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AI and Contracts

Artificial Intelligence (AI) is changing the way law is being practiced. One of the areas where AI, and more specifically Machine Learning (ML) has been making great strides recently is contract review. The progress is not even limited to reviewing contracts: automated contract generation, negotiation, e-signing and management are fast becoming a reality.

Using AI for contracts is the result of an ongoing evolution. Ever since lawyers started using word processors, they have tried to automate the process of creating contracts. Using advanced macros allowed them to turn word processors into act generators that used smart checklists to fill out templates and add or remove certain clauses. But now the available technology is sufficiently advanced to take it all a few steps further.

Some years ago, commercial lawyer Noory Bechor came to the realization that 80 percent of his work was spent reviewing contracts. As a lot of the work involved in reviewing contracts is fairly repetitive in nature, he figured the service could be done much cheaper, faster, and more accurately if it was done by a computer. So, in 2014, he started LawGeex, which probably was the first platform for automatized contract review. Users can upload a contract to, and, within a reasonably short period of time (an hour on average), they receive a report that states which clauses do not meet common legal standards. The report also warns if any vital clauses could be missing, and where existing clauses might require further attention. All of this is done automatically, by algorithms.

By now, there are other players on the contract review market as well, and the technology is evolving further. At present, AI technology is able to scan contracts and decipher meaning behind the text, as well as identify problem areas that might require human intervention. This technology can scan millions of documents in a fraction of the time it would take humans (think ‘hours’ as opposed to ‘days’ or ‘weeks’). As a result, AI contract review has reached a point where it can already do 80% of the work a lawyer used to do. For the remaining 20%, it can, at present, not reach the level of skill and comprehension of a human attorney. AI contract review, therefore, focuses attorneys’ efforts on higher-level, nonstandard clauses and concerns, and away from more manual contract review obligations.

The progress made in Machine Learning algorithms means the usage of AI is not limited to contract review. Juro is a company that tries to automate the whole contracts workflow. It has developed an integrated workflow system that allows companies to save time on contracts through automated contract generation, negotiation, e-signing and management of contracts. For this, it relies on machine learning algorithms that try to understand the data within contracts and learn from it. This can be done, e.g., by analyzing all the contracts in a company’s ‘vault’ of historical contracts. Based on these contract analytics, Juro can also provide so-called ‘negotiation heatmaps,’ where customers can see at a glance which of their contract terms are being most hotly negotiated. Knowing what other customers have negotiated can help you (based on data) decide what the contract terms should be and what you should agree to in negotiations.

Another interesting evolution is the idea of ‘smart contracts’. Stephen Wolfram, the founder of Wolfram Alpha, believes contracts should be computable, and that a hybrid code/legalese language should be developed. One of the main advantages of such language would be that it would leave less room for ambiguity, especially when it comes to the implications of certain clauses. Computable contract language becomes more valuable to the legal sector, once we start using ‘smart contracts’ that are self-executing. There is also already some interesting work in this area, namely by based in Singapore. If law is going to be made computable then the world needs two things: lawyers who can code and a legal computer language that is an improvement on today’s legalese.

The next step would then be to move from ‘smart’ contracts to ‘intelligent’ contracts. Smart Contracts resemble computer code more than typical legal documents, relying on programing to create, facilitate, or execute contracts, with the contracts and conditions stored on a blockchain, or a distributed, relatively unhackable ledger. Intelligent contracts would not just be smart, but also rely on artificial intelligence (hence ‘intelligent’ contracts). In the words of Kevin Gidney, intelligent contracts would use an AI system that “is taught to continually and consistently recognize and extract key information from contracts, with active learning based on users’ responses, both positive and negative, to the extractions and predictions made”.



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