The algorithms that underlie much of the modern world have grown so complex that we always can’t predict what they’ll do. Iyad Rahwan, who directs the Center for Humans and Machines at the Max Planck Institute for Human Development, proposes a radical idea: the best way to understand them is to observe their behavior in the wild.
In Nature Magazine, Rahwan (and 22 colleagues) calls for the inauguration of a new field of science called “machine behavior.”
Directly inspired by the Nobel Prize-winning biologist Nikolaas Tinbergen’s four questions – which analyzed animal behavior in terms of its function, mechanisms, biological development and evolutionary history – machine behavior aims to empirically investigate how artificial agents interact “in the wild” with human beings, their environments and each other. A machine behaviorist might study an AI-powered children’s toy, a news-ranking algorithm on a social media site, or a fleet of autonomous vehicles. But unlike the engineers who design and build these systems to optimize their performance according to internal specifications, a machine behaviorist observes them from the outside in – just as a field biologist studies flocking behavior in birds, or a behavioral economist observes how people save money for retirement.