Using Gen AI in Document Review: A Brave New World
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Matthew Verga is an attorney, consultant, and eDiscovery expert proficient at leveraging his legal experience, his technical knowledge, and his communication skills to make complex eDiscovery topics accessible to diverse audiences. A fifteen-year industry veteran, Matthew has worked across every phase of the EDRM and at every level, from the project trenches to enterprise program design. As Director of Education for Consilio, he leverages this background to produce engaging educational content to empower practitioners at all levels with knowledge they can use to improve their projects, their careers, and their organizations.
Summary
Generative AI (Gen AI) has dominated discourse in the legal industry for more than a year, and we’re now witnessing the promise of Gen AI starting to be made real in in a variety of contexts, including legal document review. Document review has long been the most expensive and time-consuming phase of a discovery project, and legal technology has been in a kind of arms race with document creation and communication technologies for the past two decades. Gen AI represents the latest advancement in this ongoing struggle, but it also represents a source of uncertainty and new technological complexity.
In simple terms, Gen AI is a type of artificial intelligence that can generate new content, like text, based on prompts from a user. Gen AI tools do this by first training on large data sets to learn patterns and features. Large language models (LLMs), for example, are trained on large collections of text documents to learn linguistic patterns and features. Such models are very good at reviewing a given block of text and answering questions about it, which makes them powerful tools to aid in legal document review.
In this Whitepaper
- Viable use cases
- Old and new benefits
- Validation methods
Key Insights
- The need for iteration and testing
- The importance of relevant expertise
- The value of knowing not just what but why
Summary
Generative AI (Gen AI) has dominated discourse in the legal industry for more than a year, and we’re now witnessing the promise of Gen AI starting to be made real in in a variety of contexts, including legal document review. Document review has long been the most expensive and time-consuming phase of a discovery project, and legal technology has been in a kind of arms race with document creation and communication technologies for the past two decades. Gen AI represents the latest advancement in this ongoing struggle, but it also represents a source of uncertainty and new technological complexity.
In simple terms, Gen AI is a type of artificial intelligence that can generate new content, like text, based on prompts from a user. Gen AI tools do this by first training on large data sets to learn patterns and features. Large language models (LLMs), for example, are trained on large collections of text documents to learn linguistic patterns and features. Such models are very good at reviewing a given block of text and answering questions about it, which makes them powerful tools to aid in legal document review.
In this Whitepaper
- Viable use cases
- Old and new benefits
- Validation methods
Key Insights
- The need for iteration and testing
- The importance of relevant expertise
- The value of knowing not just what but why
