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Article Dans Une Revue Human Systems Management Année : 2021

Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps identification using text mining

Résumé

BACKGROUND: The renewed advent of Artificial Intelligence (AI) is inducing profound changes in the classic categories of technology professions and is creating the need for new specific skills. OBJECTIVE: Identify the gaps in terms of skills between academic training on AI in French engineering and Business Schools, and the requirements of the labour market. METHOD: Extraction of AI training contents from the schools’ websites and scraping of a job advertisements’ website. Then, analysis based on a text mining approach with a Python code for Natural Language Processing. RESULTS: Categorization of occupations related to AI. Characterization of three classes of skills for the AI market: Technical, Soft and Interdisciplinary. Skills’ gaps concern some professional certifications and the mastery of specific tools, research abilities, and awareness of ethical and regulatory dimensions of AI. CONCLUSIONS: A deep analysis using algorithms for Natural Language Processing. Results that provide a better understanding of the AI capability components at the individual and the organizational levels. A study that can help shape educational programs to respond to the AI market requirements.

Dates et versions

hal-03238490 , version 1 (27-05-2021)

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Citer

Lamiae Benhayoun-Sadafiyine, Daniel Lang. Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps identification using text mining. Human Systems Management, 2021, Higher education and labor markets: Challenges for society, 40 (5), pp.639-651. ⟨10.3233/HSM-211179⟩. ⟨hal-03238490⟩
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