Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust

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Good Robots, Bad Robots: Morally Valenced Behavior Effects on Perceived Mind, Morality, and Trust Jaime Banks1 Accepted: 12 August 2020 © The Author(s) 2020

Abstract Both robots and humans can behave in ways that engender positive and negative evaluations of their behaviors and associated responsibility. However, extant scholarship on the link between agent evaluations and valenced behavior has generally treated moral behavior as a monolithic phenomenon and largely focused on moral deviations. In contrast, contemporary moral psychology increasingly considers moral judgments to unfold in relation to a number of moral foundations (care, fairness, authority, loyalty, purity, liberty) subject to both upholding and deviation. The present investigation seeks to discover whether social judgments of humans and robots emerge differently as a function of moral foundation-specific behaviors. This work is conducted in two studies: (1) an online survey in which agents deliver observed/mediated responses to moral dilemmas and (2) a smaller laboratory-based replication with agents delivering interactive/live responses. In each study, participants evaluate the goodness of and blame for six foundation-specific behaviors, and evaluate the agent for perceived mind, morality, and trust. Across these studies, results suggest that (a) moral judgments of behavior may be agent-agnostic, (b) all moral foundations may contribute to social evaluations of agents, and (c) physical presence and agent class contribute to the assignment of responsibility for behaviors. Findings are interpreted to suggest that bad behaviors denote bad actors, broadly, but machines bear a greater burden to behave morally, regardless of their credit- or blame-worthiness in a situation. Keywords Morality · Moral foundations · Ontological categories · Trust · Social cognition

1 Introduction Asimov’s “Three Laws of Robots” [1] govern fictional robots’ behaviors, and these laws persist in contemporary imaginaries about how robots should behave: do not injure humans, obey humans, engage in self-protection. How do humans respond, though, when a robot behaves “badly” by breaking these or other moral norms? Popular and scientific discourse alike attend to the potential for machine agency—the ability to variably act according to self-regulating abilities and intentions [2]—to engender both anxiety and acceptance of social machines. However, current human–robot interaction scholarship generally engages morality as holistic “goodness” or “badness” or reduces it to singular exemplars; this contrasts with contemporary moral psychology’s increasing engagement of the construct as mul-

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tidimensional [3]. Specifically, Moral Foundations Theory [4] parcels morality into five foundations (care, fairness, authority, loyalty, purity) and a sixth candidate foundation (liberty [5]). This study seeks to build on current understandings of how social judgments are impact by robots’ (im)moral behaviors by assessing (a) how attributions of behavioral goodness and responsibility may var