Falsification and consciousness

Abstract

The search for a scientific theory of consciousness should result in theories that are falsifiable. However, here we show that falsification is especially problematic for theories of consciousness. We formally describe the standard experimental setup for testing these theories. Based on a theory's application to some physical system, such as the brain, testing requires comparing a theory's predicted experience (given some internal observables of the system like brain imaging data) with an inferred experience (using report or behavior). If there is a mismatch between inference and prediction, a theory is falsified. We show that if inference and prediction are independent, it follows that any minimally informative theory of consciousness is automatically falsified. This is deeply problematic since the field's reliance on report or behavior to infer conscious experiences implies such independence, so this fragility affects many contemporary theories of consciousness. Furthermore, we show that if inference and prediction are strictly dependent, it follows that a theory is unfalsifiable. This affects theories which claim consciousness to be determined by report or behavior. Finally, we explore possible ways out of this dilemma.

arXiv comment21 pages, 4 figures

References in corpus (5)

• End to End Learning for Self-Driving Cars
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• Toward an AI Physicist for Unsupervised Learning
• Information Closure Theory of Consciousness
• The Phi measure of integrated information is not well-defined for general physical systems

Cited by in corpus (2)

• Mathematical Models of Consciousness
• Fast Falsification of Neural Networks using Property Directed Testing