Skills, Artificial Intelligence and Labour

Abstract

The development of artificial intelligence (AI), and in particular of machine learning (ML) technologies, in workplaces is transforming the nature of work and skills. The project addresses this transformation by (1) analysing the challenges of ML systems for work practices; (2) examining skill requirements for different groups of workers interacting with ML (workers, developers and users); and (3) developing criteria for the design of work, skill formation approaches and skill-enhancing ML systems, focusing on transparency and explainability. These goals are addressed through an interdisciplinary co-design approach. An international team of researchers from sociology of work, learning science, engineering and information sciences jointly conducts research in three testbeds: (i) microwork platforms, (ii) construction engineering, and (iii) manufacturing. The co-design framework will combine qualitative and quantitative analytical methods with a participatory approach which will include not only researchers, but also practitioners (managers, engineers, workers) and a broader field of experts from academia, educational institutions, state and business. The outputs will be rich descriptions of opportunities and challenges of ML for work and skill development, a typology of skill requirements for ML-mediated workplaces, policy recommendations and guidelines on the design of skill-enhancing ML technologies and learning and skill development practices in ML-mediated workplaces.

Project Management
N. N.
Duration
01.01.2020-30.04.2021
Funding
Volkswagen Stiftung
Cooperation partners
Prof. Dr. David Guile (University College London), Prof. Dr. Christian Meske (FU Berlin), Prof. Dr. Anoush Margaryan (Copenhagen Business School), Prof. Dr. Miguel Rodriguez (University College London)