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.
References
Bernstein, D. J., & Lange, T. (2017). Post-quantum cryptography: Dealing with the fallout of physics success. IACR Cryptology ePrint Archive, 2017(314). https://eprint.iacr.org/2017/314
Gulyamov, S., Rustambekov, I., Narziev, O., & Xudayberganov, A. (2021). Draft Concept of the Republic of Uzbekistan in the Field of Development Artificial Intelligence for 2021-2030. Yurisprudensiya, 1, 107-21.
Allah Rakha, N. (2023). Cyber Law: Safeguarding Digital Spaces in Uzbekistan. International Journal of Cyber Law, 1(5). https://doi.org/10.59022/ijcl.53 retrieved from https://irshadjournals.com/index.php/ijcl/article/view/53
Islambek, R., & Iskandar, M. (2022). BLOCKCHAIN TECHNOLOGIES IN INTERNАTINАL DISPUTE RESOLUTION. Universum: экономика и юриспруденция, (5 (92)), 60-63.
Ashley, K. (2017). Artificial intelligence and legal analytics: New tools for law practice in the digital age. Cambridge University Press.
Allah Rakha, N. (2023). Ensuring Cyber-security in Remote Workforce: Legal Implications and International Best Practices. International Journal of Law and Policy, 1(3). https://doi.org/10.59022/ijlp.43 retrieved from https://irshadjournals.com/index.php/ijlp/article/view/43
Katz, D. M. (2017). Legal informatics. Cambridge University Press.
Kuhn, O. (2016). Predictive analytics in the legal practice: A primer. Artificial Lawyer. Retrieved from https://www.artificiallawyer.com/2016/11/07/predictive-analytics-in-the-legal-practice-a-primer/
Allah Rakha, N. (2023). Artificial Intelligence and Sustainability. International Journal of Cyber Law, 1(3). https://doi.org/10.59022/ijcl.42 retrieved from https://irshadjournals.com/index.php/ijcl/article/view/42
Marchant, G. E., Abbott, K. W., & Allenby, B. (2018). Innovative governance models for emerging technologies. Edward Elgar Publishing.
Schwartz, P. M., & Solove, D. J. (2011). The PII problem: Privacy and a new concept of personally identifiable information. New York University Law Review, 86, 1814-1894.
Allah Rakha, N. (2023). Navigating the Legal Landscape: Corporate Governance and Anti-Corruption Compliance in the Digital Age. International Journal of Management and Finance, 1(3). https://doi.org/10.59022/ijmf.39 Retrieved from https://irshadjournals.com/index.php/ijmf/article/view/39
Surden, H. (2014). Machine learning and law. Washington Law Review, 89(1), 87-115.
Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford University Press.
Allah Rakha, N. (2023). Revolution in Learning through Digitization: How Technology is changing the Landscape of Education. International Journal of Cyber Law, 1(3). https://doi.org/10.59022/ijcl.38 retrieved from https://irshadjournals.com/index.php/ijcl/article/view/38
Tsagourias, N., & Buchan, R. (2015). Research handbook on international law and cyberspace. Edward Elgar Publishing.
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