A multidimensional conception and measure of human-robot trust

Robots are increasingly used in social applications, which raise challenges regarding people's trust in robots. A modern conception of human-robot trust must go beyond the conventional notions of human-automation relations and better connect to the current understanding of human-human trust, without assuming that human-robot trust is identical. A review of the literature together with our recent empirical work suggests that trust is multidimensional, incorporating both performance aspects (central in the human-automation literature) and moral aspects (central in the human-human trust literature). A multidimensional conception can be applied to human-robot trust, even if only some of the dimensions will be relevant for any given interaction with a robot. In addition to proposing an integrative conception of trust, we offer a measurement instrument for public use: the Multidimensional Measure of Trust (MDMT). This measure captures two superordinate factors of trust (Performance trust, Moral trust) that each break into two subfacets (Reliable and Capable within Performance, and Sincere and Ethical within Moral). We are continuing to test this measure in follow-up research and encourage other researchers to join us in collectively validating it.