algorithmic decision-making (ADM) systems are heavily used by businesses, governments, and the nonprofit sector. Their adoption by the public is important for their optimal performance, but the impact of user percepti...
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algorithmic decision-making (ADM) systems are heavily used by businesses, governments, and the nonprofit sector. Their adoption by the public is important for their optimal performance, but the impact of user perceptions on ADM system adoption is not well-understood. We develop a theoretical model that examines the effect of a user's transparency concern on perceived fairness, accountability, and privacy;it then captures the effect of these on trust in, usefulness of, and finally, intention to adopt an ADM system. We use results from a large-scale survey among 2612 Dutch citizens to test our research model. Our results shed light on the role of transparency concern on trust and perceived usefulness through its impact on perceived fairness, account-ability, and privacy. The survey data of a large representative group enables us to capture public views on ADM systems. Finally, the study provides a comparative view of ADM system percep-tions for different application scenarios. Our insights on differences between scenarios can help organizations prioritize relevant measures to improve the adoption of their ADM systems.
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