THE STRENGTH OF WEAK ARTIFICIAL CONSCIOUSNESS

Weak artificial consciousness—using synthetic models to simulate neural mechanisms—can advance understanding of how those mechanisms produce conscious experience, whereas strong artificial consciousness, which aims to instantiate consciousness in machines, is less likely to yield such insights. Synthetic models can serve as "explanatory correlates" that causally account for deep structural properties of consciousness. Strong artificial consciousness, while not impossible, has not been credibly illustrated and suffers from circularity: using models both as instantiations and as tools for discovering principles delays empirical comparison.

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Abstract

Machine (artificial) consciousness can be interpreted in both strong and weak forms, as an instantiation or as a simulation. Here, I argue in favor of weak artificial consciousness, proposing that synthetic models of neural mechanisms potentially underlying consciousness can shed new light on how these mechanisms give rise to the phenomena they do. The approach I advocate involves using synthetic models to develop "explanatory correlates" that can causally account for deep, structural properties of conscious experience. In contrast, the project of strong artificial consciousness — while not impossible in principle — has yet to be credibly illustrated, and is in any case less likely to deliver advances in our understanding of the biological basis of consciousness. This is because of the inherent circularity involved in using models both as instantiations and as cognitive prostheses for exposing general principles, and because treating models as instantiations can indefinitely postpone comparisons with empirical data.