Curing robot autism: a challenge
Gal A. Kaminka · 2013
Almost all robots are autistic; very few humans are. Out of the box, robots generally do not behave correctly in social settings (involv-ing humans, or other agents). Most researchers treat this challenge behaviorally, by superficially tacking task- and domain- specific social behavior onto functioning individual robots. These rules are built once, and applied once. In contrast, I posit that we can build better socially-capable robots by relying on general social intelli-gence building blocks, built into the brains of robots, rather than grafted on per mission: built once, applied everywhere. I chal-lenge the autonomous agents community to synthesize the compu-tational building blocks underlying social intelligence, and to apply them in concrete robot and agent systems. I argue that our field is in a unique position to do this, in that our community intersects with computer science, behavioral and social sciences, robotics, and neuro-science. Thus we can bring to bear a breadth of knowl-edge and understanding which cannot be matched in other related fields. To lend credibility for our ability to carry out this challenge, I will demonstrate that we have carried out similar tasks in the past (though at a smaller scale). I conclude with a sample of some open questions for research, raised by this challenge.