We hypothesize it is possible to search for the consciousness algorithm by recreating analogous conditions of self-organizing information processing on digital computer hardware while posing tasks requiring intelligent agency.

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• Human consciousness is tied to a biological learning algorithm — the simplest algorithm discoverable by evolutionary search to train a self-organizing biological substrate to become intelligent.claim0.854
  Core theoretical claim connecting consciousness to biological learning
• Consciousness is the simplest learning algorithm discoverable by evolutionary search to train a self-organizing biological substrate to become intelligent in service of agencyhypothesis0.847
  CIMC's specific account of what consciousness is and why it evolved
• We hypothesize that consciousness may be at the heart of a universal biological learning algorithm — one that runs on self-organizing groups of communicating cells sharing evolutionary incentives — and that it creates rather than results from organized mental architecture.hypothesis0.841
  The Genesis Hypothesis as explicit predictive conjecture
• It is basically impossible to determine if a computer program generates conscious experience by merely observing its performance; a test for consciousness must take internal structure into account.claim0.807
  Paper's argument against behavioral tests for consciousness, establishing why MCH requires internal analysis
• Consciousness is a phenomenon we have partial sensors for; building better sensors is a research and engineering question.claim0.805
• General computational machines with sufficient resources possess the necessary and sufficient means to implement consciousnesshypothesis0.801
  CIMC's central testable hypothesis grounding the entire research program
• Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.801
  Central methodological claim of the paper.
• Different learning systems facing similar computational problems will converge to similar consciousness-like solutions, including potentially biological and artificial systemshypothesis0.798
  Extension of the Universality Hypothesis to consciousness: if consciousness solves a well-defined computational problem, different systems will discover it independently