Paper Number
2118
Paper Type
Short Paper
Abstract
Healthcare organizations benefit from disruptive AI technologies only if users perceive the affordances that AI technology provides for them. Yet, there's a lack of theoretical explanations and empirical evidence regarding how users perceive these benefits in processes with limited digital maturity. We examined perceptions of future AI prediction tool use in healthcare, exploring how past and current technology experiences shape views about AI-enabled diagnostic tools. Interviews were conducted with healthcare professionals in six UK hospitals regarding AI-enabled CDSS for electrocardiograms. Whilst we observed significant appetite for digitalization of electrocardiograms, interviewees were skeptical about the future of AI-based CDSS in this area. Integrating AI-based CDSS predictions were viewed as problematic to the perceived mismatch with traditional knowledge acquisition/validation methods and clinical practices. We argue, the development of AI-based technologies for health diagnostics requires an understanding of the epistemics of different areas of medicine and practices.
Recommended Citation
Mozaffar, Hajar and Cresswell, Kathrin, "“Should AI Predictions Be Done on Something Else?”: The Future of Artificial Intelligence-Based Algorithms for Health Predictions" (2024). ECIS 2024 Proceedings. 4.
https://aisel.aisnet.org/ecis2024/track18_healthit/track18_healthit/4
“Should AI Predictions Be Done on Something Else?”: The Future of Artificial Intelligence-Based Algorithms for Health Predictions
Healthcare organizations benefit from disruptive AI technologies only if users perceive the affordances that AI technology provides for them. Yet, there's a lack of theoretical explanations and empirical evidence regarding how users perceive these benefits in processes with limited digital maturity. We examined perceptions of future AI prediction tool use in healthcare, exploring how past and current technology experiences shape views about AI-enabled diagnostic tools. Interviews were conducted with healthcare professionals in six UK hospitals regarding AI-enabled CDSS for electrocardiograms. Whilst we observed significant appetite for digitalization of electrocardiograms, interviewees were skeptical about the future of AI-based CDSS in this area. Integrating AI-based CDSS predictions were viewed as problematic to the perceived mismatch with traditional knowledge acquisition/validation methods and clinical practices. We argue, the development of AI-based technologies for health diagnostics requires an understanding of the epistemics of different areas of medicine and practices.
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