Algorithmic Fairness, Ethics, and Bias

This research area examines how individuals perceive fairness in algorithmic decision-making and how these perceptions affect the acceptance and adoption of AI systems. We investigate various fairness concerns, along with user responses to perceived bias, discrimination, and inequity in automated outcomes. Ethical considerations—such as justice, accountability, and privacy—are central to this work. By identifying the psychological and contextual factors that shape fairness and ethical evaluations, this research contributes to the development of AI systems that are efficient, fair, transparent, and socially responsible.