People do not feel guilty about exploiting machines

de Melo, C., Marsella, S. and Gratch, J. (2016) People do not feel guilty about exploiting machines. ACM Transactions on Computer-Human Interaction, 23(2), 8. (doi: 10.1145/2890495)

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Guilt and envy play an important role in social interaction. Guilt occurs when individuals cause harm to others or break social norms. Envy occurs when individuals compare themselves unfavorably to others and desire to benefit from the others’ advantage. In both cases, these emotions motivate people to act and change the status quo: following guilt, people try to make amends for the perceived transgression, and following envy, people try to harm envied others. In this article, we present two experiments that study participants’ experience of guilt and envy when engaging in social decision making with machines and humans. The results showed that, though experiencing the same level of envy, people felt considerably less guilt with machines than with humans. These effects occurred both with subjective and behavioral measures of guilt and envy, and in three different economic games: public goods, ultimatum, and dictator game. This poses an important challenge for human-computer interaction because, as shown here, it leads people to systematically exploit machines, when compared to humans. We discuss theoretical and practical implications for the design of human-machine interaction systems that hope to achieve the kind of efficiency -- cooperation, fairness, reciprocity, etc. -- we see in human-human interaction.

Item Type:Articles
Additional Information:This work is supported by the National Science Foundation, under grant SES-0836004, and the Air Force Office of Scientific Research, under grant FA9550-09-1-0507
Glasgow Author(s) Enlighten ID:Marsella, Professor Stacy
Authors: de Melo, C., Marsella, S., and Gratch, J.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
Journal Name:ACM Transactions on Computer-Human Interaction
Publisher:ACM Press
ISSN (Online):1557-7325

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