Socially Responsible AI for Distributed Autonomous Systems

This project aims to initiate a long-term collaboration and shape a solid ground for a new ambitious research area on socially-responsible robotic and autonomous systems.

These systems will be equipped with a new type of responsible distributed intelligence, aware of social values, promoting sustainability, privacy, fairness, social welfare and public good. (Inter)national research strategies highlight that RAS, including transport/aerial vehicles and smart cameras, will reach full societal and business potential when they can operate collectively with/without people. Since RAS will be pervasive in our society, social dilemmas
arise about the implications of their autonomy on well-being, environment, and democracy, i.e., implications of delegating collective decisions to RAS or risks of human nudging/manipulation.

Driven by these dilemmas and by adopting a responsible innovation approach, this project aspires to shed light on the following research challenges.

  • How can surveillance actions of self-organising smart cameras be self-regulated by citizens to balance security and privacy concerns?
  • How can coordinated vehicles optimising travel times of passengers also consider the environmental footprint of different urban areas?
  • Can AI-based algorithms and software be designed to fulfil social assurances, e.g., lower noise pollution?

Lead Academic at Lead University

Evangelos Pournaras, University of Leeds

Load Academics at other Universities

Simos Gerasimou University of York
Lyudmila Mihaylova University of Sheffield

Other Staff Associated with this Project 

Matteo Leonetti, School of Computing, University of Leeds
Jie Xu, School of Computing, University of Leeds
Zheng Wang, School of Computing, University of Leeds
Jonathan M. Aitken, Automatic Control and Systems Engineering, University of Sheffield
Roderich Groß, Automatic Control and Systems Engineering, University of Sheffield
Nicholas Matragkas, Department of Computer Science, University of York
Ibrahim Habli, Department of Computer Science, University of York




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