Project

The project proposes AI forensics as a new sociotechnical framework for the analysis and critique of AI systems. This implies the design and development of new AI forensics tools for the investigation of large AI datasets (that are impossible to analyze manually), models (reverse-engineering the black box effect), and applications (exposing their sociohistorical context), making state-of-the-art results from explainable and interactive machine learning accessible to researchers in the humanities and beyond. The resulting open source AI forensics toolkit is designed to be used by, and shared with civil organisations, academia and industry to study the social impact and implications of real-world AI systems. The AI forensics toolkit will also support four sociotechnical investigations that will examine the production pipeline of face recognition, interpretability and accountability of AI in the humanitarian sector, bias-aware design methods for AI systems, and the role of visual AI models in the sciences. Through a close integration of machine learning research and sociotechnical analysis, the project establishes a new and comprehensive methodological framework to equip the humanities and social sciences with the means to investigate the implications of 21st century artificial intelligence.

• Prof. Dr. Matteo Pasquinelli

  Staatliche Hochschule für Gestaltung
  Karlsruhe
  Forschungsgruppe für Künstliche Intelligenz und
  Medienphilosophie -- Medientheorie
  Karlsruhe
  

• Prof. Dr. Noura Al Moubayed

  Durham University
  Durham
  United Kingdom
  

• Prof. Dr. Claude Draude

  Universität Kassel
  FB 16: Elektrotechnik/Informatik
  Wissenschaftliches Zentrum für
  Informationstechnik-Gestaltung ITeG
  Kassel
  

• Prof. Dr. Fabian Offert

  University of California - Santa Barbara
  Department of Germanic and Slavic Studies
  Santa Barbara
  USA
  

• Prof. Dr. Leonardo Impett

  University of Cambridge
  The Faculty of English
  Cambrigde
  United Kingdom