Social Injustice, Group Membership and Epistemic Trust in Robots

This paper focuses on the intersection of social dynamics, knowledge production, and the implementation of identity features in robotic platforms. Concentrating on the concept of epistemic injustice, particularly in the context of trust, the study highlights the potential for justified distrust based on experienced injustice. The incorporation of social identity features, such as gender, signals group membership and can instigate trust based on assumed shared experiences of oppression. However, I argue that this can lead to a form of deception, especially for oppressed groups, as robots lack the embodied experience of living through inequality. The paper explores the risk of companies, largely composed of privileged individuals, potentially exploiting this trust. Three key suggestions for designing diverse robot identities are proposed: 1) Users should have control over robot features, emphasizing the non-fixed nature of robot identity 2) Diverse identity features should be combined to avoid overtrust and stereotyping 3) Robots should encourage users to rely on their own knowledge, fostering self-trust and preventing the perpetuation of privileged perspectives.