Seite - (000046) - in Disrupted Development and the Future of Inequality in the Age of Automation

38 L. SCHLOGL AND A. SUMNER autonomous vehicles, vessels, and drones, to 3D-printed buildings and new breakthroughs in machine learning made by firms in the Silicon Valley and beyond. A growing number of empirical studies and several monographs have recently addressed the broader phenomenon of a “dig- ital revolution” which is unfolding at high speed across OECD countries. Interest in the impact of technological change is by no means new of course as the detailed empirical study of Leontief and Duchin (1984) is testimony to. Indeed, one can trace the subject back to the classical writ- ings of David Ricardo (2010 [1817]) and Karl Marx (2012 [1867]) or Joseph Schumpeter (1943). The bulk of research on the economic impli- cations of digital transformation has so far focused on advanced indus- trialized economies where the cost of labor is high and manufacturing shows a high degree of mechanization and productivity. Yet, the devel- oping world is both affected by automation trends in high-income coun- tries (HICs) and is itself catching up in terms of automation. Indicative of this, the International Federation of Robotics (IFR) reports that Asia is currently the “strongest growth market” in a “sig- nificant rise in demand for industrial robots worldwide” (IFR, 2016, pp. 11f.). A double-digit growth trend includes not only China, Korea, and Japan but also emerging economies in South East Asia. The IFR (2016) estimates that by 2019, more than 250,000 units of multipur- pose industrial robots will be installed in Asia on a yearly basis, with the main industries driving demand in robots being the automotive, elec- trical/electronics, metal, and machinery, as well as the rubber and plas- tics industries. This only captures the more easily measurable demand for robotics hardware and does not take account of the widespread use of software in the context of economic production. In some domains of automation, emerging economies are, in fact, ahead of many OECD countries, as the opening of Beijing’s first driverless subway line in 2017 (Yan, 2017) or the popularity of the mobile phone-based financing plat- form M-Pesa in Kenya illustrate. The digitization and automation of economies raises the question of what lessons the developing world can draw from extant evidence. “Late developers” are facing the digital revolution considerably ear- lier and under different conditions than today’s advanced economies. There is thus an increasing worry that “increased automation in low- wage countries, which have traditionally attracted manufacturing firms, could see them lose their cost advantage and potentially lose their ability of achieving rapid economic growth by shifting workers to factory jobs”