Harnessing the Power of Legal-Tech: AI-Driven Predictive Analytics in the Legal Domain
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DOI:
https://doi.org/10.59022/ujldp.69Keywords:
Legal-Tech, Artificial Intelligence, Predictive Analytics, E-discovery, Legal Research, Case Outcome Prediction, Contract Analysis, Data Privacy, Algorithmic Fairness, Liability, Legal Challenges, Best PracticesAbstract
This article examines the growing role of Legal-Tech and artificial intelligence (AI) in the legal domain, with a particular focus on AI-driven predictive analytics. The study aims to provide a comprehensive analysis of the key applications, ethical considerations, and case studies related to AI-driven predictive analytics in legal practice, while identifying challenges and proposing recommendations for legal professionals and policymakers. Through a literature review and analysis of practical applications, the research explores how AI-driven predictive analytics tools such as e-discovery, legal research, case outcome prediction, and contract analysis are revolutionizing the legal landscape. The ethical considerations of integrating AI-driven predictive analytics into the legal domain, such as data privacy and security, algorithmic fairness and transparency, and liability and accountability, are discussed. Furthermore, the article analyzes various case studies and practical applications, highlighting legal challenges and resolutions, lessons learned, and best practices. By interpreting the results and comparing the legal landscape for AI-driven predictive analytics across different industries and countries, the article provides valuable insights into the potential future developments and challenges that may arise as Legal-Tech continues to evolve. The conclusion offers recommendations for legal professionals and policymakers on how to successfully integrate AI-driven predictive analytics into legal practice while addressing ethical and legal concerns. The article also proposes future directions for legal research and policy development in the context of Legal-Tech and AI-driven predictive analytics.
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