K&L Gates participated in this week’s 2023 Legalweek in New York City.  As members of our firm’s e-Discovery Analysis & Technology (“e-DAT”) Group attended panel discussions regarding emerging legal issues and met with vendors regarding evolving legal technologies, they noted three trends that were being discussed by everyone at the conference.

1)    Generative Artificial Intelligence Tools

Generative artificial intelligence (“AI”), including the technology at the heart of the new versions of OpenAI’s ChatGPT technology, has captured the imagination of the broader public and the keen interest of legal technologists.  Tools employing generative AI have been in use for a while, with such tools include the sophisticated machine language translation tools available in many document review platforms.  With generative AI receiving increased focus throughout the legal community, we will undoubtedly see new integrations of this technology within basic office productivity software and the search, analysis, and review tools used in electronic discovery.

2)    Machine Learning Models Built Through Artificial Intelligence

Artificial intelligence and advanced analytical tools are often used to generate bespoke machine learning models that are fashioned in light of the particular data sets involved in a particular case’s electronic discovery.  Many e-discovery practitioners are expanding how they use such machine learning models across cases share similar conceptual components, such as specific subject matters, privilege considerations, or broad categorizations regarding content that can be consistently excluded.

3)    Application of Linguistic and Emotional Intelligence

Data modeling is becoming increasingly adept at uncovering relationships between people, things, places, and/or times that might otherwise remain unnoticed.  This trend is particularly true with regard to multi-modal communications, as data that originates from many different forms of communication can pose unique issues when working to understand their connections and associations.  Also, e-discovery practitioners are finding additional value in using sentiment analyses to identify the tone used by authors of collected documents and to determine ways in which the positive and negative sentiments associated with these documents can be used to find potential key documents among the broader collections.