AI for industry 5.0 – matching job seekers and employers based on organizational values and skills

Problem Context

The fourth industrial revolution or Industry 4.0 is about the automation of different industrial processes made possible by advances in technologies such as artificial intelligence and robotics. While Industry 4.0 focuses on automation and relieving humans from timeconsuming tasks, Industry 5.0 is more human-centric, focusing on the wellbeing of workers. One of its main aims is to empower workers and focus on their sustainable development and growth in the fast-changing job-market.

The Horizon Europe Bridges 5.0 proposal, which was granted, aims to help in this transition towards Industry 5.0. One of the focus areas of the proposal is to use data-driven models to evaluate a company according to its values, specifically whether it invests in the wellbeing of its employees. Examples of these evaluation criteria include possibilities for learning and career advancements, variation of work and learning organization culture. This organisational information is relevant for workers/job seekers to assess whether a company is a good fit for them. Currently, however, the organizational values are not readily available and not considered for matching workers/job seekers with occupations/job vacancies. An AI matching system should not just have a single objective of matching according to skills, but the organizational values should also be fitting. In this way, long-term societal and ethical values are considered for matching rather than just short-term efficiency.

Solution

The objective of this project is to (1) extract organizational values from different data sources using natural language processing (NLP) and (2) include those relevant organizational values in an AI matching system between workers/job seekers and employers. It is not enough to only look at the required skills-sets for a vacancy, the organizational values of a company should also be a good fit for the worker/jobseeker. Explicitly involving the organizational values of a company in recruiting and deploying employees, can avoid future disappointments which can lead to dissatisfaction in the working place. Furthermore, the output of the envisioned AI matching system should be explainable and transparent towards the worker/jobseeker and the employer.

Results

Affiliations

The work of this Appl.AI use case project is endorsed by Bridges 5.0. The project is funded by the European Commission in the Horizon Europe programme. The activities in this project will furthermore be developed in partnership with our UK partner from Warwick University and our French partner from CEET-CNAM. The work will be aligned with the CEDEFOP Data Lab. CEDEFOP has developed a major EU-level data scraping of skills in job vacancies. We will work in partnership with CEDEFOP and EUROSTAT in the screening and analysis of this data. The expertise of our UK and French partners will be in support of the TNO-activities.