The Impact of AI Ethicality on Clinical Decision-making: The Role of AI Trustworthiness and Representativeness

There are critical ethical concerns about using artificial intelligence (AI) in healthcare. Healthcare professionals are more likely to adopt AI if they believe in its capability and perceive alignment in clinical decisions with ethical principles. Although previous studies have shown ethical issues in clinical decision making, empirical research investigating how AI ethicality influences healthcare professionals’ perceptions of AI performance expectancy remains limited. Drawing on integrated ethical decision making, we propose a research model to examine the effects of AI ethicality and AI trustworthiness on healthcare professionals’ perceptions of AI performance expectancy. Moreover, we explore whether AI representativeness in adhering to EDI (equity, diversity, inclusion) strengthens the impact of AI ethicality on AI performance expectancy. A vignette-based methodology is proposed to test the model using data collected from healthcare professionals. This research aims to contribute to the literature by providing empirical evidence on how ethical and representative AI systems shape healthcare professionals’ expectations.