Evaluating the morality of violence against robots
John Archer, Martin F. Wilks, Katharina Sommer
- Year
- 2025
- Citations
- 3
- Access
- Open access
Abstract
The present study explored human moral perceptions of robots and examined how these perceptions vary based on the anthropomorphic features of the agent, the type of harm inflicted, and how the robot reacts to aversive stimuli. An online survey comprised first-year psychology students (N = 234) and participants recruited via social media (N = 63). Participants watched four videos depicting harmful or aversive scenarios containing a humanoid (NAO) or machine-like robot (Roomba). Scenarios included turning the robot off, physically abusing the robot, verbally abusing the robot and socially ostracizing the robot. The robots' protest behaviors towards the harmful or aversive scenarios were either physical protest, verbal protest, a combination of verbal and physical protests, or no protest at all. The humanoid robot received significantly more moral concern than the machine-like robot in the social ostracism and turn-off scenarios. However, there was no difference in moral concern observed between the humanoid and machine-like robot in the physical and verbal abuse scenarios. Some differences between scenarios were agent dependent. As predicted, both the machine-like and humanoid robot received significantly more moral concern in the physical abuse scenario than in all other scenarios. Finally, despite the hypothesized influence of protest on attributions of moral concern, no significant impact of protest was present. The present study provides a solid foundation for future research exploring the psychological and moral implications of robot mistreatment.
Keywords
Related papers
Artificial intelligence: a modern approach
1995
Are we ready for autonomous driving? The KITTI vision benchmark suite
Andreas Geiger, P Lenz, R. Urtasun
2012
Self-Organizing Maps
Teuvo Kohonen
1995
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
Martı́n Abadi, Ashish Agarwal, Paul Barham +17 more
2016