Tag Archives: artificial intelligence

Legal IT

AI and Contracts

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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 LawGeex.com, 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 Legalese.com 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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Legal IT

Artificial Intelligence and Law

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Legal Artificial Intelligence has made the news’ headlines often, recently. There are chat bots, e.g., that help you appeal against a parking ticket (www.donotpay.co.uk), or give you a first advice if you are considering a divorce (divorce bot). There is software that predicts the likely outcome of court cases. IBM offers legal AI services for eDiscovery and legal research with its Watson supercomputer: Ross, as the service is called, uses Natural Language Processing, and can also be used for cognitive computing, e.g., to review contracts (www.rossintelligence.com). Then there is RPA (Robotics Process Automation) who are creating software robots for law firms. The idea is that any repetitive task that lawyers and paralegals do at a computer can be performed by a software robot. These are two examples of AI doing the work that is often done by paralegals and lawyers.

So, what is the current state of affairs? What is being used and developed within law firms, and what do service providers have to offer when it comes to artificial intelligence for lawyers? Basically, there are three main pillars, where AI is currently being used:

  • Research and Data Analysis: Legal Research, eDiscovery, triage services for those two, predictive systems, other analytics (statistics, correlations, etc.),
  • Cognitive systems: expert systems, contract review
  • Task automation: bots (advice, automate repetitive tasks)

Let us explore these a bit further.

Legal Research: Looking for legal information that is relevant to a case you’re handling? Legal databases are increasingly using AI to present you with the relevant laws, statutes, case law, etc.

eDiscovery: While legal research deals with legal information, eDiscovery focuses on finding evidence that is stored in a digital format. More and more evidence is stored electronically, on computers, smart phones, but also in the cloud (think, e.g., of social media). The task of finding evidence that is pertinent to a case more and more becomes like looking for a needle in a haystack. No wonder that AI is increasingly being used to assist in eDiscovery.

Triage services: So, you have used programs for legal research and eDiscovery. Often that is just the first round, i.e. finding relevant information. If you’re confronted with thousands of results, you need a second round, which is the triage: determining what is most relevant and sorting the results accordingly. Triage services are often built into the software you are using, but are also being offered by independent third party service providers.

Predictive systems: A previous article was dedicated to a software system that could accurately predict the outcome of court cases dealing with Human Rights. It was right in 79% of the cases. Several service providers have announced similar products for other areas of law. But predictive systems are not limited to case outcome predictions. US data scientists have, e.g., developed a new algorithmic analysis they believe could help judges reduce crime by up to 25% in certain situations. The software performs a risk assessment and advises a judge whether a defendant awaiting their court date for an alleged crime should or should not be released to go home before the trial starts.

Other analytics: Machine learning and data mining is also used to provide us with (other) statistics, relevant correlations, etc.

Expert systems: The first cognitive systems already were developed in the 90s. Expert systems are intelligent checklists that have the built-in ability to reason, i.e., perform logical operations and functions.

Contract review: One area where cognitive systems are shining at present is contract review. Important, e.g., is the ability to point out clauses that are lacking in a contract.

Task automation: Bots are intelligent software robots that are created to automate specific tasks. In the introduction of this article, we gave the examples of chat bots that can give advice, and other bots that are being designed to perform any task a lawyer or paralegal does repetitively on a computer.

What does this all mean for lawyers? Richard Tromans, at www.artificiallawyer.com, sums it up perfectly:  ” … the arrival of AI marks a Renaissance for the legal industry because it permits lawyers to be real lawyers again and not tired process units counting down the hours of their day. After all, isn’t the definition of a lawyer a person who is doing something special in society, i.e. taking on a client’s problems and making it their duty to help them? Isn’t that why membership of the profession is so jealously guarded and so heavily regulated? If this is just any other office job, then why all the fuss to become a lawyer? But of course, it’s not just any other office job. In which case, maybe AI is the best thing that has happened to lawyers in many decades.”

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Legal IT

Legal Technology Trends for 2017

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It is common, at the beginning of the year, to ponder upon what the year ahead will bring. Several experts have published their predictions for trends we can expect in legal technology, in 2017. So, what are they saying? Generally speaking, they expect lawyers to become more mobile, more collaborative (using the cloud do to do), and more responsive (using social media to engage with clients and potential clients). 2017 is also expected to see a rise in the usage of AI (Artificial Intelligence), and to be the year that E-Discovery goes mainstream. Cybercrime & Cyberwarfare, too, will remain in the news.

Let’s have a closer look at these items.

More Mobile

In 2016, for the first time worldwide, we saw more mobile devices being used online than desktops. This trend is expected to continue. More lawyers will start using mobile apps. They also will start accommodating their mobile clients – and potential clients – more. (We recently published two articles on the subject, where you can find more information).

