The Phenomenal Is Functional: A Unified Theory of Consciousness and Computation

Consciousness arises because organisms that learn to classify causes of their own sensations adapt more efficiently. The hard problem—why there is something it is like to be conscious—is resolved by showing that phenomenal consciousness (P-consciousness) emerges when an organism must classify its own interventions, creating a persistent quality across those interventions. Access consciousness (A-consciousness) emerges at a higher order when an organism must infer another's prediction of its interventions. Together they form H-consciousness, a hierarchy of causal identities that simplify the environment into classifiers of cause and affect. The authors deny that a philosophical zombie could be as capable as a P-conscious being, because learning causality requires presupposing objects, not just learning associations.

Study at a glance

Abstract

Please note this is a draft on which we are seeking feedback. Substantial changes and a third author are likely be added to the next version. The hard problem of consciousness asks why there is something it is like to be a conscious organism. We address this from 1st principles, by constructing a formalism that unifies lower and higher order theories of consciousness. We assume pancomputationalism and hold that the environment learns organisms that exhibit fit behaviour via the algorithm we call natural selection. Selection learns organisms that learn to classify causes, facilitating adaptation. Recent experimental and mathematical computer science elucidates how. Scaling this capacity implies a progressively higher order of ``causal identity'' facilitating reafference and P-consciousness, then self awareness and A-consciousness, and then meta self awareness. We then use this to resolve the hard problem in precise terms. First, we deny that a philosophical zombie is in all circumstances as capable as a P-conscious being. This is because a variable presupposes an object to which a value is assigned. Whether X causes Y depends on the choice of X, so causality is learned by learning X such that X causes Y, not by presupposing X and then learning if X causes Y (presupposing rather than inferring abstractions can reduce sample efficiency in learning). However, learning is a discriminatory process that requires states be differentiated by value. Without objects, variables or values, there is only quality. By this we mean an organism is attracted to or repulsed by a physical state. Learning reduces quality into objects by constructing policies classifying cause of affect (``representations'' are just behaviour triggered by phenomenal content). Where selection pressures require an organism classify its own interventions, that policy (a ``1st order causal identity'') has a quality that persists across interventions, and so there is something it is like to be that organism. Thus organisms have P-consciousness because it allows them to adapt with greater sample efficiency, and infer the cause of affect. We then argue neither P nor A-consciousness alone are remarkable, but when P-consciousness gives rise to A-consciousness we obtain ``H-consciousness'' (what Boltuc argues is the crux of the hard problem). This occurs when selection pressures require organism o infer organism u's prediction of o's interventions a ``2nd order causal identity'' approximating intent). A-consciousness is the contents of 2nd order causal identities, and by predicting another's prediction of one's own 1st order causal identities it becomes possible to know what one knows and feels, and act upon this information to communicate meaning in the Gricean sense. Thus P and A-consciousness are two aspects of H-concsiousness, the process of learning and acting in accord with a hierarchy of causal identities that simplify the environment into classifiers of cause and affect. We call this the psychophysical principle of causality.