CIFAR Program in Brain, Mind and Consciousness

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• Center for Mind, Brain, and Consciousnessinstitute0.763
  Major consciousness science center directed by Ned Block and David Chalmers
• Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.731
  Central methodological claim of the paper.
• 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.claim0.728
  Core theoretical claim connecting consciousness to biological learning
• 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.hypothesis0.727
  The Genesis Hypothesis as explicit predictive conjecture
• Different learning systems facing similar computational problems will converge to similar consciousness-like solutions, including potentially biological and artificial systemshypothesis0.724
  Extension of the Universality Hypothesis to consciousness: if consciousness solves a well-defined computational problem, different systems will discover it independently
• What computational function does consciousness serve, and what functional organization is sufficient for its presence?question0.717
  Opening motivating question addressed by the paper's thesis
• All cognitive systems have some degree of consciousness.hypothesis0.716
  Gradualism implies that if brains are conscious, so are other tissues with similar mechanisms.
• California Institute for Machine Consciousnessinstitute0.716
  The organization whose research program this whitepaper describes, dedicated to building and analyzing computational systems to test theories of consciousness