Automating Sexual Injustice: Epistemic Injustice in Fembot Design and Feminist Directions for Equitable HRI

A new research paper titled 'Automating Sexual Injustice: Epistemic Injustice in Fembot Design and Feminist Directions for Equitable HRI' presents a critical analysis of current AI-enabled female sex robots. Authored by Surabhi Bhardwaj and presented at the Equitable Robotics for Wellbeing Workshop during the ACM/IEEE International Conference on Human-Robot Interaction (HRI 2026), the 5-page peer-reviewed study argues that so-called 'fembots' are designed primarily through a lens of male-centric bias and pornographic stereotypes rather than empirical understanding of female sexuality.

Using philosopher Miranda Fricker's framework of testimonial and hermeneutical injustice, the paper demonstrates how current fembot interfaces systematically discredit women's lived sexual knowledge while privileging male-centered fantasies. The analysis reveals how these design choices perpetuate harmful stereotypes and ignore established research on female sexual physiology, creating what the author terms a 'failure in equitable robotics.'

The paper proposes three concrete Feminist Design Directions to address these issues: empirical grounding in actual sexual research, epistemic plurality that incorporates diverse perspectives, and active consent modeling. These directions are informed by Donna Haraway's concept of 'Situated Knowledge' and include specific evaluation criteria for implementation. The goal is to facilitate a transition toward evidence-based intimate AI that prioritizes epistemic justice, mutuality, and inclusive design.

Ultimately, the research calls for a fundamental redesign of intimate AI systems to serve not just mainstream users but specifically marginalized communities including disabled, neurodivergent, and LGBTQ+ individuals. The paper represents a significant intervention in the growing field of human-robot interaction, challenging developers to move beyond reinforcing harmful stereotypes and toward creating genuinely equitable robotic systems.