HORIZON EUROPE┋Assessing and strengthening the complementarity between new technologies and human skills



Expected Outcome

Projects should contribute to all of the following expected outcomes:

  • Deepened our understanding on the potential and impact of new technologies such as artificial intelligence technologies and robotics to substitute or complement human skills and in performing job tasks.
  • Development and deployment of technologies that complement and enhance human skills, and development of the corresponding skills in the workforce.


Recent research highlights that new technologies may increase or reduce overall employment opportunities: they tend to increase them in the presence of strong productivity gains or if they create new tasks that are best carried out using human skills (possible example: a nurse using medical machines to perform checks previously carried out by a doctor), but can reduce them if the substitution of labour by machines dominates (possible example: self-service supermarket counters). However, there is still a limited understanding of which types of technologies and technology applications are particularly promising from the perspective of enhancing rather than displacing human skills and of creating employment opportunities as well as decent working conditions.

Some authors argue that recent technological change has been biased towards automation and has focused insufficiently on creating new tasks where labour can be productively employed, with associated declining labour shares in national income, rising inequality and lower productivity growthThis highlights the need to better understand the complementarity between new technologies and skills that can serve as basis for policy recommendations that complement and enhance human skills, such as targeting investment subsidies. Policy may for instance want to prioritise public investment support in areas where innovation is more complementary to existing skills (possible examples: education and healthcare as opposed to pattern recognition “across the board”), including of people without high formal qualifications (or for other disadvantaged groups, e.g. those affected by disabilities), or it may want to support the development of skills complementary to emerging technologies with targeted education and training programmes. Both types of policy interventions could improve the impacts of new technologies on employment prospects, decent working conditions and social inclusion, but their design requires opening the “black box” of technology-skill demand complementarity.

Examples of research activities carried out under this topic include the development of criteria to assess the complementarity of specific new technologies with human skills and vice versa. This could include an analysis of specific applications of new technologies (such as artificial intelligence technologies and robotics), possibly with a sectoral or occupational focus. It could also include the development of policy recommendations to support technologies and skills/training courses that are conducive to a digital transition that creates more good jobs. Clustering and cooperation with other selected projects under this call and other relevant projects are strongly encouraged.

Date de candidature
Humanités : Anthropologie & Ethnologie, Numérique, Big Data
Sciences sociales : Droit, Economie, Gestion et administration publique, Identités, genre et sexualités, Psychologie et sciences cognitives, Science politique, Sciences de l'éducation, Sciences de l'information et de la communication, Sociologie