THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERIZATION?

Probability of
Computerisation
1
Dishwasher
Event
Planner
Public
Relations
0
0 100
Social Intelligence
Probability of
Computerisation
1
Court Clerk
Fashion
Designer
0
Biologist
0 100
Creativity
Probability of
Computerisation
1
Telemarketer
Boilermaker
0
Surgeon
0 100
Perception and manipulation
FIGURE I. A sketch of how the probability of computerisation might vary as a function of
bottleneck variables.
non-susceptible task characteristics.
IV.
MEASURING THE EMPLOYMENT IMPACT OF COMPUTERISATION
IV.A. Data sources and implementation strategy
To implement the above described methodology, we rely on O∗NET, an online
service developed for the US Department of Labor. The 2010 version of O∗NET
contains information on 903 detailed occupations, most of which correspond
closely to the Labor Department’s Standard Occupational Classification (SOC).
The O∗NET data was initially collected from labour market analysts, and has
since been regularly updated by surveys of each occupation’s worker population
and related experts, to provide up-to-date information on occupations as they
evolve over time. For our purposes, an important feature of O∗NET is that it
defines the key features of an occupation as a standardised and measurable set
of variables, but also provides open-ended descriptions of specific tasks to each
occupation. This allows us to: (a) objectively rank occupations according to
the mix of knowledge, skills, and abilities they require; and (b) subjectively
categorise them based on the variety of tasks they involve.
The close SOC correspondence of O∗NET allows us to link occupational
characteristics to 2010 Bureau of Labor Statistics (BLS) employment and wage
data. While the O∗NET occupational classification is somewhat more detailed,
distinguishing between Auditors and Accountants, for example, we aggregate
these occupations to correspond to the six-digit 2010 SOC system, for which
employment and wage figures are reported. To obtain unique O∗NET variables
corresponding to the six-digit SOC classification, we used the mean of
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