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One size does not fit all: Constructing complementary digital reskilling strategies using online labour market data

Author: Stephany, F.
Published in: Big Data & Society, 8(1)
Year: 2021
Type: Academic articles
DOI: 10.1177/20539517211003120

Digital technologies are radically transforming our work environments and demand for skills, with certain jobs being automated away and others demanding mastery of new digital techniques. This global challenge of rapidly changing skill requirements due to task automation overwhelms workers. The digital skill gap widens further as technological and social transformation outpaces national education systems and precise skill requirements for mastering emerging technologies, such as Artificial Intelligence, remain opaque. Online labour platforms could help us to understand this grand challenge of reskilling en masse. Online labour platforms build a globally integrated market that mediates between millions of buyers and sellers of remotely deliverable cognitive work. This commentary argues that, over the last decade, online labour platforms have become the ‘laboratories’ of skill rebundling; the combination of skills from different occupational domains. Online labour platform data allows us to establish a new taxonomy on the individual complementarity of skills. For policy makers, education providers and recruiters, a continuous analysis of complementary reskilling trajectories enables automated, individual and far-sighted suggestions on the value of learning a new skill in a future of technological disruption.

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Fabian Stephany, Dr.

Assoziierter Forscher: Innovation, Entrepreneurship & Gesellschaft

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