Understanding technological change and skill needs: big data and artificial intelligence methods
English
Information is gathered from other international organizations that promote skills development and the transition from education and training to work. The Interagency Group on Technical and Vocational Education and Training (IAG-TVET) was established in 2009 to share research findings, coordinate joint research endeavours, and improve collaboration among organizations working at the international and national levels.
Digital skills
The world of work is undergoing a substantial transformation due to new forces. In particular, technological advances, such as AI, automation and robotics, have produced numerous new opportunities, but also given rise to urgent challenges. While new jobs are constantly being created with the emergence of the digital economy, many jobs are at risk of becoming obsolete. Digital innovations will rapidly change the demand for skills, thereby creating a wider skills gap that has the potential to hold back economic growth. Equipping people with basic or advanced digital skills promises to prepare them for unprecedented job opportunities in the digital economy. This will lead to innovation, higher productivity and competitiveness, as well as expanding markets, access to work and entrepreneurship opportunities.
Research papers
Working papers, reports, and other publications from international organizations, academic institutions and bilateral agencies. Research findings to stimulate informed debate on skills, employment and productivity issues.
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.