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- 01HKWAH1P6Q8N7SDJMPX9SSGDZ classification C1.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ date "2022".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ language "eng".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ type conference.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ hasPart 01HKWAPD8AKJGF6YS1EDCEHFZP.pdf.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ subject "Social Sciences".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ presentedAt urn:uuid:5bb59ac8-7e33-4ec3-928b-c2c61713d0cc.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ abstract "Algorithmic decision-making systems (ADMs) support an ever-growing number of decision- making processes. We conducted an online survey study in [omitted] (N=1082) to understand how lay people perceive and trust health ADMs. Inspired by the traditional Ability, Benevolence, and Integrity trust model (Mayer et al., 1995), this study investigated how trust is constructed in health ADMs. In addition, we investigated how trust construction differs between ADA Health (a chatbot that suggests a diagnosis) and IBM Watson (a system that suggest treatments for cancer). Our results show that perceptions of accuracy, fairness and control significantly differ between both contexts. Accuracy and fairness play the biggest role in predicting trust for both ADMs. Control plays a smaller, yet significant, role. Interestingly, control and accuracy play a bigger role in explaining trust for ADA Health than for IBM Watson. Moreover, goal appropriateness and AI concern proof to be good predictors for accuracy, fairness, and control. These results exemplify the importance to take broader contextual, algorithmic, and case specific characteristics into account when investigating trust construction in ADMs.".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ author 0B636B04-F0EE-11E1-A9DE-61C894A0A6B4.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ author 356171F8-F0EE-11E1-A9DE-61C894A0A6B4.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ author F5DF92F8-F0ED-11E1-A9DE-61C894A0A6B4.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ dateCreated "2024-01-11T13:14:03Z".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ dateModified "2024-10-29T18:41:36Z".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ name "People’s trust in algorithmic decision-making systems in health : a comparison between ADA health and IBM Watson".
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ pagination urn:uuid:3014404e-443c-4b2a-9c2d-e6566a7b6f2d.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ sameAs LU-01HKWAH1P6Q8N7SDJMPX9SSGDZ.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ sourceOrganization urn:uuid:dbb80a69-d6b0-4b84-83f2-ff7d7a13ace2.
- 01HKWAH1P6Q8N7SDJMPX9SSGDZ type C1.