The best of both worlds: dual systems of reasoning in animals and AI

Much of human cognition involves two different types of reasoning that operate together. Type 1 reasoning systems are intuitive and fast, whereas Type 2 reasoning systems are reflective and slow. Why has our cognition evolved with these features? Both systems are coherent and in most ecological circumstances either alone is capable of coming up with the right answer most of the time. Neural tissue is costly, and thus far evolutionary models have struggled to identify a benefit of operating two systems of reasoning. To explore this issue we take a broad comparative perspective. We discuss how dual processes of cognition have enabled the emergence of selective attention in insects, transforming the learning capacities of these animals. Modern AIs using dual systems of learning are able to learn how their vast world works and how best to interact with it, allowing them to exceed human levels of performance in strategy games. We propose that the core benefits of dual processes of reasoning are to narrow down a problem space in order to focus cognitive resources most effectively.