TRANSEUROWORKS: Transforming European Work and Social Protection

• European Commission, H2020 program
• November 2022 - October 2026

TransEuroWorkS examines the main structural transformations of the labor market: the green transition and decarbonization, technological change, and the internationalization of the workforce. The project aims to offer a multi-disciplinary approach to understand the impacts of these transformations on workers, institutions, work relations, and policymaking. Special emphasis is placed on assessing the effects on inequality, poverty, education, skill demand, and social exclusion.

The Spanish research team is centered on examining technological change, particularly focusing on shortages in digital skills and the need to retrain the workforce in digital competencies. Given the significance of providing digital skills as an integral part of Europe’s Digital Transition, the research team plans to conduct a field experiment in Catalonia to study the effect of short digital training programs on the unemployed population. The study will assess self-selection, and analyze impacts on labor market outcomes, psychological well-being, and socio-political integration.

CATAI – Citizen Attitudes towards Artificial Intelligence

• Spanish Ministry of Science and Innovation
• January 2023 - December 2026

CATAI studies the implications of recent technological transformations encompassing digitalization, automation, and artificial intelligence (AI), for the realm of work and politics. This project explores the consequences of AI introduction in workplaces on workers’ political behavior, amid ongoing debates about the complementary or substitutive nature of AI and its distributive consequences for workers.

From a political science approach, the project aims to address the following goals: 1) To assess the current status of AI adoption in workplaces from both workers’ and companies’ perspectives; 2) To map and analyze responses from the political sphere –including political parties and governmental public policies– concerning AI-related risks for workers; 3) To investigate citizens’ experiences and attitudes towards AI adoption in workplaces, and support for public policies to AI-related risks. To accomplish these goals, the project uses a variety of research methods including reviews of secondary literature, focus groups, surveys, and machine learning techniques for text analysis.