EMBARGOED UNTIL 4:30 PM ET, DECEMBER 20, 2016
Box 1: Automated Vehicle Case Study
A helpful case in understanding the types of effects AI may have on productivity and labor
demand is the development of automated vehicles (AVs). Like other forms of technological
disruption, AV technology will likely cause disruptions in the labor market as the economy
adapts to new paradigms.
CEA estimates that 2.2 to 3.1 million existing part- and full-time U.S. jobs may be threatened
or substantially altered by AV technology. Importantly, this is not a net calculation—it does
not include the types of new jobs that may be developed—but rather a tally of currently held
jobs that are likely to be affected by AI-enabled AV technology. A second caveat is that these
changes may take years or decades to occur because there will be a further lag between
technological possibility and widespread adoption.
This estimate of the number of current jobs likely displaced or substantially altered by AVs
starts by identifying occupations that involve substantial driving and relatively few other
responsibilities to lead and coordinate others, drawing occupation descriptions from the
Bureau of Labor Statistics (BLS) and the Occupational Information Network (O*NET). For
each of these occupations, an analysis of what non-driving tasks the occupation also requires
yields an estimate of the share of jobs that will be displaced: driving jobs that also involve
less-automatable tasks have a lower chance of disappearing. For example, the job of school-
bus driver mixes both the tasks of driving and of attending to children. This job will not
disappear, though it may evolve to focus heavily on the task of attending to children. As a
result, AV technology may replace only a modest share of school-bus driver jobs, but child
care workers will still be required. On the other hand, non-driving tasks are less important in
inter-city bus driver jobs, and AV technology will likely replace a large share of these jobs.
Many jobs involve limited amounts of driving. These jobs are not included in the analysis
below as individuals in these occupations would likely see a productivity boost, not a threat of
displacement, as their time allocated to driving is freed up to focus on other critical tasks.
In addition to occupations identified from BLS and O*NET, CEA’s estimate of jobs
threatened or likely to be substantially altered by AVs also includes approximately 364,000
self-employed individuals driving either part- or full-time with ride-sharing services as of
May 2015 that may find AV technology substituting for their services.
Table 1, below, presents the identified occupation categories.