Hiding Behind Machines: Artificial Agents May Help to Evade Punishment

• Published in: Science and engineering ethics Vol. 28; no. 2; p. 19
• Main Authors: Feier, Till, Gogoll, Jan, Uhl, Matthias
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-04-2022; Springer Nature B.V
• Subjects: Agents (artificial intelligence); Algorithms; Autonomous vehicles; Behavior; Biomedical Engineering and Bioengineering; Decision making; Delegation of authority; Education; Engineering; Ethics; Expected utility; Experiments; Humans; Incentives; Laboratories; Medicine/Public Health; Morality; Morals; Original Research/Scholarship; Philosophy; Philosophy of Science; Punishment; Questions; Ethics; Automation; Responsibility; Algorithm; Experiment
• ISSN: 1353-3452; 1471-5546; 1471-5546
• DOI: 10.1007/s11948-022-00372-7

The transfer of tasks with sometimes far-reaching implications to autonomous systems raises a number of ethical questions. In addition to fundamental questions about the moral agency of these systems, behavioral issues arise. We investigate the empirically accessible question of whether the imposition of harm by an agent is systematically judged differently when the agent is artificial and not human. The results of a laboratory experiment suggest that decision-makers can actually avoid punishment more easily by delegating to machines than by delegating to other people. Our results imply that the availability of artificial agents could provide stronger incentives for decision-makers to delegate sensitive decisions.