ALERT TO THE "DANGER" WE'LL BE WEALTHIER WITHOUT WORKING:

The thinker who has done most to explain the consequences of connectedness is a Belfast man named W Brian Arthur, an economist who was the youngest person ever to occupy an endowed chair at Stanford University and who in later years has been associated with the Santa Fe Institute, one of the world's leading interdisciplinary research institutes. In 2009, he published a remarkable book, The Nature of Technology, in which he formulated a coherent theory of what technology is, how it evolves and how it spurs innovation and industry. Technology, he argued, "builds itself organically from itself" in ways that resemble chemistry or even organic life. And implicit in Arthur's conception of technology is the idea that innovation is not linear, but what mathematicians call "combinatorial", ie one driven by a whole bunch of things. And the significant point about combinatorial innovation is that it brings about radical discontinuities that nobody could have anticipated.

In recent years, we've begun to see the results of this in information technology. The most dramatic case is probably the self-driving car, a development that most of us failed to predict and which was made possible by the sudden conjunction of a whole lot of different technologies. These include: the near-infinite computing power provided by Moore's law; precise digital mapping; GPS; developments in laser and infrared sensor technology; and machine-learning algorithms plus the availability of massive data-sets on which to train them. Put these together using the kind of skilled engineering resources possessed by a company such as Google and you get the self-driving car.

The implications of this vehicle stretch far beyond the future of the automobile industry or even the future of transport. What it signals is that vast swaths of human activity - and employment - which were hitherto regarded as beyond the reach of "intelligent" machines may now be susceptible to automation. So we need to revise our assumptions about the future of work in the light of combinatorial innovation.

Last September, Dr Carl Benedikt Frey and Michael Osborne, two researchers at the Martin School in Oxford, published the results of a major study of the susceptibility of jobs to this new kind of automation. Their report, The Future of Employment: How Susceptible Are Jobs to Computerisation?, makes for a pretty sobering read. Frey and Osborne used machine-learning techniques to estimate the probability of computerisation for 702 detailed occupations, based on US government classifications of those occupations. Their conclusion? About 47% of total US employment is at risk from technologies now operational in laboratories and in the field.

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