About the webinar
The landscape of computational legal analysis is changing rapidly, and the emergence of large language models (LLMs) has fundamentally transformed the field. While traditional computational methods in law focused on relatively simple text processing and statistical techniques, LLMs now enable more advanced operations on legal texts that once required expert legal reasoning—often approaching or even surpassing human-level performance on these tasks. This webinar provides an updated framework for understanding how LLMs are reshaping legal scholarship and practice. Professor Michael A. Livermore examines three primary applications of LLMs in legal analysis: automated feature extraction and data generation from legal documents; prediction, classification, and description tasks; and engineering-focused studies that develop benchmarks and optimize model performance for legal domains. The rapid advancement of LLMs presents both unprecedented opportunities to scale legal analysis and significant challenges related to accuracy, bias, and professional responsibility. As these models become increasingly integrated into legal practice, understanding their capabilities and limitations has become essential for legal scholars, practitioners, and policymakers.
