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      Judge Juan Manuel Padilla Garcia, ChatGPT, and a controversial medicolegal milestone

      1 , 2 , 3
      Indian Journal of Medical Sciences
      Scientific Scholar

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          Abstract

          Chat Generative Pre-Trained Transformer (ChatGPT) has revolutionized how we perceive artificial intelligence (AI).: Judge Juan Manuel Padilla Garcia created history by mentioning its use while passing judgment about an autistic child and payment for his medical treatment by his insurance company. The use of AI is not new and is helping the judiciary system in many ways. However, this judgment given on January 30, 2023, has ignited controversy among Judge Garcia’s peers and the global community (a Google search produced more than 70 million hits on February 5, 2023). EU has established guidelines that are to be followed before calling any AI tool trustworthy. This requires stringent compliance with the verification and due diligence process. In this instance, ChatGPT was used within 2 months of its launch, even when it has been shown to give incomplete, incorrect, and misleading answers in many instances. Hasty adaption of unproven technology, however good it may be, should not be our path. This might fuel the misguided fear amongst people about robots taking over from human judges.

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          Most cited references5

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          ChatGPT Goes to Law School

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            Is Open Access

            A general approach for predicting the behavior of the Supreme Court of the United States

            Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time-evolving random forest classifier that leverages unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve 70.2% accuracy at the case outcome level and 71.9% at the justice vote level. More recently, over the past century, we outperform an in-sample optimized null model by nearly 5%. Our performance is consistent with, and improves on the general level of prediction demonstrated by prior work; however, our model is distinctive because it can be applied out-of-sample to the entire past and future of the Court, not a single term. Our results represent an important advance for the science of quantitative legal prediction and portend a range of other potential applications.
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              Courts and artificial intelligence

                Author and article information

                Journal
                Indian Journal of Medical Sciences
                IJMS
                Scientific Scholar
                1998-3654
                0019-5359
                2023
                March 02 2023
                March 11 2023
                : 75
                : 3-8
                Affiliations
                [1 ]Professor and Head of Clinical Hematology, Department of Clinical Hematology, Mahatma Gandhi University of Medical Sciences and Technology, Jaipur, India,
                [2 ]Department of Interventional Cardiology, Michigan Physicians Group, Troy, United States,
                [3 ]AKSP Solutions, Auckland, New Zealand,
                Article
                10.25259/IJMS_31_2023
                02628bce-ac03-4f73-a29b-669f9e735bee
                © 2023
                History

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