Expecting the expected: an analytical framework to examine people’s expectations of robots

We present a novel framework for human-robot interaction designers to analyze and explore expectations of their robot designs. It consists of a model of how people form expectations of robots, and a taxonomy for classifying them. A known challenge in human-robot interactions is expectation discrepancy, in which the expectations people form when interacting with a social robot are not aligned with its actual capabilities. This can disappoint users and hinder interaction. Research has proposed ways to mitigate expectation discrepancy, but designers lack a systematic approach to analyzing and describing expectations. We developed a rigorous theoretical framework by drawing from theories and models from psychology and sociology on expectations between people, and by conducting a field review of expectations in human-robot interactions. We further propose methods for designers to leverage the framework in systematic analysis of how and why people form expectations of a given robot and what those expectations may be. This can empower designers with greater control over people’s expectations, enabling them to combat expectation discrepancy.