Digitalisation of the economy and its impact on labour markets —

<strong>Digitalisation</strong> <strong>of</strong> <strong>the</strong> <strong>economy</strong> <strong>and</strong> <strong>its</strong> <strong>impact</strong> on labour markets
complex than <strong>the</strong> over-simplified notions <strong>of</strong> repetitive work, or routine tasks
not requiring thought. The decline in employment in <strong>the</strong>se repetitive tasks has
been documented in <strong>the</strong> literature (Charles et al. 2013; Jaimovich <strong>and</strong> Siu
2012, quoted in Frey <strong>and</strong> Osborne 2013), with some authors seeing this factor
as a probable explanation for economic growth without employment growth
(Brynjolfsson <strong>and</strong> McAfee 2011 <strong>and</strong> 2014). This background trend is likely to
be accompanied by a strong polarisation <strong>of</strong> <strong>the</strong> labour force with, on <strong>the</strong> one
side, highly skilled <strong>and</strong> highly paid workers <strong>and</strong>, on <strong>the</strong> o<strong>the</strong>r, very low-skilled
manual tasks, with <strong>the</strong> gradual disappearance <strong>of</strong> <strong>the</strong> routine jobs that required
medium-level skills <strong>and</strong> <strong>of</strong>fered middling-level pay (i.e. <strong>the</strong> phenomenon <strong>of</strong>
<strong>the</strong> ‘hollowing out’ <strong>of</strong> <strong>the</strong> middle class).
In future <strong>the</strong> algorithms <strong>and</strong> Big Data combined with <strong>the</strong> increasing skills <strong>of</strong>
robots will, in an increasing number <strong>of</strong> spheres, be able to replace <strong>the</strong> jobs <strong>of</strong>
workers, since <strong>the</strong>se machines will be capable <strong>of</strong> carrying out increasingly
complex <strong>and</strong> non-routine tasks. The conclusions <strong>of</strong> Frey <strong>and</strong> Osborne’s study
(2013) are alarming: ‘according to our estimates around 47 percent <strong>of</strong> total US
employment is in <strong>the</strong> high risk category. We refer to <strong>the</strong>se as jobs at risk – i.e.
jobs we expect could be automated relatively soon, perhaps over <strong>the</strong> next
decade or two’. It is true, <strong>the</strong> authors explain, that this prediction must be
envisaged with caution: developments will depend, in particular, on political
decisions. For example, will <strong>the</strong> circulation <strong>of</strong> driverless lorries be allowed?
And if so, subject to what new highway-code regulations? None<strong>the</strong>less, <strong>the</strong>
concern raised by this trend is to be taken seriously.
By aggregating <strong>the</strong> data put forward by <strong>the</strong>se various authors <strong>and</strong> anticipating
somewhat on <strong>the</strong> next chapter, <strong>the</strong> situation can be summarised as in Table 1.
Table 1
Jobs in <strong>the</strong> digital <strong>economy</strong>
Jobs at greatest risk <strong>of</strong> automation/
digitalisation
Office work <strong>and</strong> clerical tasks
Sales <strong>and</strong> commerce
Transport, logistics
Manufacturing industry
Construction
Some aspects <strong>of</strong> financial services
Some types <strong>of</strong> services (translation, tax
consultancy, etc.)
Jobs at least risk <strong>of</strong> automation/
digitalisation
Education, arts <strong>and</strong> media
Legal services
Management, human resources management
Business
Some aspects <strong>of</strong> financial services
Health service providers
Computer workers, engineers <strong>and</strong> scientists
Some types <strong>of</strong> services (social work,
hairdressing, beauty care, etc.)
New jobs
‘Top <strong>of</strong> <strong>the</strong> scale’
Data analysts, data miners, data architects
S<strong>of</strong>tware <strong>and</strong> application developers
Specialists in networking, artificial
intelligence, etc.
Designers <strong>and</strong> producers <strong>of</strong> new intelligent
machines, robots <strong>and</strong> 3D printers
Digital marketing <strong>and</strong> e-commerce specialists
‘Bottom <strong>of</strong> <strong>the</strong> scale’
Digital ‘galley slaves’ (data entry or filter
workers) <strong>and</strong> o<strong>the</strong>r ‘mechanical Turks’ working
on <strong>the</strong> digital platforms (see below)
Uber drivers, casual odd-jobbing (repairs,
home improvement, pet care, etc.) in <strong>the</strong>
‘collaborative’ <strong>economy</strong>
Source: Christophe Degryse (ETUI 2016) on <strong>the</strong> basis <strong>of</strong> data from Frey & Osborne, Ford, Valsamis, Irani, Head, Babinet
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