Abstract of this talk: In this talk, I will present our current two lines of theoretical work on consciousness. In the first half, I will discuss our recent work on the information closure theory of consciousness (ICT; Chang et al., 2020) in which we argue that the scale and the boundary of consciousness are determined by the so-called information closure of the system. In the ICT, we introduce the notion of non-trivial information closure (NTIC) to explain how the content of consciousness can be informationally closed from the environment and at the same time mirrors the events in the external world. We discuss our preliminary results on how Bayesian agents may develop NTIC over a short time period and how NTIC may be disrupted by prediction errors.
In the second half, I will present a hypothesis that consciousness has evolved as a platform for general intelligence (Kanai et al. in preparation). Here we define general intelligence as the ability to apply knowledge and models acquired from past experiences to generate solutions to novel problems. We propose three ways to establish general intelligence in AI systems, namely solution by simulation, solution by combination and solution by generation. Then, we relate those solutions to putative functions of consciousness put forward, respectively, by the information generation hypothesis (Kanai et al., 2019), the global workspace theory, and a form of higher order theory where qualia are regarded as meta-representations. By linking theories of consciousness to possible architectures of artificial general intelligence, I will discuss the fundamental link between consciousness and intelligence.
Keywords: Mathematical Consciousness Science Online Seminar Series