University of Oxford (lead) and Maastricht University 

Due to developments in machine learning/ AI, increased computing power, big data, and robotics, many machines may turn from tools into workers and soon outcompete human labour in many jobs. Indeed, some economists interpret the reduced labour share of national incomes all over the world as proof that machines are taking over much of the labour.


Some predict that the impact of current waves of automation and robotics on the labour market will substantially different from the one of earlier waves of technological progress. However, others have dismissed this prediction as overly alarmist. Whether the current developments are as disruptive as some believe them to be is still subject to heated debate. This project aims to nourish this debate with relevant research findings and expert opinions. We aim to place current changes into a longer-term historical perspective and examine the evolution of the wage structure and the relative demand and supply for skills from the 1960s onwards.  Understanding how past waves of technological change and automation affected the labour market may help us to predict how current and future waves of automation and robotics may affect the labour market. 

  1. The future of work in Europe

  2.  Understanding technological inequality

  3. Educating for tomorrow's labor market

  4. Reinventing social welfare

  5. Understanding consequences for public finances

  6. Is this time really different?

  7. Co-creating policies that work


Maastricht University (ROA)

University of Oxford (OMS, Skope)

Cambridge Econometrics (CE)

Berlin Social Science Centre (WZB)

University of Tallinn  (Sociology dept)

University of Tilburg (Tranzo)

University of Stockholm (SOFI)

European University Institite (SPS)


Prof. dr. Mark Levels

[mail] [phone]

Dr. Raymond Montizaan 

[mail] [phone

Maaike Bierman (project officer)



This project has received funding from the European Union's Horizon 2020 Research and Innovation programme under grant agreement No 822330

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