A Failure of Imagination: How and Why People Respond Differently to Human and Computer Team-Mates

Abstract

Much attention in the development of artificial team-mates has focused on replicating human qualities and performance. However, all things being equal, do human players respond in the same way to human and artificial team-mates ? and if there are differences, what accounts for them?

Related research has examined differences using direct comparisons of responses to human and AI partners in conversational interactions, competitive games, and in the cooperative game context. However, the work to date examining the effects of team-mate identity has not been extensive and previous attempts to explain the findings have not sufficiently examined player beliefs about their team-mate or the rationale and motivation for behavior.

This thesis reports on research to understand differences in player experience, perception, and behavior when human players play with either human or AI team-mates in real-time cooperative games. A number of experiments were conducted in which the subjects played a computer game involving an unseen team-mate whom they were told was a human or a com-puter program. Data gathered included performance logs, questionnaires, and in-depth interviews.

Participants consistently rated their enjoyment higher with the ?presumed human? (PH) team-mate and rated it more favorably ? higher in cooperation, skill, and noticed more risk-taking by the PH team-mate. PH team-mates were given more credit for successes and less blame compared to their AI counterparts. In terms of behavior, players pro-tected the PH team-mate more in a game involving few decisions, yet players protected AI team-mates more in a complex cooperative game involving sustained effort and constant decision-making.

In order to explain why the identity of the team-mate results in different emotional, evaluative, and behavioral responses, an original Cooperative Attribution Framework was developed. The framework proposes that the player considers the intentions and attributes of their team-mates and also considers the pressures and motivations of the player in the larger social context of the interaction.

Using the Cooperative Attribution Framework, this thesis argues that the differences observed are broadly the result of being unable to imagine that an AI team-mate could have certain attributes (e.g., emotional dispositions). One of the more surprising aspects of this insight is that the ?inability to imagine? impacts decisions and judgments that seem quite unrelated (e.g., credit assignment for objectively equivalent events).

This thesis contributes to the literature on artificial team-mates by revealing some of the differences in response to human and computer team-mates in cooperative games. In order to explain these differences, a framework is developed and applied to our studies, and justified through its application to the results of related research.