The Long Road Ahead for AI and the Future of Work

MIT Conference Lays Out the Long Road Ahead for AI & the Future of Work

I had the privilege of attending the AI and the Future of Work conference at MIT last week, a joint project of MIT research centers, CSAIL (Computer Science and Artificial Intelligence Laboratory) and IDE (The Initiative on the Digital Economy). The conference brought together leading academics across science, technology, economics and business, as well as a variety of stakeholders from the public and private sectors, for thoughtful dialogue on the impact of artificial intelligence as it relates to the workforce.

One theme came up repeatedly over the two-day conference: artificial intelligence presents society not with one distinct challenge, but with two.

  1. How do we ensure that our workforce is able to adapt to new technologies in the near-term future?
  2. How do we ensure that the more distant future these technologies create, is one of inclusive prosperity?

While these problems weren’t solved in Cambridge last week, speakers at the conference shared many ideas on how to tackle each issue. Here’s a recap of the highlights.

When it comes to ensuring our workforce adapts successfully to the near-term future of work changes, most speakers agree that the future is already here. Whether seen in the adoption of robotics in manufacturing or in the rise of e-commerce, there are a variety of industries in which workers are already feeling the impacts of the digital revolution. Helping these individuals remain employed, useful members of the workforce—despite technological displacement—boils down to their capacity to add-to and reapply their existing skills.

Recommendations made last week include:

  • Consider which human skills are beyond the reach of technology, at least in the foreseeable future. These skills—which many speakers argue include creativity and interpersonal relations—are applicable across a wide variety of fields, provide solid foundation for workers, and are sure to be marketable over the course of their careers, despite where technology takes us.
  • Determine which skills are currently in-demand, and identify skill-adjacencies—similar skill sets that one already has—which can be adapted and built out in order to pursue new career paths. Bit Source co-owner, Rusty Justice, explained that his company hires and trains former coal miners to become software developers, building on the collaborative and analytical skills they’ve developed and relied on in their former careers.
  • Utilize targeted, short-term training programs that will help get displaced employees up to speed and back to work quickly. By the time one completes a four-year degree, the workforce skills most in-demand will have likely changed. Often times, shorter courses or training programs are a stronger investment as they provide enough education to give workers the skills they need, but are also completed in time for those skills to remain relevant.

These recommendations are relevant both for workers themselves and for the variety of organizations that aim to help them. Highly-touted among these institutional efforts are ones in which employers and educators work together to ensure candidates receive the most up-to-date education, develop applicable skills and leave training with a job offer in-hand.

Despite having more time to prepare, envisioning the distant future as it will be affected by artificial intelligence is a much different—and much more difficult—story. Whereas in the short-term, we have a good sense of what will become technologically feasible, a number of speakers noted that we have little ability to project the technology that will be achievable in the long-term.

There was, however, some consensus:

  • Many jobs will modify, rather than disappear, as technology’s advantage over humans is not uniform to all tasks. While some tasks may be given to a computer, humans will still be doing many of the other tasks that were once considered part of the same job. Discussed at the conference were examples such as doctors interacting with patients more and diagnosing less, and journalists identifying breaking news less while putting a heavier focus on investigating and asking great questions.
  • Technological adoption is driven not by capability but by demand. Several speakers suggested that there will always be demand for human work. Examples for this were seen in hand-made items commanding higher prices than those made by machines, and the need for communicating information (namely bad news) on a human-level, with empathy.
  • Despite the uncertainty over what humans will do after this digital revolution, creativity, initiative, and entrepreneurial prowess were all emphasized as the most likely essential skills in the future of work. Agreement was unanimous that our entire education system needs to be revamped in order to ensure students gain these skills, as our current system—designed for the industrial era—doesn’t match up to the coming digital age. These changes need to be enacted swiftly.

At the conference, most speakers expressed a great deal of optimism about the future, implying that not only will there be work for our children and grandchildren in the years to come, but that through good policy and programs, we’ll be able to ease the transition as well.

Google prototype self-driving car” by Marc van der Chijs is licensed under CC BY 2.0

Written by

ZipRecruiter's former Chief Economist, Cathy Barrera is the founding economist of Prysm Group, a leading blockchain economics and governance design firm.

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