Abstract
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.
Highlights
Artificial Intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence (Russell & Norvig, 2016)
Despite recognition of the signals, there has been scant research empirically examining their effects on attitudes to, satisfaction, and usage intentions with AI technology
Our research model draws on signal-mechanism-consequence (SMC) theory (Li & Wu, 2018; Pavlou & Dimoka, 2006) and examines how autonomy, beneficence, explainability, justice, and nonmaleficence all serve as signals to healthcare practitioners steering their decisions to engage with workplace AI
Summary
Artificial Intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence (Russell & Norvig, 2016). The global healthcare AI market worth is expected to reach USD 190.6 billion in 2025 (Singh, 2020). Many countries including China, are experiencing dramatic digitisation in the healthcare sector. China takes the lead in AI-based diagnostic imaging equipment (Nikkei Asia, 2020). AI technology is transforming the healthcare industry and offering great support to healthcare practitioners. Its implementation is evidenced in areas of medical imaging, disease diagnostics, drug discovery, various sensors, and devices to track patients’ health status in real time
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