Can More Robust Job Training Stem AI Disruption?

While the jury is still out on how AI will affect job markets, warning signs abound and policymakers are searching for ways to ease the transition.  Not surprisingly, expanded job training programs rank at the top of most policy solution sets.  While I applaud this belated appreciation of workforce development programs, a new report from Anthropic cautions that training alone will not solve the AI job transition challenge. 

“An Evidence Review of Workforce Training” offers a detailed policy and literature review of workforce training models and impacts.  The findings focus on stand-alone programs, as opposed to training programs at community colleges or apprenticeships.  The research finds that training programs do help, but their impacts can be relatively small. They tend to have real, but small, effects on overall  employment level (up an average of 1.7%) and incomes (with average increases of only $800).  Sectoral programs, such as cluster or employer-led efforts, can have bigger impacts, but more research is needed on how these programs work.

What can we conclude from this sobering research?  My take is that addressing AI disruptions will require more than simply spending more on current workforce programs.  We will need to rethink programs, repackage them, and consider bringing in new models and approaches.  This will be a tough challenge, but maybe there is a silver lining.  As we deal with AI disruptions, we may finally get serious about building robust and effective workforce development systems that American workers need and deserve.