CareLit Fachartikel
Levels of explicability for medical artificial intelligence: What do we normatively need and what can we technically reach?
Ursin, F.; Lindner, F.; Ropinski, T.; Salloch, S.; Timmermann, C. · Ethik in der Medizin · 2023 · Heft 4 · S. 173 bis 199
Dokument
346153
CareLit-ID
Jahr
2023
Publikation
PDF
ja
Volltext
DOI
–
zitierfähig
Bibliografische Angaben
Zusammenfassung
IntroductionThe umbrella term explicability refers to increasing the understanding of black-box artificial intelligence (AI) systems (Robbins 2019). Reducing the opacity of black-box AI systems is crucial for medical AI applications because of the moral and professional responsibility of physicians to provide reasons for decisions (Swartout 1983). As such, commentators claim that medical AI systems “must have an explainable architecture, designed to align with human cognitive decision-making processes familiar to physicians, and directly tied to clinical evidence” (Char et al. 2020). This is because the output o…
Schlagworte
Explizierbarkeit
Künstliche Intelligenz
medizinische Ethik
informierte Einwilligung
Transparenz
Interpretierbarkeit
Artificial Intelligence
Ethics
Medical
Informed Consent
Transparency
Decision Making
Patient Care
Ethik in der Medizin
