The way forward depends on how you prefer to read this bifurcation between the technologists and the sceptics. We don’t know which group is right: there are no future facts. But there are some observations that can help shape our perspectives on this.

The first is that these widely divergent views are a feature of this point in the technology cycle. The most the most excitable projections of the future of the car were seen at just this point on the oil and auto curve in the 1950s. The technology S-curve in Figure 1, based on the work of Carlota Perez, helps us to understand why. At this point, when the S-curve is at or approaching its second inflection point, people have been experiencing rapid technological change for the best part of two generations. The notion that “the only constant is change” has become a breathless platitude in the public discourse. So, the technologists’ perspective (point ’t’ in Figure 1) is a projection of this steep ramp. The sceptics note instead sign of falling returns and declining customer utility – and see a flattening of the line (point ’s). The gap is large, and one’s perspective on it is a matter of worldview, not evidence.

Figure 1


Source: Carlota Perez/ additional analysis by The Futures Company

Second, almost all business innovation and new business value is driven by the application of knowledge, and the way it is embedded in individuals, teams, and systems. The Futures Company has explored this in recent research with the Association of Finnish Work on the idea of ‘high value work.’ The important point here is that this is true of a whole range of knowledge, including knowledge of service and customers, and knowledge of culture and place, as well as technological knowledge. The most successful businesses use technology to complement and enhance this knowledge, not to replace it.

Third, the trend towards is a deep and powerful one. If Millennials express a desire for meaningful work, this is also true more broadly. We are on the cusp of a transition to a world where, as Hardin Tibbs (2011) has argued, half of the populations of Europe and the United States subscribe to post-modern values (drawing on Inglehart) of autonomy and diversity. The workplace will not escape this trend. One way in which this is expressed is in a transition from consumer or employee to citizen. Increasingly, anyone with any degree of choice in the labour market is choosing employees who recognise them as a whole person, not just as a unit of labour. The evidence suggests that the engagement that the employer gets in return (even, say, in retail) is a powerful driver of performance and profitability.

Fourth, the bargain that businesses struck in the 1980s and 1990s, as they enforced flexibility and “downsized” headcount, may turn out to be a Faustian pact. Shedding jobs and exerting tight control of labour markets increased short-run profits. But at the same time that same control squeezed out their sources of growth. And as both the OECD (Cingano, 2014) and the IMF (Ostry et al, 2014) have noted recently, wage inequality has been a further drag on economic growth. To regain growth, they are likely to have to increase wages and give back some control and power to their workforces.

My own best guess is that we are not headed for long-run technological unemployment. I have changed my mind about this over the past year as I have spent more time with the evidence.

The explanation that seems best to fit present state of work and labour markets is that it has been through a “perfect storm” of a globalised workforce, the deskilling of routine work (which was highly vulnerable to automation) and the shift of these workers into manual or service work, and aggressive deregulation of labour markets driven by a neoliberal political agenda.

The discourse around technological unemployment is not persuasive to me. The “abstract” jobs (using David Autor’s analysis above) will be complemented by technology, and so, in a different way, will be the manual jobs. Meanwhile, the projected gains from Artificial Intelligence and analytics are going to be harder to achieve than currently anticipated. As an example, big data gets less useful as the data sets get larger, and the driverless car, the poster child for the tech future, is a far tougher proposition than Google lets on. Meanwhile, these tech scenarios never seem to include the new jobs that will emerge as we understand better the potential of the technologies, other, sometimes, than as a panic about the possible speed of change.

But, and it is a big but, we’re only part of the way through the dislocation to work and to labour markets caused by this perfect storm. Things will not get better quickly.