The advent of generative artificial intelligence systems such as ChatGPT has stirred the legal industry, posing novel questions about their potential implications in the sector. Among these, the impact of these AI systems on document review services stands as a salient issue awaiting serious deliberation.
Courts regularly subject parties that use technology-assisted review to stricter scrutiny than those conducting linear, manual document reviews. It is, therefore, prudent for parties using large language models for document review to brace themselves for increased attention, as well as a surging need for quality control and validation, according to the attorneys at Sidley.
Document review, while an integral cog in the legal process, can be a draining task, with professionals often having to comb through piles of verbose documents to extract meaningful and relevant information. The deployment of tech-assisted solutions such as large language models can facilitate this process and improve its efficiency. But, as is the case with most technological advancements, it does not come without its set of caveats.
Quality control and validation become paramount when relying on such tech-assisted tools. Since these models inherently lack human discernment, they might gloss over the intricate nuances of legal language often laden with legalese, or even omit certain context-dependent interpretations. Consequently, the need for diligent oversight and systematic validation over the outputs of these models becomes crucial to ensure accuracy and avoid any potentially damaging consequences.
Law firms and legal departments intending to leverage significant language models for document review services need to understand these challenges and equip themselves with the necessary mechanisms to surpass them.
The broader implications of this matter are detailed in an article by Daniel Kelly, Colleen Kenney, and Matt Jackson for Law360.