Cloud

2017 will see a further increase in cloud usage. The could will play an increasingly important role in collaboration between lawyers. Bigger law firms are expected to start using big data analytics. The cloud will also play a significant role in the further development of AI and E-Discovery (see below).

Cybersecurity

Cybercrime will continue to rise, and will continue to become more and more sophisticated. AI will increasingly be used in cyber-protection, as well as in attacks. Experts also expect an increase in cyberwarfare.

Social Media – Business Social

More lawyers will start embracing social media, and as a result they will become more responsive, i.e. engage more with clients and potential clients. More specifically, for lawyers, an increase is expected in the usage of professional or business social media. Some experts foresee an important role for new players (service providers) on this market.

AI

In 2017, AI will continue its rise, and become more omnipresent. The main focus of artificial intelligence in legal tech will remain on Machine Learning. More specifically, AI will continue to push legal technology in the fields of Legal Research (with, e.g., virtual Legal Research assistants), Contract Review, Security, and E-Discovery (see further). One expert also expects AI to be introduced in legal practice management, as well as legal project management, which, in turn could lead to significant advances being made in those fields.

E-Discovery

Last, but not least, 2017 is the year E-discovery is expected to go mainstream. E-Discovery, also spelled eDiscovery, stands for electronic discovery. It refers to the discovery of relevant information in legal proceedings – such as litigation, government investigations, or Freedom of Information Act requests – where the information that is being analyzed is stored in an electronic format. Think, e.g., about the recent example of the FBI analyzing tens of thousands of emails that were leaked by WikiLeaks, in just four days. As more and more information is being stored electronically, E-Discovery is becoming more and more important. In 2017, it is expected to go mainstream.

Experts predict the following trends for E-Discovery in 2017:

  • The increase in social media usage implies that E-Discovery will have to be able to incorporate the analysis of social media information as well.
  • The Internet of Things will also have a serious impact on E-Discovery, as it will have to learn to process the data that are produced by billions of devices. In the US, e.g., there is a murder case where Amazon is asked to give access to the data one of its digital Echo devices (virtual assistants) may have recorded as evidence.
  • Because of these two developments (social media & Internet of Things), data privacy is becoming more important than ever.
  • Machine Learning is expected to become the most important technology for E-Discovery.
  • Cross-border compliance will continue shaping E-Discovery: multinationals, e.g., must comply with laws in several countries. This has implications on what can be stored where, which in turn has its effects on E-Discovery.

 

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Legal IT

AI Predicts Outcome of Human Rights Cases

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It’s the stuff of science fiction: an artificial intelligence judges the merits of a court case and reaches a verdict. We are now one step closer to that being a reality. Researchers have created an artificial intelligence system that has accurately predicted the outcomes of many cases heard at the European Court of Human Rights (ECHR). Out of 584 cases, the system had a success rate of 79% where it correctly decided whether there had been a Human Rights’ violation or not.

The project was carried out by researchers at University College London and the universities of Sheffield and Pennsylvania. The method consisted of automatically analyzing case text using a machine learning algorithm. For the learning phase, equal amounts of cases with violations and without violations were used. In developing the method, the team found that judgements by the ECHR are highly correlated to non-legal facts rather than directly legal arguments, suggesting that judges of the Court are, in the jargon of legal theory, ‘realists’ rather than ‘formalists’.

The most reliable factors for predicting the court’s decision were found to be the language used, as well as the topics and ‘circumstances’ mentioned in the case text. The ‘circumstances’ section of the text includes information about the factual background to the case.

The team identified English language data sets for 584 cases related to three articles of the Convention on Human Rights:

  • Article 3: cases involving torture or degrading treatment, good for 250 cases
  • Article 6: rights to a fair trial, good for 80 cases
  • Article 8: respect for private life, good for 254 cases

By combining the information extracted from a) the abstract ‘topics’ that the cases cover and b) the ‘circumstances’ across data for all three articles, an accuracy of 79% was achieved.

The 21% of cases where the prediction was not correct involved situations where there were similar cases but with different outcomes. This could be an indication that in those cases, the finer subtleties of the law were missed by the artificial intelligence.

One of the key researchers, Dr Nikolaos Aletras, who led the study at UCL, said the following about using AI to predict cases: ‘We don’t see AI replacing judges or lawyers, but we think they’d find it useful for rapidly identifying patterns in cases that lead to certain outcomes. It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights.’

Given the huge numbers of cases that the ECHR’s legal staff has to consider every year, the program could indeed prove very useful: in 2015, e.g., the court had to process 40,650 applications for a hearing, while in 2014 it processed 56,200 cases.

