Full Description
Millions of individuals worldwide struggle to understand and assert their legal rights without legal representation. Equalizing Justice examines how AI and other technologies can address this access to justice crisis by providing unrepresented litigants with knowledge and skills traditionally available only through lawyers. This volume takes a needs-first approach, identifying tasks that unrepresented litigants must complete and mapping specific technologies to each task, such as generative AI, computational logic, and document automation. The book highlights real-world applications, demonstrating proven impact, and presents case studies and interviews to explore both the potential positive outcomes and potential challenges of AI for access to justice. Equalizing Justice proves that AI technologies offer unprecedented opportunities to create equitable justice systems serving everyone, not just those who can afford representation. The volume argues for legal AI assistants as a public good that should be accessible to all.
Contents
Introduction; Part I. Addressing the Crisis in Access to Justice with Legal AI: 1. The global access to justice crisis; 2. The language gap; 3. The needs of civil litigants; Part II. Automatic Legal Tasks with AI and Other Technologies: 4. Introduction to generative AI; 5. The origins of legal AI; 6. Computation logic; 7. Machine learning; 8. Document automation; 9. Interactive legal technologies; Part III. Promising Applications: 10. Putting it all together; 11. Online dispute resolution; 12. Applications of generative AI for access to justice; Part IV. Today's Access to Justice Systems: 13. Today's access to justice systems; Part V. Barriers and Risks: 14. The UPL barrier; 15. AI assurance; Part VI. Recommendations: 16. Technical methods for evaluating AI applications for legal tasks; 17. Institutional reform for AI in legal services; Conclusion.
