitive biases. Conscious AI becomes more plausible only as systems become more brain-like or life-like. Ethical considerations arise from AI that either is, or convincingly appears to be, conscious. Overestimating machine consciousness risks underestimating our own selves.