Public Opinion and the Politics of the Killer Robots Debate

19 Pages Posted: 23 Aug 2015

See all articles by Michael C. Horowitz

Michael C. Horowitz

University of Pennsylvania - Department of Political Science

Date Written: August 5, 2015


The possibility that today’s drones could become tomorrow’s killer robots has attracted the attention of people around the world. Scientists and business leaders from Stephen Hawking to Elon Musk recently signed a letter urging the world to ban autonomous weapons. Part of the argument against these systems is that they violate the public conscience provision of the Martens Clause due to public opposition, making them illegal under international law. What, however, does the US public think of these systems? Existing research suggests widespread US public opposition, but only asked people about support for autonomous weapons in a vacuum. This paper uses two survey experiments to test the conditions in which public opposition rises and falls. The results demonstrate that public opposition to autonomous weapons is extremely contextual. Fear of other countries or non-state actors developing these weapons makes the public significantly more supportive of developing them. The public also becomes much more willing to actually use autonomous weapons when the alternative is sending in US troops. Beyond contributing to ongoing academic debates about casualty aversion, the microfoundations of foreign policy, and weapon systems, these results suggest the need for modesty when making claims about how the public views new, unknown, technologies such as autonomous weapons.

Keywords: autonomous weapons, killer robots, public opinion

Suggested Citation

Horowitz, Michael C., Public Opinion and the Politics of the Killer Robots Debate (August 5, 2015). Available at SSRN: or

Michael C. Horowitz (Contact Author)

University of Pennsylvania - Department of Political Science ( email )

Stiteler Hall
Philadelphia, PA 19104
United States

Register to save articles to
your library


Paper statistics

Abstract Views
PlumX Metrics