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Zulueta-Coarasa, T., Jug, F., Hartley, M., Mathur, A., Moore, J., Muñoz-Barrutia, A., Anita, L., Babalola, K., Bankhead, P., Gilloteaux, P., Gogoberidze, N., Jones, M., Kleywegt, G.J., Korir, P. and Kreshuk, A. (2023) MIFA: Metadata, Incentives, Formats, and Accessibility Guidelines to Improve the Reuse of AI Datasets for Bioimage Analysis. arXiv: 2311.10443.

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• TITLE: Artificial Intelligence-Powered Legal Document Processing for Medical Negligence Cases: A Critical Review

  AUTHORS: Gobind Naidu, Vicknesh Krishnan

  KEYWORDS: Artificial Intelligence, Medical Negligence, Legal Document Processing, Ethical Implications, Regulatory Frameworks

  JOURNAL NAME: International Journal of Intelligence Science, Vol.15 No.1, January 27, 2025

  ABSTRACT: This critical review looks at the assessment of the application of artificial intelligence in handling legal documents with specific reference to medical negligence cases with a view of identifying its transformative potentialities, issues and ethical concerns. The review consolidates findings that show the impact of AI in improving the efficiency, accuracy and justice delivery in the legal profession. The studies show increased efficiency in speed of document review and enhancement of the accuracy of the reviewed documents, with time efficiency estimates of 60% reduction of time. However, the review also outlines some of the problems that continue to characterize AI, such as data quality problems, biased algorithms and the problem of the opaque decision-making system. This paper assesses ethical issues related to patient autonomy, justice and non-malignant suffering, with particular focus on patient privacy and fair process, and on potential unfairness to patients. This paper’s review of AI innovations finds that regulations lag behind AI developments, leading to unsettled issues regarding legal responsibility for AI and user control over AI-generated results and findings in legal proceedings. Some of the future avenues that are presented in the study are the future of XAI for legal purposes, utilizing federated learning for resolving privacy issues, and the need to foster adaptive regulation. Finally, the review advocates for Legal Subject Matter Experts to collaborate with legal informatics experts, ethicists, and policy makers to develop the best solutions to implement AI in medical negligence claims. It reasons that there is great potential for AI to have a deep impact on the practice of law but when done, it must do so in a way that respects justice and on the Rights of Individuals.