Tittle: Ethical Considerations of Facial Expression Recognition AI for Human-Robot Interactions

Authors: De’Aira Bryant and Ayanna Howard

Abstract: This paper explores the ethical considerations surrounding Facial Expression Recognition (FER) AI in Human-Robot Interactions (HRI), focusing on whether and how robots should perceive and interpret human facial expressions. It examines the implications for privacy, user consent, and societal integration, applying existing frameworks and proposing four ethical approaches: Ethical Non-Use, Visible Cue Perception, Necessary Informed Consent, and Contextual Appropriateness. A privacy risk matrix is introduced to evaluate these approaches, highlighting potential risks such as invasion of privacy, algorithmic bias, data misuse, and consent mismanagement. The paper underscores the need for proactive measures in AI development, including auditing, bias mitigation, and contextually sensitive safeguards, to ensure responsible deployment of FER technology. By addressing these ethical dimensions, the paper contributes to advancing a future where AI technologies in robotics are aligned with ethical principles, promoting fairness, transparency, and user trust.​