Why we do need Explainable AI for Healthcare
June 30, 2022 Β· Declared Dead Β· π Diagnostic and Prognostic Research
"No code URL or promise found in abstract"
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Authors
Giovanni CinΓ , Tabea RΓΆber, Rob Goedhart, Ilker Birbil
arXiv ID
2206.15363
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.LG
Citations
19
Venue
Diagnostic and Prognostic Research
Last Checked
4 months ago
Abstract
The recent spike in certified Artificial Intelligence (AI) tools for healthcare has renewed the debate around adoption of this technology. One thread of such debate concerns Explainable AI and its promise to render AI devices more transparent and trustworthy. A few voices active in the medical AI space have expressed concerns on the reliability of Explainable AI techniques, questioning their use and inclusion in guidelines and standards. Revisiting such criticisms, this article offers a balanced and comprehensive perspective on the utility of Explainable AI, focusing on the specificity of clinical applications of AI and placing them in the context of healthcare interventions. Against its detractors and despite valid concerns, we argue that the Explainable AI research program is still central to human-machine interaction and ultimately our main tool against loss of control, a danger that cannot be prevented by rigorous clinical validation alone.
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