Reflection Machines: Supporting Effective Human Oversight Over Medical Decision Support Systems

Human decisions are increasingly supported by decision support systems (DSS). Humans are required to remain "on the loop," by monitoring and approving/rejecting machine recommendations. However, use of DSS can lead to overreliance on machines, reducing human oversight. This paper proposes...

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Κύριοι συγγραφείς: Haselager, Pim (Συγγραφέας) ; Schraffenberger, Hanna (Συγγραφέας) ; Thill, Serge (Συγγραφέας) ; Fischer, Simon (Συγγραφέας) ; Lanillos, Pablo (Συγγραφέας) ; Groes, Sebastiaan van de (Συγγραφέας) ; Hooff, Miranda van (Συγγραφέας)
Τύπος μέσου: Ηλεκτρονική πηγή Άρθρο
Γλώσσα:Αγγλικά
Έλεγχος διαθεσιμότητας: HBZ Gateway
Interlibrary Loan:Interlibrary Loan for the Fachinformationsdienste (Specialized Information Services in Germany)
Έκδοση: 2024
Στο/Στη: Cambridge quarterly of healthcare ethics
Έτος: 2024, Τόμος: 33, Τεύχος: 3, Σελίδες: 380-389
Άλλες λέξεις-κλειδιά:B Decision-making
B human oversight
B medical decision support system
B human–computer interaction
B meaningful human control
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520 |a Human decisions are increasingly supported by decision support systems (DSS). Humans are required to remain "on the loop," by monitoring and approving/rejecting machine recommendations. However, use of DSS can lead to overreliance on machines, reducing human oversight. This paper proposes "reflection machines" (RM) to increase meaningful human control. An RM provides a medical expert not with suggestions for a decision, but with questions that stimulate reflection about decisions. It can refer to data points or suggest counterarguments that are less compatible with the planned decision. RMs think against the proposed decision in order to increase human resistance against automation complacency. Building on preliminary research, this paper will (1) make a case for deriving a set of design requirements for RMs from EU regulations, (2) suggest a way how RMs could support decision-making, (3) describe the possibility of how a prototype of an RM could apply to the medical domain of chronic low back pain, and (4) highlight the importance of exploring an RM’s functionality and the experiences of users working with it. 
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