In today’s rapidly evolving labor market, the emergence of new roles and the decline of traditional ones have led to a complex landscape of job titles and skill requirements. This complexity often causes ambiguity and confusion, affecting both novices and experienced professionals. To address this, extensive international efforts have produced reference databases of jobs and skills, such as ESCO and O*NET. However, the challenge remains to make this information easily accessible and interpretable for users with varying levels of expertise. To address the challenge above, this paper introduces a Knowledge Plug-in for ChatGPT, designed to serve as an intuitive, user-friendly interface between workers and these authoritative databases. By harnessing the power of natural language processing (NLP), the plug-in enables a seamless question-answering experience, effectively masking the underlying complexity with a carefully engineered architecture. Furthermore, generative AI enhances the user experience by providing relevant information in domains extending beyond the traditional scope of employment. An initial user study demonstrates the plug-in’s effectiveness in improving the usability and accuracy of job-related queries. We detail the development, architecture, and validation of this innovative tool, highlighting its potential impact on the future of employment search and career development.

A Seamless ChatGPT Knowledge Plug-in for the Labour Market

DESSi D.;reforgiato Recupero D.
;
Scarpi G.
2024-01-01

Abstract

In today’s rapidly evolving labor market, the emergence of new roles and the decline of traditional ones have led to a complex landscape of job titles and skill requirements. This complexity often causes ambiguity and confusion, affecting both novices and experienced professionals. To address this, extensive international efforts have produced reference databases of jobs and skills, such as ESCO and O*NET. However, the challenge remains to make this information easily accessible and interpretable for users with varying levels of expertise. To address the challenge above, this paper introduces a Knowledge Plug-in for ChatGPT, designed to serve as an intuitive, user-friendly interface between workers and these authoritative databases. By harnessing the power of natural language processing (NLP), the plug-in enables a seamless question-answering experience, effectively masking the underlying complexity with a carefully engineered architecture. Furthermore, generative AI enhances the user experience by providing relevant information in domains extending beyond the traditional scope of employment. An initial user study demonstrates the plug-in’s effectiveness in improving the usability and accuracy of job-related queries. We detail the development, architecture, and validation of this innovative tool, highlighting its potential impact on the future of employment search and career development.
2024
Conversational agents
labor market
large language models
natural language processing
occupational databases
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/480306
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