Statistics can hold brutal truths. We are constantly told that innovation is occurring faster than ever, yet the data coming out of the so-called Fourth Industrial Revolution suggests that it is anything but revolutionary. Among advanced economies, productivity growth is the slowest it has been in 50 years.
This âproductivity paradoxâ is often attributed to measurement problems or lags after the adoption of disruptive technologies. But another possible explanation is that public debates on technological trends tend to be dominated by the companies and entrepreneurs that are shaping them. The voices of the vast majority of companies that are struggling to keep up with technological change (or actively resisting it) are going unheard.
Buzzy talk relies on biased generalisations
Acknowledging this underrepresented perspective is essential to understanding why the digital revolution is not showing up in the data, and why it may yet stall.
Simply put, buzzy talk tends to rely on biased generalisations. For all their purchase on the public imagination, artificial intelligence (AI), machine learning, big data and humanoid robots fall within the remit of only a handful of companies. The attention these technologies receive is wildly disproportionate to the scale of their development and adoption. As Dan Ariely, of Duke University, North Carolina, said in a lighter vein back in 2013: âBig data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.â
The dynamic is easy to discern. Journalists chase juicy stories. Investors seek attractive returns. Consumers try to anticipate the next technological fad. Social networks, global media and international conferences amplify the voices of disruptors who have an interest in inflating their own prospects. And as the information cascades, the ranks of believers grow. The rumour becomes the rule.
Consider the latest World Economic Forum (WEF) annual report on emerging labour market trends, which is based on a survey of large, multinational corporations. It contends that by 2022 a substantial increase in investments in machine learning, data analytics, new materials and quantum computing will boost demand for data scientists, AI specialists and robotics engineers, to the detriment of existing professions.
Sample not representative of the real economy
The problem is that the WEF population sample is hardly representative of the real economy. Across Organisation for Economic Co-operation and Development (OECD) countries, enterprises employing more than 250 workers account for just 7 per cent of all active companies and employ less than 40 per cent of the workforce. And while the authors of the report acknowledge this bias, their conclusions still amount to dangerous generalisations. Their jobs of the future have nothing to do with the immediate employment needs of the vast majority of small and medium-sized enterprises that are still operating within the framework of the Third Industrial Revolution.
Similarly, an OECD study finds that the labour productivity gap between enterprises at the technological frontier and all other enterprises has been widening sharply over the past decade. Many of the advanced technologies one hears so much about in the media remain unexploited by a nontrivial share of companies, which suggests that we have a long wait before even the most revolutionary innovations start driving GDP.
It has been said that general-purpose technologies such as electricity and the personal computer tend to boost productivity not immediately, but around 25 years after their inception. Yet it has now been 32 years since Robert Solow, winner of the Nobel Prize for Economics, observed: âYou can see the computer age everywhere but in productivity statistics.â And we still do not see the computer age in the productivity statistics. Why should AI be any different from personal computers in this respect?
Ignoring the perspective of technological laggards can have far-reaching policy implications, especially if techno-alarmism diverts attention from pressing problems facing education systems and labour markets in the here and now. If governments start allocating more resources to train the high-skilled professional elite of tomorrow, they could foster even deeper inequality today.
Small companies can seek tougher rules for new technologies
Of course, cynics might dismiss the âlosersâ as having little to add to the debates on technology: at best, they will fill the roles created for them by the digital vanguard; at worst, they will be forced out of the labour market altogether. But it is worth remembering that smaller companies, even if they face economic headwinds, still have the political power to push for tougher regulation of new technologies that threaten their existence.
A global giant such as Uber knows this all too well. Over the years, it has encountered strong resistance from small groups of well-organised taxi drivers who were never invited to gatherings of the global elite to contemplate the virtues of the platform economy. By the same token, the âleft-behindsâ across the worldâs advanced economies are now taking their revenge by bringing anti-trade, populist parties and politicians to power.
To avoid an even worse backlash, and to develop a better appreciation of what the Fourth Industrial Revolution actually entails, one must understand where all companiesï¼not just those at the topï¼stand with respect to todayâs disruptions. A sustainable technological transformation requires widely shared benefits, which means that helping the laggards adapt to the changes is just as important as enabling the innovators to thrive. The voices of the disrupted must be heard.
The author is a Future of the World fellow at the Centre for the Governance of Change at IE University in Madrid
This article was originally produced and published byÂ ChinaÂ Daily. View the original article atÂ chinadaily.com.cn
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