| Authors |
Koundouri, P., Pitti, C. and Feretzakis, G. |
| Title |
Sustainability-Related Skills for the Green Transition: AI-Enabled Assessment, Curricula Revision Across All Educational Levels, and Upskilling/Reskilling Pathways for Labour Market Participation |
| Abstract |
The transition to a sustainable economy depends on transforming the workforce at least as quickly as the labour market is being reshaped by automation. This chapter examines how artificial intelligence (AI) can identify the competencies required to deliver the United Nations Sustainable Development Goals (SDGs) and can guide the revision of curricula across all levels of education, while critically assessing the risks that accompany technology-driven workforce planning. Drawing on an operational natural-language-processing framework that extracts skills from policy documents and curricula, maps them to the European ESCO taxonomy and to SDG targets-achieving an overall F1 score of 0.963 for skills extraction and 0.809 for environmental-SDG alignment in an authors' evaluation-we show how AI can accelerate the skills intelligence needed for evidence-based upskilling and reskilling. We weigh these promises against the perils of algorithmic bias, linguistic and regional exclusion, worker displacement, surveillance and rebound effects, and we propose governance and educational pathways for an inclusive transition that genuinely empowers labour-market participation. |
| Creation Date |
2026-07-27 |
| Keywords |
sustainability skills, green transition, artificial intelligence, upskilling and reskilling, curricula reform, Sustainable Development Goals, ESCO, just transition |
| File |
2619.Chapter.Koundouri.Pitti.Feretzakis.FullChapter.v4.pdf (443755 bytes) |
| File-Function |
First version |
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Copyright © 2009 [D.I.E.S.S. A.U.E.B.]. All rights reserved.
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