Page 43 - The Fourth Industrial Revolution

It is interesting to note that it is not only the increasing abilities of

algorithms, robots and other forms of non-human assets that are driving this
substitution. Michael Osborne observes that a critical enabling factor for
automation is the fact that companies have worked hard to define better and
simplify jobs in recent years as part of their efforts to outsource, off-shore

and allow them to be performed as “digital work” (such as via Amazon’s
Mechanical Turk, or MTurk, service, a crowdsourcing internet
marketplace). This job simplification means that algorithms are better able
to replace humans. This job simplification means that algorithms are better

able to replace humans. Discrete, well-defined tasks lead to better
monitoring and more high-quality data around the task, thereby creating a
better base from which algorithms can be designed to do the work.

In thinking about the automation and the phenomenon of substitution, we
should resist the temptation to engage in polarized thinking about the impact
of technology on employment and the future of work. As Frey and Osborne’s

work shows, it is almost inevitable that the fourth industrial revolution will
have a major impact on labour markets and workplaces around the world.
But this does not mean that we face a man-versus-machine dilemma. In fact,

in the vast majority of cases, the fusion of digital, physical and biological
technologies driving the current changes will serve to enhance human labour
and cognition, meaning that leaders need to prepare workforces and develop
education models to work with, and alongside, increasingly capable,
connected and intelligent machines.

Impact on skills

In the foreseeable future, low-risk jobs in terms of automation will be those
that require social and creative skills; in particular, decision-making under
uncertainty and the development of novel ideas.

This, however, may not last. Consider one of the most creative professions
– writing – and the advent of automated narrative generation. Sophisticated
algorithms can create narratives in any style appropriate to a particular
audience. The content is so human-sounding that a recent quiz by The New

York Times showed that when reading two similar pieces, it is impossible
to tell which one has been written by a human writer and which one is the
product of a robot. The technology is progressing so fast that Kristian

Hammond, co-founder of Narrative Science, a company specializing in

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