The world of work is being impacted by a fourth industrial revolution, transformed by artificial intelligence and other emerging technologies. With forecasts suggesting large shares of workers, displaced by automation, in need of upskilling/reskilling, the design of active skills policies is necessary.
Conventional methods used to anticipate technological change and changing skill needs, such as skill surveys and forecasting, have limited scope to provide insights into emerging trends. With the increasing use of big data and AI methods, analysts have new ‘real-time’ tools at their disposal. Skill foresight techniques are also increasingly used to gauge in-depth stakeholder information about future technologies and skill needs.
A series of Cedefop guides aims to inform analysts and policy-makers about available skills anticipation methods used to navigate through the uncertainty of changing technologies and skill demands. This second practical guide focuses on automated skills intelligence methods: big data and AI-driven analyses.
Cedefop (2021). Understanding technological change and skill needs: big data and artificial methods: Cedefop practical guide 2. Luxembourg: Publications Office. http://data.europa.eu/doi/10.2801/144881
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Understanding technological change and skill needs: big data and artificial intelligence methods