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Lessons learned from the underrepresentation of women in STEM: AI-enabled solutions and more
Abuwatfa, Waad Hussein Zamel, Nada Al-Othman, Amani
Abuwatfa, Waad Hussein
Zamel, Nada
Al-Othman, Amani
Date
2021
Advisor
Type
Article
Peer-Reviewed
Published version
Peer-Reviewed
Published version
Degree
Citations
Altmetric:
Files
Description
Abstract
The absence of women in STEM and energy sectors is driven by discrimination and socio-cultural factors. A greater number of women “leak out” from Energy and STEM fields than men. AI-enabled solutions offer analysis tools to measure and evaluate diversity and inclusion.