It is easy to see how such programs could benefit law firms as well. Having intelligent software at your office to predict the outcome of a case would offer a clear and objective view of the strengths and weaknesses of your case and argumentation. This could then help devise a different argumentation if necessary. Alternatively, it could help avoiding the costs of litigation if similar cases were not considered ‘winnable’.

Does this mean lawyers or judges should start fearing for their jobs? No, it doesn’t. The program still misses the finer subtleties of the law. As Dr Aletras pointed out, it is meant as a tool to assist, not to replace. In the long run, though, it could result in lawyers and judges dealing with more complex or specialized cases, while the processing of simpler cases gets more automated.

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Legal IT

The bots are coming

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In last week’s article, we mentioned the rise of virtual offices and websites that offer legal services. One of those, www.donotpay.co.uk, has drawn a lot of attention, recently. The website is the brain child of nineteen-year-old Joshua Browder, who refers to it as the world’s first robot lawyer. He created the website after he received more than thirty unfair traffic fines in London in just a few months, and wanted to appeal them. The website is designed to make that process as easy as answering a few questions, either by filling out a form, or in a chatroom. The website then files the appeal on your behalf, for free.

That Browder chose a chatroom solution that uses a chat bot shouldn’t come as a surprise. Indeed, experts have been predicting that the use of chat bots to interact with customers would constitute one of the biggest new technology shifts. After all, chatting apps are extremely popular, and offer users a familiar interface. Chances are you’ve already used a chat room to interact with IT support services or with companies’ customer services. The natural next step was that chat bots would get involved to automate and streamline the process. Tests have shown that the artificial intelligence used in chat bots has sufficiently matured to pass the Turing Test, i.e., the person interacting with the chat bot does not realise he or she is interacting with a chat bot. In the US, e.g., chat bots are already being used successfully in fast food chains to process online orders. Or you can just call an Uber through Facebook Messenger. Chat bots can also get you news headlines, weather forecasts, or traffic information. IT companies like Slack.com, e.g., already use a chat bot (called slackbot) for their online customer support. Microsoft acknowledged the potential of chat bots when it started working in March on tools that allow you to create your own chat bot on Skype.

With DoNotPay, the first legal chat bot is now a fact, too. When the website started offering Londoners an easy way to appeal unfair traffic fines for free, it did so with huge success: in less than two years’ time, 250 000 appeals were submitted and 160 000 of those were successful. As a result, approximately four million USD worth in parking tickets did not have to be paid. By now, people in New York can use the service as well. Seattle is next, and South Africa may follow as well. And that’s not all. Given its success, the website intends to extend the services it offers. Apart from appealing parking tickets, the website can now also assist you in claiming compensation if your flight was delayed.

In an interview with Fortune Magazine Catherine Bamford, a former lawyer in Leeds who advises law firms and corporate legal departments on automation, underlined how important this evolution is. “Access to justice for the non-wealthy is a serious concern. Legal aid budgets have been slashed in recent years. With helper bots like DoNotPay, some willing lawyers and expert programmers, legal advice could become cheap and accessible to everyone via the Internet. This is a real step in the right direction.”

The DoNotPay website wasn’t Joshua Browder’s first endeavour. The second-year IT student at Stanford, indeed has a nice track record already. As a thirteen-year-old he created an app for ‘Pret-a-manger,’ a sandwich chain, that became so popular that the company adopted it as its official app. He also contacted several human rights organizations offering his services for free. Some, like Freedom House (a human rights watchdog) and International Bridges for Justice accepted his offer.

We are likely to encounter more and more intelligent chat bots in the near future. And they won’t be limited to just support departments or customer services. One startup, x.ai, is already working on a virtual personal assistant, and uses the built-in chat bot to interact with people, e.g., to set up appointments, suggesting possible times, etc. It’s probably just a matter of time before law firms start using virtual legal assistants. In fact, IBM already offers a virtual legal research assistant. And that’s just the beginning. We can expect artificial intelligence aspects to be integrated in the user interfaces of legal software, replacing the more traditional wizards. And Law still is a field that deals with a lot of formalities. Robot lawyers that assist people with those, e.g., could be really useful, and could make things more transparent and accessible.

So, should lawyers be worried that legal robots will be taking over their jobs? Not really! After all, with each new technology arise new opportunities for lawyers, too. Take, e.g., liability questions: what if the robot lawyer makes a mistake, or if your virtual legal assistant sends out the wrong information? As long as there are legal conflicts, the need for lawyers will remain. (And that’s a good thing, because otherwise we would be out of job, too).

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