AI-Driven Justice: Evaluating the Impact of Artificial Intelligence on Legal Systems

Abstract

This integrative literature review (ILR) examines the impact of artificial intelligence (AI) on legal systems, focusing on technologies such as natural language processing (NLP), machine learning (ML), and AI-driven decision support systems. The research problem addresses the need to understand how AI enhances efficiency, precision, and data handling in legal operations, transforming tasks like document analysis and decision-making procedures. The ILR aims to comprehensively understand AI integration in legal systems, considering its advantages and difficulties. It is guided by a conceptual framework based on AI, legal analytics, and decision support systems to enhance efficiency, accuracy, and innovation. Using a systematic methodology, the review integrates and examines existing research, evaluating AI's tangible benefits and ethical implications. The findings indicate that while AI can revolutionize legal systems, the study underscores the importance of continuous oversight, frequent evaluations, and developing AI models with the ability to identify and correct biases. Future research should prioritize longitudinal studies to assess AI's enduring effects, address ethical considerations, and encompass various legal and geographical contexts. Encouraging cross-disciplinary cooperation and utilizing diverse research methodologies is crucial to ensure that AI improves legal services while maintaining the integrity and impartiality of judicial procedures, and it makes the audience feel included and part of the AI revolution in legal systems.

Keywords:

Artificial intelligence, Legal systems, Natural language processing, Machine learning, AI-driven decision support systems, Document analysis, Judicial decision-making, Ethical challenges, Operational efficiency, Bias mitigation, Transparency, Skill degradation, Job displacement, Longitudinal studies, Interdisciplinary collaboration, Data management, Ethical integration