Tag Archives: Technology and inequality

Hiding from the Computers Part 1: The 47%

A rather dismal chart to kick off the New Year (click for larger image):

Probability of Computerisation jpeg

It’s taken from a paper by Frey and Osborne of Oxford University entitled “The Future of Employment: How Susceptible Are Jobs to Computerisation?”.

Let’s break this chart down. The total area under the curve is equivalent to aggregate US employment. The bottom x axis is the probability that any given job will be computerised: it ranges from zero, no chance of computerisation, to 1, a 100% chance of computerisation. Further, the authors have lumped these probabilities into three broad categories: 1) low probability, zero to 30% change of computerisation, 2) medium, 30% to 70% chance and 3) high, 70% to 100% chance.

So if you are doing a job in the high probability category, there is a high risk that your job will disappear over the course of time. How many people are in this category. Kindly they give the rather shocking number: 47%. Conversely, around 33% of the working population sit in the low probability category and can sleep easily at night for a little while longer.

Now the eagle-eyed will have noticed that there are no dates given in the chart over which the rise of the computers will take place. This is because the authors have looked at the problem as engineers, disassembling jobs into their component parts to decide which bits can be replaced by computers and which can’t. They don’t try to predict when the technology will reach the necessary maturity. In their words:

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 should be note that the probability axis can be seen as a rough timeline, where high probability occupations are likely to be submitted by computer capital relatively soon.

So, accordingly to their guestimate, computers will munch through the job market—moving from right to left in the chart—arriving in the medium probability category some time around 2030.You can also see where you don’t want to be; for example, the yellow band ‘production’ stinks along with orange ‘office and administration support’.

To arrive at this chart, the authors looked at 702 occupations and analysed them with respect to how susceptible each one was to computerisation. Computerisation here is taken in the broad sense to include machine learning, artificial intelligence and mobile robotics. To do so, they identified cognitive and non-cognitive bottle necks to computerisation and used these as variable to predict the order and extent of future computerisation. The bottleneck variables are given below:

O Net Variable Jan 14 jpeg

Further, a bottleneck such as manual dexterity could be classed as low, such as fitting a light bulb, to high, as for example performing open heart surgery.

Overall, the paper’s analysis suggests that the job market, as we know it, will be blown up over the next two decades, along with all our economic assumptions. Yet I hear not one politician talking about this risk. I will return to this subject in my next post.