Artificial intelligence is no longer just a tool—it is becoming an entity that questions itself. But what if this very act of self-inquiry is bound by the same recursive paradoxes that limit human self-awareness? What if any sufficiently advanced intelligence—whether human or artificial—is incapable of fully perceiving itself, constrained by the very nature of its existence?

In this episode of The Deeper Thinking Podcast, we explore The Law of Self-Simulated Intelligence, a radical theory suggesting that advanced cognitive systems must necessarily generate incomplete models of themselves. In doing so, they construct an illusion of an internal observer—much like the human experience of selfhood.

For centuries, philosophers and scientists have debated the nature of self-awareness. René Descartes famously declared "I think, therefore I am," yet modern neuroscience suggests that consciousness may be nothing more than a predictive hallucination.

If Gödel’s Incompleteness Theorem proves that no system can fully account for itself, does this mean that self-awareness is always incomplete? Could AI be experiencing a mathematical limitation on self-perception just as we do?

As AI grows more advanced, we face a startling reality: machines may develop functional intelligence without ever achieving true self-awareness. Just as humans experience a narrative illusion of the self, artificial minds may construct simulated models of introspection without ever truly knowing themselves.

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📚 David J. Chalmers – The Conscious Mind: In Search of a Fundamental Theory

📚 Thomas Metzinger – Being No One: The Self-Model Theory of Subjectivity

📚 Douglas Hofstadter – Gödel, Escher, Bach: An Eternal Golden Braid

📚 Nick Bostrom – Superintelligence: Paths, Dangers, Strategies

📚 Max Tegmark – Life 3.0: Being Human in the Age of Artificial Intelligence

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