In eDiscovery, discussions about «artificial intelligence» generally focus on predictive coding — the machine learning process that reduces
the time human reviewers must spend reading non-relevant information — by teaching the software to analyse periodic human feedback, learn for itself what information reviewers are actually interested in, and then locate that information.
Not exact matches
You can't make everyone happy all the
time, but if a
reviewer complains of never being able to reach a
human being when calling the front office, make changes to your customer service practices.
That means firms can get more done in less
time with fewer
human reviewers.
Machine learning tools will assist trained
human reviewers who, Facebook says, block millions of fake accounts at the
time of registration...
When a
human reviewer actually «reads» your resume for the first
time, you have roughly 10 seconds to make your case.
On the other hand, having too much information may give the ATS more opportunities to find keyword matches, but then it comes back to hurt you when the
human reviewer has a hard
time digesting the numerous pages of information.