As a licensed attorney, Andrew Arruda has experienced first-hand the many hours of menial research that go into preparing a case, which can drain a law firm’s resources and inflate fees for clients. But Arruda decided to do something about it. He joined a group of computer science students from the University of Toronto to create Ross, a digital legal expert that helps lawyers power through research.
Instead of wasting time sifting through mounds of documents, lawyers can ask Ross, a desktop app, questions in plain English. The program then combs through the entire body of U.S. case law (the team plans to incorporate other countries later) and returns relevant legislation, judgments and other useful information in response. Arruda, who left his job in June to serve as CEO of Ross, says the digital assistant shortens the research time for each case, allowing lawyers to take on more challenging files and preventing client fees from escalating.
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Ross is part of a wave of artificial intelligence (AI) technologies handling increasingly complex tasks once performed by white-collar workers. Many of these technologies are built on top of Watson, the supercomputer designed by IBM that trounced contestants on Jeopardy a few years ago. Watson leverages deep learning, a branch of artificial intelligence that essentially trains computers to learn from raw data.
A wide swath of industries is already taking advantage. Wall Street hedge funds are using a cheap supercomputer called Ufora to analyze extremely large sets of market data and working with a separate technology to write analyst reports once produced by humans. Oncologists are using AI to diagnose diseases, and even the travel industry is finding applications. Texas-based startup WayBlazer, combs through search engine queries to deliver personalized travel insights and special offers to customers. With the growth of AI’s potential, businesses need to start thinking about how to automate more tasks using these new technologies in order to stay competitive.
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Ross has already generated a lot of interest from potential investors and law firms looking to implement the digital helper. “Law is a huge market,” Arruda says. Big law firms are obvious candidates for the technology, but so are in-house lawyers working for large corporations and governments. Despite the benefits services like Ross provide, some people may be worried that advancements in AI may lead to massive layoffs. But Arruda says that’s not the purpose of Ross. “It’s a tool to augment human capability,” he says. “Ross is not out to replace but to improve.”
For Deep Genomics, AI has only helped the company work more efficiently. The Canadian startup, which launched in July, employs deep learning to assist doctors in diagnosing and treating diseases faster. Brendan Frey, CEO of Deep Genomics and a biomedical engineering professor at the University of Toronto, says his research team trained its system to analyze individual cells to draw conclusions about the entire cellular system and, ultimately, make a diagnosis. “It allows the diagnostician to more quickly produce the report, and gives them a whole new level of information to figure out what the problem is,” Frey says.
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While these technologies can carry out specific tasks extremely well, they’re nowhere near the level of human intelligence, says Ruslan Salakhutdinov, assistant professor of computer science and statistics at the University of Toronto. “Right now, on the deep-learning side, we’re mostly trying to improve speech recognition and object detection,” he says. Some routine tasks will be completely overtaken by machines in the future, but the process will be gradual. Near-term advancements will likely concern speech recognition and voice-to-text technology on smartphones that can better filter out background noise to understand commands. Smart home monitoring systems that can recognize visitors also represent a growing market, Salakhutdinov says. A startup called Netatmo already launched a security camera this summer that sends the names of people it recognizes to the homeowner’s smartphone, as well as notifications about unknown visitors.
Even if the technology is rudimentary, businesses should take its development seriously, says Mike Watson, a principal at Wazuku Advisory Group. Watson advises creating a team to assess how AI will affect all facets of the business and then figure out how to jump on the opportunities. “Companies that adapt will develop a deeper understanding of their clients’ needs while simultaneously operating with lower reliance on human input—and thus lower costs,” says Watson. Those that don’t risk getting left behind. AI will either become a huge aid or a headache to businesses in the future, depending on how they act.
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Would you consider using artificial intelligence for tasks current performed by humans? What white-collar work would you like to see automated? Let us know using the comments section below.