Abstract

This research paper traces the historical evolution of Artificial Intelligence in law, from Gottfried Wilhelm Leibniz’s visionary concept of a “calculus of justice” to the modern era of Large Language Models. It explores key phases in this development, including early Jurimetrics, the knowledge representation era, and the current machine learning revolution. The study highlights how each phase built upon the limitations of its predecessors, driving innovation in legal technology. It examines the transformative impact of AI on legal practice, from predictive justice tools to automated contract analysis, and discusses the emergence of legal tech startups and research centers like Stanford CodeX. The research paper also delves into critical ethical and regulatory challenges, including algorithmic bias, transparency, and accountability in AI-driven legal systems. It analyzes the global regulatory landscape, comparing approaches in the EU, US, and India, and emphasizes the need for balanced governance that fosters innovation while safeguarding fundamental rights. By situating AI in law within a broader historical and socio-technical context, this research provides valuable insights into the complex interplay between technology, law, and society. It concludes by calling for enhanced collaboration between legal professionals, computer scientists, and policymakers to shape a future where AI serves the broader interests of justice and equity in an increasingly algorithmic legal landscape.

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