A carregar...
Publicação
AI-Powered Career Navigation Platform: Predicting Automation Risk and Guiding Professionals to Optimal Occupation Transitions with a Focus on Generation X in Portugal
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 3.87 MB | Adobe PDF |
Autores
Orientador(es)
Resumo(s)
The rapid advance of artificial intelligence (AI) and automation technologies has raised
significant concerns about job displacement, particularly among Generation X professionals in
Portugal. This project addresses these concerns by developing an interactive recommendation
system named Career Xplorer, designed to help professionals navigate potential career
transitions in a personalised way. Using advanced Natural Language Processing (NLP) models
such as BERT and GPT-4 and a task-based approach that assesses automation risk for
individual tasks rather than entire occupations, Career Xplorer estimates the automation
probability for each user’s occupation. The recommendation system also suggests alternative
occupations with lower automation risks and provides a detailed job transition guide outlining
the essential skills and competences needed for these transitions. This guide helps users
identify which skills to focus on and which to deprioritise, facilitating a more confident and
smoother professional transition. The study finds that not only occupations with repetitive
and low-skilled tasks face the greatest risks of automation but also more technical roles,
mainly due to the presence of well-established rules. On the other hand, more communicative
and creative occupations have lower levels, suggesting an area of greater security in a labour
market impacted by AI and automation. By empowering Generation X professionals with the
tools and knowledge to proactively manage their careers amidst the evolving technological
landscape, Career Xplorer helps mitigate the impacts of job displacement and promotes longterm career stability and growth while taking employee happiness into account.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science
Palavras-chave
Job Displacement Job Transition Guide Automation Risk Natural Language Processing Interactive Recommendation System SDG 1 - No poverty SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 10 - Reduced inequalities SDG 17 - Partnerships for the goals