Publicação
Artificial intelligence applications supporting women’s career development: a scoping review
| dc.contributor.author | Fonolla, Sara Portell | |
| dc.contributor.author | Fassi, Yasmina El | |
| dc.contributor.author | Gaspar, Augusta D. | |
| dc.contributor.author | Correia, Luís | |
| dc.contributor.author | Pinto, Joana Carneiro | |
| dc.date.accessioned | 2026-05-05T16:27:27Z | |
| dc.date.available | 2026-05-05T16:27:27Z | |
| dc.date.issued | 2026-02-22 | |
| dc.description.abstract | Artificial intelligence (AI) is increasingly integrated into career guidance and organisational decision systems, yet empirical evidence on applications designed to support women’s career development remains limited. Following PRISMA-ScR and a preregistered protocol, we searched 7 databases (plus backward and forward citation searching) and synthesised 13 empirical studies published between 2018 and 2025. Using inductive thematic analysis, we identified three functional domains: (a) bias mitigation and representation (e.g., auditing gendered language and platform-level disparities), (b) skills development and empowerment (e.g., AI-supported learning and writing interventions), and (c) career pathways and retention (e.g., matching and attrition-risk modelling). The evidence base was concentrated in system-facing applications that detect or shape inequities within recruitment, evaluation, and exposure systems; fewer studies evaluated individual-facing developmental support, and sustained career outcomes were rarely measured. Formal theory use was limited, with only a small minority of studies explicitly drawing on established frameworks; reporting on ethics, transparency, and governance was inconsistent. We suggest that research prioritises longitudinal and theory-informed evaluations, including intersectionality-informed analyses, and assess downstream impacts on women’s career trajectories alongside robust governance and accountability practices. | eng |
| dc.identifier.doi | 10.31234/osf.io/ef7q5_v1 | |
| dc.identifier.other | 642ef6bf-3933-47d7-9687-e857b1b77e73 | |
| dc.identifier.uri | http://hdl.handle.net/10400.14/57656 | |
| dc.language.iso | eng | |
| dc.publisher | OSF | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Artificial intelligence | eng |
| dc.subject | Career development | eng |
| dc.subject | Gender equity | eng |
| dc.subject | Women in STEM | eng |
| dc.subject | SDG 5 | eng |
| dc.subject | SDG 8 | eng |
| dc.subject | Bias mitigation | eng |
| dc.subject | Governance | eng |
| dc.title | Artificial intelligence applications supporting women’s career development: a scoping review | |
| dc.type | preprint | |
| dspace.entity.type | Publication | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 |
Ficheiros
Principais
1 - 1 de 1