Technology-assisted review (TAR), also known as predictive coding and computer-assisted review, has become a frequently used tool to complete large document reviews quickly and cost efficiently. The promise of fast, accurate computer-assisted coding as a practical solution to increasingly massive collections is encouraging, but understanding various vendor approaches can be confusing and overwhelming. In many cases, there is little, if any, information about how a specific TAR methodology works, creating potential defensibility blind spots and jeopardizing the progress of your case. How can you trust or account for the results of a mystery process? Alternatively, if a methodology is fully disclosed, case teams can evaluate, explain, and justify outcomes with confidence.
- What is Technology-Assisted Review (TAR)?
- How does TAR/Predictive Coding work?
- Why use TAR/Predictive Coding?
- Comparing outcomes: predictive coding vs.and manual review
- Importance of transparency in TAR applications
- Benefits of scalability in predictive coding architectures
About the Speaker
Karsten Weber is CTO and Principal, Lexbe LC. Mr. Weber is an eDiscovery consultant and expert and leads the product development at Lexbe. He holds an MBA from the University of Texas and an M.S. Engineering, Danish Technical University.