A few weeks ago I asked explicitly about the possible outcomes of current man vs. machine race. Now, an economist and a computer scientist, Carl Benedikt Frey and Michael Osborne of the University of Oxford, have joined forces to examine in detail how susceptible jobs are to computerisation⁽¹⁾.

Our paper is motivated by John Maynard Keynes’s frequently cited prediction of widespread technological unemployment “due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour” (Carl Benedikt Frey and Michael Osborne, “The Future of Employment”)

Computerisation has been historically confined to routine tasks involving explicit rule-based activities, but big data is now rapidly entering domains reliant upon pattern recognition and can readily substitute for labour in a wide range of non-routine cognitive tasks. Advanced robots are gaining enhanced senses and dexterity, allowing them to perform a broader scope of manual tasks. This is likely to change the nature of work across industries and occupations.

Carl and Michael have developed a novel methodology to categorise more than 700 occupations according to their susceptibility to computerisation, and they use it to examine the expected impact of future computerisation on US labour market. Their findings suggest that Machine Learning will put a substantial share of employment (47%), across a wide range of occupations, at risk in the near future.

Their conclusions are brilliantly summarized in an outstanding Figure (Figure III in the paper), where they distinguish between high, medium and low risk occupations, depending on their probability of computerisation (with thresholds at probabilities of 0.7 and 0.3). The figure suggests that an initial wave of automation would be followed by a subsequent slowdown in computers for labour substitution, due to persisting inhibiting engineering bottlenecks to computerisation:

According to our estimate, 47 percent of total US employment is in the high risk category, meaning that associated occupations are potentially automatable over some unspecified number of years, perhaps a decade or two. It shall be noted that the probability axis can be seen as a rough timeline, where high probability occupations are likely to be substituted by computer capital relatively soon. Over the next decades, the extent of computerisation will be determined by the pace at which the above described engineering bottlenecks to automation can be overcome. Seen from this perspective, our findings could be interpreted as two waves of computerisation, separated by a “technological plateau”.

Looking at the figure, it is also easy to notice that this first incoming way of automation will sweep away a significant part of the occupations categorized under:

• Transportation and Material Moving
• Production
• Installation, Maintenance, and Repair
• Construction and Extraction
• Farming, Fishing, and Forestry
• Office and Administrative Support
• Sales and Related

As well, as a significant share of the broad category services.

You should carefully study the results, particularly if you have a stake in the business of education or, for example, if you want to give a well-grounded answer to a typical question like: Daddy, what should I study?

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(1) Frey, C.B., Osborne, M.A., “The future of employment: how susceptible are jobs to computerisation?” September 7, 2013

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