Extract from Venio Systems’s article “Artificial Intelligence & eDiscovery: What You Need To Know”
The Secret Weapon for eDiscovery Success You Need to Know
Artificial intelligence has been at the forefront of eDiscovery software development, automating processes and simplifying solutions, all to go above and beyond the clients’ changing needs.
Customers are able to optimize their cases and investigations through maximizing efficiency and productivity and minimizing security risks and costs with the different types of AI being used in eDiscovery.
Supervised vs Unsupervised Learning
The most common use of AI in eDiscovery can be categorized into two main subfields: supervised and unsupervised learning during early case assessment (ECA) and the review processes.
Supervised Learning
Supervised learning requires software to be trained by a human through rounds and rounds of sample data sets to identify important documents. Once the software recognizes the patterns, it is able to continue the review process autonomously.
This technology is often referred to as TAR, or technology assisted review and has been integral to cutting down the time spent on ECA and review.
