Підвищення довіри до ШІ в юриспруденції через пояснюваний ШІ

Abstract

AI is rapidly changing legal practice, automating tasks like contract analysis and legal research. However, the "black box" nature of many AI models, especially LLMs, creates concerns about trust and accountability in law, where accuracy is crucial. Risks of bias and lack of transparency hinder responsible AI adoption. This article proposes using Explainable AI (XAI) methods, tailored for the legal field, to build trust and ensure accountability in legal AI systems. We examine current challenges and offer a conceptual approach for developing XAI solutions that provide understandable explanations of AI decisions for legal professionals.