Will Generative AI awaken the need for serious focus legal research education?
The introduction of Generative AI to the practice of law has been anything but smooth. First there was the unfortunate case of Mr. Schwartz who used Chat GPT-3 to write a brief complete with hallucinated cases which he submitted to a federal court in New York. Judge castell of the Southern District of New York noted that the attorneys had “abandoned their responsibilities.” More recently there have been the controversies related to a Stanford Human-Centered Artificial Intelligence (HAI) team study criticizing the quality of the Lexis and WL generative AI products. The study was so roundly criticized that it was revised and reissued. The HAI study’s conclusions regarding the Westlaw Precision AI and Lexis+ AI products requires a nuanced understanding of the HAI benchmarking definitions. The HAI studies flag a wide range of issues including some which appear to be subjective. Problems noted range from a “true hallucination” to a factual error e.g. name of a judge, to the length of responses. Everyone agrees that legal generative AI products require serious benchmarking studies, but Stanford fumbled the ball.
Selling any new legal technology to law firms is hard. Selling generative AI products to law firms appears to be moving at a glacial pace and this post will explore some of the obstacles to adoption of GAI in legal. There are probably more stakeholders in the mix than I have seen for any prior technology. Most noticeable is the presence of the General Counsel/Ethics Officer who in many firms is waving cautionary flags. Then there are clients who are sending conflicting signals limiting, requiring or banning use of GAI products on their matters. Add to this stew of ambiguity, the proliferation of judges rules restricting or establishing requirements regarding not only the use of generative AI but AI products in general. (AI is probably in 90% of the products the average lawyer uses including their smartphone).
Why are law firms are holding off generative AI adoption for legal research?
Read the full post on Legal TechHubContinue Reading Generative AI Risk in Legal Research: Is the Fault in the Technology or in Ourselves? Answer is Both
and the appointment of Daniel Lewis as US CEO. Daniel Lewis is well known in the U.S. legal tech community as the co-Founder of Ravel Law (later acquired by LexisNexis). Ravel Law 
dramatic breakthroughs in neural net technology to natural language processing (NLP). Pablo Arredondo, Co-Founder / Chief Innovation Officer, Casetext provided an intensely passionate tutorial on the history of AI through the centuries.
improve the quality of research results. Westlaw Precision will be sold as an upgrade to Westlaw Edge. Westlaw Precision is tackling the gnarly and perennial problem of language ambiguity by doubling down on taxonomy. At launch, Westlaw Precision covers 8 topics (Commercial law, Federal Civil Procedure, Federal Discovery and Evidence, Federal Remedies, Federal Class Actions, Employment, Securities, and Anti-trust.) Fifteen new topics will be released through 2023. Only the most recent 12 years of caselaw in each topic are included in search results.
f law library and technology thought leaders to contribute to her new book “Law Librarianship in the Age of AI” which was released last week by the American Library Association.