08 Jul 2019   |   Network Updates   |   Update from University of Amsterdam
These updates are republished press releases and communications from members of the Science|Business Network

UvA's new projects on societal implications of AI


Seven interdisciplinary, innovative projects are launched to investigate the societal implications of AI. Highlighting the breadth and the depth of AI research at the University of Amsterdam, these projects showcase the critical need for interdisciplinarity in addressing the opportunities and challenges brought on by the increasing adoption of AI and automated-decision making in a wide variety of societal contexts.

The projects were awarded funding in the first year of the seed funding programme of the UvA Research Prioirty Area 'Human(e) AI'. 

“It is very exciting to see this initiative kicking off, and especially the diversity and richness of AI research at the University of Amsterdam. We expect these seed grants to strengthen and expand the University of Amsterdam’s profile in this area”, highlighted Natali Helberger, Julia Noordegraf, Sonja Smets and Claes de Vreese, members of the RPA Human(e) AI Steering Board.

Awarded projects

  • Ethical MInDS: Mapping interventions for data use in squads
    Prof. Dr. G. van Noort (Faculty of Social and Behavioural Sciences) and Prof. Dr. P. Groth (Faculty of Science)

  • Evolutionary mismatch: The social and moral psychology of human interactions with algorithmic agents
    Dr. G.G. van Houwelingen (Faculty of Economics and Business), Dr. B.T. Rutjens (Faculty of Social and Behavioural Sciences) and Prof. Dr. Ir. J.W. Stoelhorst (Faculty of Economics and Business)
  • Governing AI-driven virtual assistants
    Dr. T. Araujo (Faculty of Social and Behavioural Sciences), Dr. T. Poell (Faculty of Social and Behavioural Sciences) and Dr. J. P. Quintais (Amsterdam Law School)
  • Humanizing speaking chatbots? How prosody in chatbots influences communication effects
    Dr. H. A. M. Voorveld (Faculty of Social and Behavioural Sciences), Dr. T. O. Lentz (Faculty of Science) and Prof. Dr. E. Kanoulas (Faculty of Science)
  • Machine learning classifier to diagnose kidney transplant diseases with quantitative tissue proteomics
    Dr. J. Kers (Faculty of Medicine), Prof. Dr. Garry Corthals (Faculty of Science), Prof. Dr. A. Schönhuth (Utrecht University)
  • Mapping value(s) in AI
    Dr. B. Rieder (Faculty of Humanities), Dr. G. Gordon (Amsterdam Law School) and Dr. G. Sileno (Faculty of Science)
  • Small data, big challenges: Concept drift for multilingual philosophy corpora
    Prof. Dr. A. Betti (Faculty of Humanities), Dr. L. Beinborn (Faculty of Science) and Dr. A.S. Fokkens (VU Amsterdam)

More about the RPA 'Human(e) AI

This communication was first published 4 July 2019 by University of Amsterdam.

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