It’s been over four years since Da Silva Moore energized the legal tech industry, bringing predictive coding into the wider legal lexicon. Also known as technology-assisted review (TAR), predictive coding leverages machine learning to apply human relevancy decisions to documents across a dataset, ranking them according to likely relevance. Yet despite growing awareness and adoption, myths and misconceptions continue to propagate.
The amended FRCP and new ethical obligations to understand technology create a near-mandate for attorneys to appraise the benefits and risks of predictive coding. This session will provide an in-depth study of predictive coding from legal theory and case law analysis to practical implementation and unconventional use cases.
Since Da Silva Moore there have been almost 40 opinions that further discuss predictive coding issues that will be covered in this session, including:
- Defensible workflows
- TAR 1.0 vs TAR 2.0
- Transparency obligations
- Cooperation guidelines
- Combining analytics
- Negotiating protocols
- Proportionality principles
Session attendees will walk away with comprehensive case law guides and practical implementation tips from meet & confer tactics to vendor dialogue.