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      ‘Just like I thought’: Street‐level bureaucrats trust AI recommendations if they confirm their professional judgment

      1 , 2 , 3
      Public Administration Review
      Wiley

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          Abstract

          Artificial Intelligence is increasingly used to support and improve street‐level decision‐making, but empirical evidence on how street‐level bureaucrats' work is affected by AI technologies is scarce. We investigate how AI recommendations affect street‐level bureaucrats' decision‐making and if explainable AI increases trust in such recommendations. We experimentally tested a realistic mock predictive policing system in a sample of Dutch police officers using a 2 × 2 factorial design. We found that police officers trust and follow AI recommendations that are congruent with their intuitive professional judgment. We found no effect of explanations on trust in AI recommendations. We conclude that police officers do not blindly trust AI technologies, but follow AI recommendations that confirm what they already thought. This highlights the potential of street‐level discretion in correcting faulty AI recommendations on the one hand, but, on the other hand, poses serious limits to the hope that fair AI systems can correct human biases.

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          Most cited references56

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          Longitudinal data analysis using generalized linear models

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            The case for motivated reasoning.

            Ziva Kunda (1990)
            It is proposed that motivation may affect reasoning through reliance on a biased set of cognitive processes--that is, strategies for accessing, constructing, and evaluating beliefs. The motivation to be accurate enhances use of those beliefs and strategies that are considered most appropriate, whereas the motivation to arrive at particular conclusions enhances use of those that are considered most likely to yield the desired conclusion. There is considerable evidence that people are more likely to arrive at conclusions that they want to arrive at, but their ability to do so is constrained by their ability to construct seemingly reasonable justifications for these conclusions. These ideas can account for a wide variety of research concerned with motivated reasoning.
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              "Why Should I Trust You?"

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                Author and article information

                Journal
                Public Administration Review
                Public Administration Review
                Wiley
                0033-3352
                1540-6210
                March 2023
                January 22 2023
                March 2023
                : 83
                : 2
                : 263-278
                Affiliations
                [1 ] Institute of Public Administration Leiden University The Hague The Netherlands
                [2 ] National Police Lab AI Utrecht University Utrecht The Netherlands
                [3 ] Utrecht University School of Governance Utrecht The Netherlands
                Article
                10.1111/puar.13602
                69ad0725-2ede-41cb-8e74-acd1f5278072
                © 2023

                http://creativecommons.org/licenses/by/4.0/

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