Practice Guide: Keep Calm and CAL On: Key Decisions about Continuous Active Learning
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Prior to becoming an attorney, Xavier worked in the information technology industry for several years in database administration, telecom and VoIP implementation, and software development. As a senior director of Consilio’s Data Analytics group, Xavier oversees projects that involve, Technology-Assisted Review, Immediate Case Assessments™, and analytics research.
Xavier Diokno has a bachelor’s degree in computer science from Southern Illinois University, a master’s degree in computer science from the University of Illinois at Chicago and a juris doctor degree from DePaul University College of Law. He is licensed to practice in the state of Illinois and the United States Patent and Trademark Office. Xavier oversees Consilio’s Data Analytics team, where he advises clients on how to leverage technology in supporting their projects.
Summary
On any new matter, an eDiscovery professional must assess the project’s goals and whether CAL can be leveraged to help achieve those goals. When considering CAL, there are three main decision points: deciding whether to use CAL, deciding how to use CAL, and deciding when your CAL process is complete. This practice guide will review the key factors that must be considered when facing these decision points.
In this Practice Guide
- Deciding whether to use CAL
- Deciding how to use CAL
- Deciding when your CAL process is complete
Key Insights
- The relationship between goals and methods
- The potential of transferable models
- The importance of results validation
Summary
On any new matter, an eDiscovery professional must assess the project’s goals and whether CAL can be leveraged to help achieve those goals. When considering CAL, there are three main decision points: deciding whether to use CAL, deciding how to use CAL, and deciding when your CAL process is complete. This practice guide will review the key factors that must be considered when facing these decision points.
In this Practice Guide
- Deciding whether to use CAL
- Deciding how to use CAL
- Deciding when your CAL process is complete
Key Insights
- The relationship between goals and methods
- The potential of transferable models
- The importance of results validation
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