Open AccessDoes higher education properly prepare graduates for the growing artificial intelligence market? Gaps’ identification using text mining
Author(s) -
Lamiae Benhayoun,
Daniel W. Lang
Publication year - 2021
Publication title -
human systems management
Language(s) - English
Resource type - Journals
eISSN - 1875-8703
pISSN - 0167-2533
DOI - 10.3233/hsm-211179
Subject(s) - categorization , identification (biology) , computer science , certification , artificial intelligence , python (programming language) , knowledge management , natural language processing , data science , management , botany , economics , biology , operating system
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.