A panel working with the National Academies of Sciences, Engineering and Medicine has published a much-needed report on developing new tools to track two important trends:

  1. the rate at which A.I. is developing
  2. how these developments are affecting U.S. employment

As the co-chairmen* of the panel put it, we are currently “flying blind” on these trends.

Thus, without inventing some new kind of ‘radar,’ we won’t know either our location or where we’re headed, and we won’t know how to give career and training/retraining advice to vulnerable U.S. workers.

To give an example of such advice: “Mr. Smith, your current job likely won’t exist in 6 years; here’s a related job that probably will still exist, and here’s how to start training for it.”  Or, “Ms. Jones, the college major you’ve chosen most commonly leads to these 3 careers, all of which have a >70% chance of being automated in 15 years.  Perhaps consider another major!”

As the panel notes, however, elements of these tracking tools already exist, in the form of the A.I. and Big Data infrastructures currently in place (LinkedIn, Google, etc.).   What is needed, the panel says, are public-private collaborations to combine the existing mountains of data with secure, anonymous, and unbiased ways of distributing and making sense of it.

Thus, one essential way to track and adjust to the development of A.I. is by means of A.I. — provided that oversight for the common good is also in place.  (In particular, machine learning’s focus on gleaning practical insights from petabytes of data will be key.)  If properly directed, the very technologies that threaten so many workers’ jobs may, it turns out, help put those same workers back to work.

*The panel is co-chaired by Erik Brynjolfsson of MIT, the co-author of the outstanding The Second Machine Age — a must-read on the topic of A.I. and employment.

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