This AI checks NDAs for free
NDA Lynn, an AI that can evaluate confidentiality agreements for free, is a perfect example of the role artificial intelligence will probably play in our life.
For the past decade or so, Arnoud Engelfriet has been the Netherland’s go-to guy for any question regarding internet and the law. Also his last name translates roughly to ‘Angelic Fries,’ which is awesome.
One of the services Engelfriet offered was checking NDAs if they should be signed. Non-disclosure agreements (NDAs) are pretty standard business contracts used to keep confidential information under wraps. They are quite common, but do require some scrutiny to establish what exactly establishes a breach and that they don’t gag one forever.
“A businessman who needs his NDAs checked, but doesn’t have the budget to have them all checked, only needs to know which one really needs to looked at by a professional,” he tells me
“And if something is too expensive to do manually, but people need it a lot, it’s a good candidate for automation,” he concludes.
Checking NDAs pretty standard work, but nonetheless time-consuming. So he put his computer science degree to good use and started building an AI that could help him out.
“Way back in 1993 I studied computer sciences at university. Back then there was no machine learning, or at least not in this way. For this project I used BigML, a cloud solution for machine learning that aims at making it more accessible to the masses.”
All Engelfriet needed was a good dataset, which he happened to have as a lawyer. “To start out with, I uploaded 300 NDAs from my archive, and labeled them by hand,” he tells me.
The dataset consisted of about 10,000 sentences, and to train the AI, each of those had to be marked if they contained something untoward for an NDA.
“I put all that in the system, and that produced an AI. All it needed afterwards was a nice wrapper.”
Engelfriet is very realistic about how revolutionary NDA Lynn is. “It’s not very innovative, but that’s exactly what makes it powerful. AI has become a commodity.”
NDALynn itself is a machine learning system that has been trained to identify clauses in NDAs that don’t seem right. It then returns a clause-by-clause report on which ones seem fine, and which ones seem to require too much or are unclear.
It sounds trivial, but reviewing NDAs requires a significant amount of work. “Drafting or reviewing a non-disclosure agreement is an art and therefore requires significant amounts of work to get right.”
At the moment NDA Lynn achieves an accuracy of 94,8 percent in the latest tests, which is remarkably high. A study published this week by LawGeex, a competing NDA AI, pitted lawyers against their system to check NDAs, with lawyers scoring a paltry 85 percent accuracy on average.
I tried out a few NDAs collected from colleagues, and most of them did contain some fishy clauses, which the system labels as ‘dealbreakers.’ But that doesn’t necessarily mean they’re not ok, Engelfriet admits.
“Imagine a reporter, for a story they look for sources, reach out to a few of them. You could train an AI to do that. But every reporter has certain biases.
