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Judicial Decision under Ambiguity and Predictive Justice| title | Judicial Decision under Ambiguity and Predictive Justice |
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| start_date | 2023/04/13 |
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| schedule | 11h-12h |
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| online | no |
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| location_info | salle R2-21 |
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| summary | Going to court is always a tough decision to take. Indeed, you never know your probabilities to win, the time it will require and how much you will win or spend. Predictive justice is an AI tool that uses big data to bring information to lawyers and litigants about their probabilities to win and the potential rewards. This objective information should reduce the difficulty to make the ambiguous decision of going to court or not. Seeing judicial decision as a decision under natural ambiguity, we test the effect of three types of information on attitudes:partial ambiguity, risk and similarity. In a complement study, we elicit the willingness to pay to access this information. Results first show that attitudes toward ambiguity differ under natural and artificial settings. Then, under both settings, the information provided to a complete ambiguous situation changes the behaviors but with no major difference according to the content of information.The valuations of the types of information are relatively in line with these attitudes. |
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| responsibles | Chassagnon, Apouey |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2023/03/29 14:31 UTC |
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