ABA Legal Rebel John Tredennick speaks about How GPT and Other Large Language Models are Changing Ediscovery​ – Podcast

I had the opportunity to join Victor Li, legal affairs writer for the ABA Journal on the Legal Rebels podcast, to talk about ChatGPT and the similarities between this emerging technology and TAR for investigations and discovery. 

In the 2010s, the emergence of technologically assisted review (TAR) revolutionized the e-discovery process, garnering widespread attention and excitement similar to the buzz surrounding ChatGPT. TAR, a cutting-edge approach to sifting through vast amounts of electronic data during legal investigations, offered a more efficient and accurate alternative to traditional manual review methods.

The advent of large language models like GPT has further extended the potential to ediscovery. These language models possess unparalleled capabilities in understanding natural language, enabling them to assist legal professionals in tasks such as document classification, entity recognition, and even predictive coding. By processing and analyzing vast volumes of legal texts, such as case law, statutes, and regulatory documents, GPT and similar language models could identify crucial patterns and legal insights that may have been challenging to spot through manual review alone.