Robot Eyes Wide Shut: Understanding Dishonest Anthropomorphism

Abstract

The goal of this paper is to advance design, policy, and ethics scholarship on how engineers and regulators can protect consumers from deceptive robots and artificial intelligences that exhibit the problem of dishonest anthropomorphism. The analysis expands upon ideas surrounding the principle of honest anthropomorphism originally formulated by Margot Kaminsky, Mathew Ruben, William D. Smart, and Cindy M. Grimm in their groundbreaking Maryland Law Review article, "Averting Robot Eyes." Applying boundary management theory and philosophical insights into prediction and perception, we create a new taxonomy that identifies fundamental types of dishonest anthropomorphism and pinpoints harms that they can cause. To demonstrate how the taxonomy can be applied as well as clarify the scope of the problems that it can cover, we critically consider a representative series of ethical issues, proposals, and questions concerning whether the principle of honest anthropomorphism has been violated.