Fostering Austria's Innovative Strength and Research Excellence in Artificial Intelligence



FAIR-AI addresses the research gap posed by the requirements of the upcoming European AI Act and the obstacles of its implementation in the daily development and management of AI-based projects and its AI Act conform application. These obstacles are multilayered due to technical reasons (e.g., inherent technical risks of current Machine Learning such as data shift in a non-stationary environment), engineering and management challenges (e.g., the need for highly skilled labor, high initial costs and project risks at a project management level), and socio-technical factors (e.g., need for risk-awareness in applying AI including human factors such as cognitive bias in AI-assisted decision making). In this context we consider the detection, monitoring and, if possible, the anticipation of risks at all levels of system engineering and application as a key factor. Instead of claiming a general solution to this problem our approach follows a bottom-up strategy by selecting typical pitfalls in a specific engineering and application context to come up with a repository of instructive self-contained “mini”-projects. Going beyond the state of the art we explore ways of risk anticipation and its integration into a recommender system that is able to give active support and guidance.
Tatsächlicher Beginn/ -es Ende1/01/2431/12/26


  • Wirtschaftsuniversität
  • AIT Austrian Institute of Technology GmbH (Leitung)
  • FH Burgenland
  • Fachhochschule Salzburg GmbH
  • Fachhochschule St. Pölten GmbH
  • FH Technikum Wien
  • Österreichische Akademie der Wissenschaften
  • Institut für Informationssysteme, Technische Universität Wien
  • Software Competence Center Hagenberg GmbH (SCCH)
  • Austria Wirtschaftsservice GmbH
  • Cloudflight
  • eutema GmbH
  • Semantic Web Company GmbH
  • Siemens Aktiengesellschaft Österreich
  • Women in AI
  • Vienna Data Science Group