In this paper we present a lightweight psychometric tool that we developed and published online to involve medical practitioners and specialists in the impact assessment of some general negative effects of medical Artificial Intelligence on their practice and profession. This tool can be adopted in, and possibly adapted to, different settings, to perform more focused AI impact assessment within specific medical settings. We applied the tool to a large and heterogeneous sample of medical doctors (N=121) and we discuss the main findings from this user study.

Cabitza, F., Campagner, A., Cavosi, V. (2021). Assessing the impact of medical AI: A survey of physicians' perceptions. In ACM International Conference Proceeding Series (pp.225-231). Association for Computing Machinery [10.1145/3472813.3473195].

Assessing the impact of medical AI: A survey of physicians' perceptions

Cabitza F.;Campagner A.;
2021

Abstract

In this paper we present a lightweight psychometric tool that we developed and published online to involve medical practitioners and specialists in the impact assessment of some general negative effects of medical Artificial Intelligence on their practice and profession. This tool can be adopted in, and possibly adapted to, different settings, to perform more focused AI impact assessment within specific medical settings. We applied the tool to a large and heterogeneous sample of medical doctors (N=121) and we discuss the main findings from this user study.
paper
Algorithmic Impact Assessment; Artificial Intelligence Impact Assessment; medical artificial intelligence; unintended consequences of automated decision systems;
English
5th International Conference on Medical and Health Informatics, ICMHI 2021 - 14 May 2021 through 16 May 2021
2021
ACM International Conference Proceeding Series
9781450389846
2021
225
231
none
Cabitza, F., Campagner, A., Cavosi, V. (2021). Assessing the impact of medical AI: A survey of physicians' perceptions. In ACM International Conference Proceeding Series (pp.225-231). Association for Computing Machinery [10.1145/3472813.3473195].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/394388
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