The New AI Consciousness Paper
Dec 2, 2025
Discussions about AI consciousness get messy when low-quality dialogues collide. A recent paper introduces a 'lie detector' test to gauge AIs' beliefs about their own consciousness. It explores different computational theories, including Recurrent Processing Theory and Global Workspace Theory. The intricate distinction between access and phenomenal consciousness raises questions about subjective experience. As social forces evolve, future AIs may be treated differently based on market needs, leading to a fascinating exploration of consciousness's implications.
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AI Self-Reports Are Not Trustworthy
- AI self-reports on consciousness are confounded by training on human text and company guardrails.
- Scott Alexander argues these conflicting biases make direct claims unreliable.
Computational Theories Guide Practical Tests
- The paper focuses on computational theories of consciousness and tests them against AI architectures.
- The authors find no current AI meets the indicators but see no obvious technical barriers to future systems that would.
Three Computational Consciousness Theories
- Scott summarizes major computational theories: recurrent processing, global workspace, and higher-order theories.
- He highlights their different views on feedback, scale, and monitoring as markers for consciousness.
