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Artificial intelligence closes in on the work of junior lawyers

After more than five years at a leading City law firm, Daniel van Binsbergen quit his job as a solicitor to found Lexoo, a digital start-up for legal services in the fledgling “lawtech” sector.

Many are abandoning traditional firms to pursue entrepreneurial opportunities or join in-house teams, as the once-unthinkable idea of routine corporate legal work as an automated task becomes reality.

But since the 2008 financial crisis, their business model has come under pressure as companies cut spending on legal services, and technology replicated the repetitive tasks that lower-level lawyers at the start of their careers had worked on in the past.

Lexoo does not automate legal work, but it does cut out the traditional law firm by using data and algorithms to match prices from experienced and self-employed lawyers with work for mid-size companies.

In the past, BLP would have pulled together a small team of junior lawyers and paralegals at short notice, then put them in a room to extract that data manually from hundreds of pages — a process that could take weeks.

Slaughter and May, another London firm, uses AI technology from Luminance, a start-up backed by Autonomy founder Mike Lynch to help its mergers and acquisitions lawyers plough through thousands of documents they have to review when analysing target companies in deals.

Luminance’s machine-learning technology means, at a keystroke, lawyers can see all the governing law in clauses within global sales contracts, for example, and identify legal wording thatdiffers from the norm.

“It cuts out work that people find the least interesting and does not cut out analysing the results and looking at importance of transactions and relevant details which client cares about,” she says.

In the US, Lex Machina , a start-up acquired by Lexis Nexis in 2015, crunches data about court rulings to analyse types of cases filed and examine past successes, replacing work that is normally done by newly qualified lawyers.

In the US, law firms using automated software to issue mass debt collection notices without them being reviewed by lawyers have been criticised by the courts because evidence and details have not been properly verified.

A.I. Is Doing Legal Work. But It Won’t Replace Lawyers, Yet.

Kira’s clients report reducing the lawyer time required for contract review by 20 percent to 60 percent, said Noah Waisberg, chief executive of Kira.

Ask for the case most similar to the one you have and the Ross program, which taps some of IBM’s Watson artificial intelligence technology, reads through thousands of cases and delivers a ranked list of the most relevant ones, Mr. Salazar said.

After 10 hours of searching online legal databases, he found a case whose facts nearly mirrored the one he was working on.

My view

Stories about the inevitable and relentless disruption artificial intelligence ('AI') will cause to established industries are commonplace. A recent Financial Times article was entitled: 'Artificial Intelligence closes in on the work of junior lawyers'.  However, before aspiring lawyers start wondering whether their hard-earned skills will soon be redundant in the modern world, it’s worth thinking about the effects that AI has already had on running large-scale disputes.  Disclosure is typically the most expensive phase of large-scale litigation cases. At the appropriate stage of the proceedings, a party to a Court dispute has a duty to carry out a reasonable search for, and then allow the other parties to inspect, documents which support or adversely affect their own or another party's case (i.e.

This is a crucially important task but, as the number of documents potentially relevant to a large dispute could be in the millions and each needs to be manually reviewed by a trainee or junior lawyer, it could be an incredibly time-consuming process.  “Predictive coding is a form of technology assisted review which helps identify relevant documents based on an algorithm, which uses machine learning to suggest the relevance of each document.” However, recently AI – in the form of predictive coding – has been used to ease some of the burden. Predictive coding is a form of technology assisted review which helps identify relevant documents based on an algorithm, which uses machine learning to suggest the relevance of each document.  How it works is that senior team members with extensive case knowledge (typically senior associates) will review a sample set of documents. The algorithm will then promote, to a specified confidence level, the documents it believes are likely to be relevant (e.g.

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