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  • Title: ➤  The Influence Of Unrealistic Recommendations By Algorithms An Law Experts On Unexperienced Judges
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Algorithms are increasingly implemented in the criminal justice system to assist and support judges especially in decisions requiring a prognosis (e.g., parole decisions). The aim of these algorithmic support systems is to assist but also to avoid biases and heuristics in the decision process. The aim of the present study is to explore the impact of algorithmic as well as legal human experts’ recommendations on judicial decisions in the context of parole decisions because these judgments require a prognosis of recidivism. Trainee lawyers are presented ten different (pretested) fictional cases. The cases have a high complexity because they contain mixed information (in favor, in disfavor, and irrelevant information) about the defendant. The trainee lawyers’ task is to review all ten cases and to make a parole decision, to assess the risk of recidivism, and to self-asses their confidence in their decision. In three recommendation conditions manipulated between the trainee lawyer, they receive a recommendation on how to decide on the question of parole in form of a risk score. This risk score is allegedly either provided by a supervision group of experienced judges (legal human experts’ recommendation) or by an algorithmic system that presumably bases its recommendation on data of comparable past cases (algorithmic recommendation). For the purpose of the study, the risk score is chosen randomly so that it is perceived as more realistic. We investigate the impact of these recommendations on judicial decisions by comparing the recommendation conditions (legal human experts vs. algorithm) to a control condition in which the trainee lawyers do not receive a risk score as a recommendation (i.e., baseline condition).

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  • Added Date: 2023-01-30 07:01:16
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