Human cooperation when acting through autonomous machines

de Melo, C. M., Marsella, S. and Gratch, J. (2019) Human cooperation when acting through autonomous machines. Proceedings of the National Academy of Sciences of the United States of America, 116(9), pp. 3482-3487. (doi: 10.1073/pnas.1817656116) (PMID:30808742) (PMCID:PMC6397531)

Abstract

Recent times have seen an emergence of intelligent machines that act autonomously on our behalf, such as autonomous vehicles. Despite promises of increased efficiency, it is not clear whether this paradigm shift will change how we decide when our self-interest (e.g., comfort) is pitted against the collective interest (e.g., environment). Here we show that acting through machines changes the way people solve these social dilemmas and we present experimental evidence showing that participants program their autonomous vehicles to act more cooperatively than if they were driving themselves. We show that this happens because programming causes selfish short-term rewards to become less salient, leading to considerations of broader societal goals. We also show that the programmed behavior is influenced by past experience. Finally, we report evidence that the effect generalizes beyond the domain of autonomous vehicles. We discuss implications for designing autonomous machines that contribute to a more cooperative society.

• Item Type: Articles
• Additional Information: This work is supported by the Air Force Office ofScientific Research, under Grant FA9550-14-1-0364, and the US Army.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Marsella, Professor Stacy
• Authors: de Melo, C. M., Marsella, S., and Gratch, J.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Journal Name: Proceedings of the National Academy of Sciences of the United States of America
• Publisher: National Academy of Sciences
• ISSN: 0027-8424
• ISSN (Online): 1091-6490
• Published Online: 11 February 2019
• Copyright Holders: Copyright © 2019 The Authors
• First Published: First published in Proceedings of the National Academy of Sciences of the United States of America 116(9):3482-3487
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher