Health care

Communication

Healthcare industry

Social psychology

Economic Justice

Operating system

Computer science

Beneficence

Psychology

Applied psychology

Political science

Workload

Autonomy

Clinical psychology

Stressor

Affect (linguistics)

Information Systems Frontiers

Artificial Intelligence (AI) technology is transforming the healthcare sector. However, despite this, the associated ethical implications remain open to debate. This research investigates how signals of AI responsibility impact healthcare practitioners’ attitudes toward AI, satisfaction with AI, AI usage intentions, including the underlying mechanisms. Our research outlines autonomy, beneficence, explainability, justice, and non-maleficence as the five key signals of AI responsibility for healthcare practitioners. The findings reveal that these five signals significantly increase healthcare practitioners’ engagement, which subsequently leads to more favourable attitudes, greater satisfaction, and higher usage intentions with AI technology. Moreover, ‘techno-overload’ as a primary ‘techno-stressor’ moderates the mediating effect of engagement on the relationship between AI justice and behavioural and attitudinal outcomes. When healthcare practitioners perceive AI technology as adding extra workload, such techno-overload will undermine the importance of the justice signal and subsequently affect their attitudes, satisfaction, and usage intentions with AI technology.

Accelerating AI Adoption with Responsible AI Signals and Employee Engagement Mechanisms in Health Care