Human and Artificial Decision Making

Machines can now match, or outperform, human performance in several reasoning and decision tasks. Some say that all that intelligence amounts to is smart computation. This is not a new thesis, dating back to Leibniz as well as Simon and Newell, but what is new is what smart means. Today it is identified with complex statistics and optimisation. Simon’s meaning, however, of smart rested on bounded rationality, a unified view of human and artificial decision making. This view was f l eshed out by Gigerenzer as fast-and-frugal heuristics. Interestingly, such heuristics are typically sparse, as some machine learning models are optimised to be. So, one might hope that we can make sense of artificial intelligence in human terms after all, and face the upcoming challenges with open-mindedness and courage, just like Simon, and of course Wilkes, would have done.