The Lexpert Special Editions profiles selected Lexpert-ranked lawyers whose focus is in Corporate, Infrastructure, Energy and Litigation law and relevant practices. It also includes feature articles on legal aspects of Canadian business issues.
Issue link: https://digital.carswellmedia.com/i/1470136
8 www.lexpert.ca Feature WHERE HEALTH CARE MEETS ARTIFICIAL INTELLIGENCE AS THE commercialization of artificial intelligence and machine learning grows, the next frontier for its use will be in the world of health care. is use will potentially change health outcomes for the better – and brings questions surrounding privacy and data use to the forefront. "We've been seeing the crossover between information technology companies and health-care-related companies applying AI and machine learning to solve health-care- related problems," says Chad Bayne, partner with Osler, Hoskin & Harcourt LLP in its emerging and high-growth companies prac- tice. ese crossover matters can range from medical devices to therapeutics to patient management and triage. Bayne notes that Canada "punches above its weight" in AI and machine-learning science in centres of excellence, including Toronto, Montreal, Kitchener-Waterloo, and the University of Alberta. ese, in turn, have helped create companies focused on the intersection of information technology and AI, whether it is to improve drug discovery, develop a screening system that can predict which patients will need treatment, or find out what to do to avoid the need for treat- ment at all. ADVANCES IN AI AND MACHINE LEARNING COULD LEAD TO BETTER, MORE EFFICIENT HEALTH CARE. BUT THE ROAD TO GETTING THERE IS NOT WITHOUT RISK, WRITES ZENA OLIJNYK Artificial intelligence combines computer science with data to enable machines to mimic human intelligence when solving problems. Machine learning is a sub-field of artificial intelligence in which algorithms help processes or devices achieve learning through experience and new data. ese algorithms can be "locked," so their function does not change, or "adaptive," meaning their behaviour can change over time. AI oen conjures images of independent, "thinking" robots. However, its actual uses are far more practical, whether it is handling routine and repetitive administrative tasks, such as triaging resources, or used for more complex purposes like detecting a potential medical condition in a patient's electronic medical record. "Properly harnessing AI technology will have huge ramifications for improving our health care system, making it more efficient," says Danielle Miller Olofsson, a senior asso- ciate with the corporate law group at Stikeman Elliott LLP's Montreal office. "We as a society are starting to realize that as we're aging, the health care system may become overburdened," she says. "So we need solutions that are as much about preventing disease as managing it when it happens." ere are many examples of Canadian hospitals and health care organizations using AI to improve efficiencies and outcomes for better patient care in a clinical setting. ese include: • looking at administrative applications, such as using AI to manage hospital resourc- es better (one example would be aligning schedules to match patient traffic) • clinical applications for improving patient care and outcomes • detection and diagnosis, to improve their speed and accuracy • research and development in areas like drug discovery and medical devices While the potential for using AI in health care is vast, Miller Olofsson says it is a "deli- cate balance" of private- and public-sector players coming together for the greater good. She points out that "these are extremely chal- lenging issues that are also very political," depending on the regulatory landscape. For example, on one end, there is the European Union, which Miller Olafsson describes as having a very "human-centred" approach to AI and its commercial use. On the other end, jurisdictions like China embrace the potential of this technology at the expense of the impact on privacy and human rights. North America, including Canada, has taken more of a wait-and-see approach to using AI and its challenges in potentially sensi- tive sectors like health care. One consideration that Canadians might want to think about, she adds, is that, given we have a public, universal health care system, is there an argument that we are more permissive in sharing data for AI purposes? "Is integration into a larger network breaking down our traditional perception of what is private and what is public?" Of course, transparency and privacy concerns are significant, she notes, but if the information from our public health care system benefits everyone, is it inefficient to ask for consent for every use? On the other hand, cybersecurity is another essential consideration, as "we've come to learn