Canadian Lawyer

28 A P R I L 2 0 1 7 w w w . C A N A D I A N L a w y e r m a g . c o m "massive step forward" for knowledge management, adds Arruda. That would certainly pique the interest of law firms and legal insurance protection insurers, noted Scott Ferraui- ola, associate general counsel at Watson IBM Corporation, at a conference held last fall in Montreal. Law firms and insur- ers are drawn to the possibility of being able to harness the power of AI to identify, capture, evaluate, retrieve and share all of an organization's information assets, says Ferrauiola. "Who are your experts on certain legal issues? Do they have memos or briefs? Where are they? Can we access them? Can we search them? It's almost a back-office function. It's not quite decision-making, but it helps in decision-making," adds Ferrauiola. Using machine learning to predict legal outcomes is another area that may sway lawyers to explore the potential of AI, according to experts. Last year, the lord chief justice of England and Wales warned jurists that AI will be better at predicting the outcome of cases than the "most learned Queen's Counsel" as soon as it has better statistical informa- tion. That day may have come. In a breakthrough develop- ment, computer scientists last fall using AI reached the same verdicts as judges at the European Court of Human Rights in nearly four out of five cases involving torture, degrading treatment and privacy, marking the first time that AI success- fully predicted the outcomes of a major international court by analyzing case text. "This can be useful, for both lawyers and judges, as an assisting tool to rapidly identify cases and extract patterns which lead to certain decisions," noted the authors of the study. Blue J Legal is another player in this area. The Canadian legal tech startup boasts that its AI simulation product, Tax Foresight, a joint initiative with Thomson Reuters (pub- lisher of Canadian Lawyer), is able to predict with greater than 90-per-cent accuracy what a court would hold in new circumstances. The tool has the additional allure of being simple to use: The machine learning tool asks questions These are tools that allow people to perform some elements of their jobs better, and these algorithms can do a better job in certain things. It's a very powerful complement to human judgment. BENJAMIN ALARIE, BLUE J LEGAL Canada: a hub for AI W hen AlphaGO, Google's artificial intelligence system, defeated the 18-time world champion in the complex and highly intuitively game of the ancient Chinese board game GO, it was not just a demonstration of yet another computer beating a human at a game. GO, a game with simple rules but profound complexity, has more possible positions than there are atoms in the universe, leading some to describe it as the Holy Grail of AI gaming. It was a remarkable feat because AlphaGo was not taught how to play Go. It learned how to play, and win, by play- ing millions of games, using a form of AI called deep learning, which utilizes neural networks that allow computer programs to learn just like humans. More than that, the victory showed that a computer is now able to rely on its own intuition, something that was thought only humans could do. AlphaGO was developed by a group of computing scientists led by University of Alberta grads, underscoring Canada's enviable position as a world leader in AI. The Montreal Institute for Learning Algo- rithms, the University of Toronto and the University of Alberta are all recognized as pioneers in deep learning. Over the past couple of years, Canada has been cementing its status as an AI hub with the likes of Google flocking to Montreal, the Royal Bank of Canada establishing its machine learning division as part of an initial partnership with the Uni- versity of Toronto and with Thomson Reuters founding a research lab in the Waterloo region and a technology centre for cognitive computing in Toronto. All of this has touched off an arms race for AI talent, and particularly Canadian machine learning researchers. "There's a lot of poaching of professors that is going on," remarks Aaron Courville, an AI professor with the Montreal Institute for Learning Algorithms. "It's a big problem. It's like you are biting the hand that feeds you in some ways. You are taking professors out and who's going to train the next genera- tion of people with this expertise." On the other hand, the rapid pace of developments in AI will almost certainly lead to greater collaboration between publicly funded and private research organizations, creating a win-win situation for all researchers, says Khalid Al-Kofahi, vice-president of R&D at the Thom- son Reuters Centre for Cognitive Computing. "The rate of change that is now occurring in technology, especially around machine learning and artificial intelligence, significantly exceeds our ability to learn," says Al- Kofahi. "We don't have to collaborate at the application level, but we can collaborate on problems that are pre-application stage." In the meantime, the Canadian AI scene has spawned a lot of activ- ity such as pioneering legal tech startups such as ROSS Intelligence, Blue J Legal and Beagle, as well as innovative AI offerings. Thomson Reuters' Waterloo lab, which uses data science to look for new insights or analy- sis in order to solve customer problems, recently developed, in the space of three months, an AI tool that helps employers determine settlement offers in the case of employee termination. The AI product is a "research tool for legal professionals, not a calculator that does the job of a human — and that's the way that the legal profession should view artificial intel- ligence in the first place," says Brian Zubert, the director of the lab.

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