Abstract

Innovative technologies such as Artificial Intelligence (AI) increasingly transform societies and economies. The actual consequences of AI on workers and jobs are not well understood yet. Particularly, knowledge gaps remain when it comes to identifying the causal effect of AI applications at workplaces on workers and jobs. Empirical studies on the micro-level are still scarce, and many of the most pressing questions remain unanswered: How does AI change the tasks and skill profiles of existing jobs? How does AI affect productivity and performance of workers in various jobs? How do workers perceive the changes and respond to them, e.g. in terms of well-being? And what are the macro level implications of potential AI diffusion? How does AI affect the job structure, skill demands and inequality on the labour market? With our research project, we address these hiatuses in knowledge, investigating the causal impact of AI on workers and jobs. The project gives access to causal evidence from randomised controlled trials (RCTs) in large companies in combination with access to high quality register data of workers` careers in the long run. We deal with matters of generalisability of our micro level field studies, exploring the macro level impact of potential AI diffusion and broader labour market trends. Building on a co-creation process with scientists, managers, technology experts and e.g. works council representatives of the host organisations, the transdisciplinary team performs empirical research at workplaces in three large companies in Germany. The project combines high-level empirical research with co-creative formats that are adapted to the needs of business and policy making. Doing so, the project enables peer learning, fosters social partnership and helps create policies that work.