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78 P E E R T O P E E R : I L T A ' S Q U A R T E R L Y M A G A Z I N E | W I N T E R 2 0 2 1 Dramatic advances in A.I. became achievable as computer processing power increased exponentially over the years. By way of example, ASCI Red – the world's fastest supercomputer of 1996, cost $55M to build, almost filled a tennis court, and ran off enough electrical power to run 800 houses. 5 By 2006, the $500 Sony PlayStation 3 already matched the ASCI Red's processing power, 6 and current iPhones run even faster than that, and fit in your pocket. 7 With today's top supercomputers running almost 56 million times faster than the ASCI Red, 8 processing power is no longer a barrier to A.I. Advances in data storage technology – affording ample storage space for the volume of data necessary for an A.I. system to mirror human problem-solving skills – was the final piece of the puzzle. 9 The first 1GB Hard Drive was introduced by IBM in 1980 at a cost of $44,000. 10 We can now purchase a hard drive with 2000GBs for about $50 on Amazon.com. With sufficient storage now available, we are now seeing dramatic advances in Natural Language Processing (enabling computers to understand, learn from, and communicate in standard prose, rather than via scripts of code), and Machine Learning (computer algorithms that improve automatically through experience), both of which have become key drivers in the successful A.I. applications we are seeing in the legal space today. Artificial Intelligence Applications in Law While media coverage would have readers believe A.I. in legal is a new trend, applications of artificial intelligence, such as Machine Learning (ML) and Natural Language Processing (NLP), have been around for years and are at the core of several legal research platforms. As early as the mid-90s, mainstream legal research platforms were introducing natural language search features. Since then, artificial intelligence applications in legal have expanded to several areas. Artificial Intelligence applications used by law firms tend to fall into several main categories: (1) A.I.-assisted document review, (2) A.I.-assisted case assessment, (3) A.I.- assisted research, (4) A.I.-assisted document generation, and (5) legal automation and robotics. The following are several examples in development or in use at our firm: • Technology Assisted Review (TAR). Artificial intelligence has been used for years by law firms to interpret, analyze, and review e-discovery. TAR systems use A.I. to electronically classify documents based on input from expert reviewers, expediting the organization and prioritization of the document collection. What used to take a team of paralegals and associates hundreds of hours in a room filled with printouts, now can be done in a much more streamlined, more efficient, and more accurate fashion. • A.I.-Assisted Case Assessment. Providing sound case assessments – advising a client what is likely to happen in court given their particular fact pattern and the case law on point – has traditionally been exclusively in the domain of human lawyers. A Toronto-based company called Blue J Legal aims to change that. Blue J Legal recently developed A.I.- powered technology that predicts Canadian labor and employment case outcomes, based on their fact patterns and relevant case precedent, with approximately 90% accuracy. Appreciating the incredible promise of such software, in 2020, Fisher Phillips and Blue J Legal forged a partnership to spend the next few years applying this cutting-edge predictive technology to labor and employment laws F R O M T H E K M C C T

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