Instruct or Evaluate: How People Choose to Teach Norms to Social Robots

摘要

Robots deployed in social settings must act appropriately-that is, in compliance with social and moral norms. However, efforts of teaching norms to robots have typically relied on single teaching methods (e.g., instruction, reward). By contrast, humans may naturally use more than one teaching method when training a novice. To test this claim in the domain of human-robot teaching, we present a novel paradigm in which participants interactively teach a simulated robot to behave appropriately in a healthcare setting, choosing to either instruct the robot or evaluate its proposed actions. We demonstrate that 89% of human teachers naturally adopt mixed teaching strategies. We further identify some of the factors that influence people's choices. Results reveal that human teachers dynamically update their impression of the robot from early to late in the teaching session, and they choose their teaching strategy based on the robot's specific actions and their accumulated perceptions of the robot's learning progress.