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The Impact of A.I. in the Millennial Job Market

Columns | February 7, 2017

One of my fondest Tufts memories was Halloween my sophomore year when I dressed up as a “Tufts Dad.” I wore my pants high-waited, a brown Tufts Dad T-shirt, sported a Tufts Alumni mug, and carried a copy of the Wall Street Journal tucked into my Lee jeans. My character reminisced on the trials and tribulations of signing up for classes with a pen and paper, and having to wait in line on a Friday night to use the payphone in Lewis Hall only to be swiftly rejected by any and all potential dates to the Saturday sock hop—“You kids don’t know how good you have it!”

Regardless of how “good” we may or may not have it, our generation is certainly at a crossroads with our relationship to technology. Is this more connected world one that we have chosen to live in? Or was it clandestinely thrusted upon us? I believe our generation is standing on the floor of a court room with no one to defend us against the fast development of technologies challenging the role of human beings in the home, the workplace, and the classroom.

Descartes saved humanity from similar lines of questioning in the early enlightenment by clearly explaining that rational, strategic, and evidence-based thinking is what makes human beings unique to this planet—“I think, therefore I am.”

Centuries later, the professional fields we hold near and dear as bastions of intellect, such as law, medicine, and academia, are being forced to question the role of “thinking” once again as artificial intelligence (A.I.), or the theory and development of computer systems able to perform tasks that normally require human intelligence, continues to develop. Examples of A.I. include visual perception, individual task management, speech recognition, decision-making, and language translation. Primarily, A.I. is being developed to address issues relating to task productivity, efficiency, and human error. This progress is beginning to affect global industries.

At the University of Toronto, researchers have created an A.I. lawyer named Ross. Ross can take legal questions posted by attorneys and sift through its ever-expanding database of legal statutes and jurisprudence to come up with the “correct” answer. The system grows more accurate over time as it learns about a firm’s specific areas of practice. Much like a first year paralegal, Ross learns by completing tasks and gets better as he goes along. The only difference between Ross and a novice paralegal is that he never shows up late, has perfect recall, and wouldn’t dare excuse himself from work for another “finding myself” trip around the world.

Aspiring doctors are not off the hook. Modernizing Medicine is just one example of web-based repositories of medical information that have received billion dollar investments in the last fiscal year. A doctor lists a patient’s symptoms and within seconds the site presents drug options that have worked in comparable cases. The system lets practitioners tap into the collective knowledge of doctors and institutes around the world gathered from roughly 3,700 providers and more than 14 million patient visits. It’s a bit like how Amazon remembers your favorite purchases, cross lists it with trends across the web, and makes recommendations for your next purchase.

What about academia’s crystal castle? While we may not see I-Robot-esque humanoids pontificating in Braker 001 within the decade, there are many projects already in the works that use computer intelligence to help students and teachers get more out of the education experience. There are many possible examples showcasing the ways those tools, and those that will follow them, will shape and define the educational experience of the future. One could be the possibility of completely automated grading, eliminating the chances that your T.A. had a good day and would give you extra credit for showcasing that you did the extra readings. In most cases, the true frontier of the education experience is already here vis-a-vis online classes, gaps in learning being filled by detailed Google searches as opposed to office hours, and open access to academic journals.

In all these fields, the human role shift is moving from practitioner to facilitator. Most centrally, this means other professional fields may be forced to adopt these technologies sooner rather than later as a necessity for competing on a global stage. Their day-to-day could move more towards software and management than expertise and experiential knowledge. These professional fields and others will be forced to reconcile with what MIT Media Lab director, Joi Ito, refers to as “emergence mindset,” in which success is no longer determined by one’s ability to learn all possible information and retain it themselves, but by their capacity to find information in a timely manner. It will be our job, as both shapers and test-dummies of such technologies, to be vigilant, to speak up when these tools do not serve our collective mission as a school and as a global community. We will be better off if we understand the tools around us and how to effectively put them to use.