Ethical public Robots & AI
Advancements in digitization, computing, robotics, and AI have enabled technological innovation on an unprecedented scale, including in public and commercial services. Decisions about how and when automated systems should replace or supplement existing services are driven by technological advancements rather than the demands of society. Involving citizens in the societal debate and decision-making processes regarding automated services would increase public oversight and adoption. To this end, EPURAI seeks to bring together theoretical and empirical perspectives on how citizens can participate in automated service design processes (co-engineering) and policy development (co-governance). We have focus on how individual behavior is shaped in interaction with AI and robotics and how the public can be involved in developing rules and regulations for deploying intelligent systems and robots in the context of public and commercial services.
Theoretical contributions are derived from a broad range of formalisms, including game theory, decision theory, and social choice theory. Empirical approaches include laboratory experiments, field experiments on interactions between human subjects and robots and AI, agent-based modeling, mass surveys, and observational data.
We hold workshops, organize seminars, and facilitate collaborations between researchers and practitioners. We provide a forum for people from diverse scientific fields, including administrative sciences, computer science, economics, management, mechanical engineering, and psychology, as well as practitioners from the industry, governmental, and non-governmental institutions.
Specific topics include:
Human-AI interaction and strategic decision-making
Social preferences and AI
Ethics of algorithmic and robotic services
Transparency, Explainability, Interpretability
Fairness
Autonomy and control
Equity, Inequality
Bias and discrimination
Privacy and surveillance
Co-engineering processes
Co-governance and policy-making
Our efforts are currently financed by ANR and CNRS in France.
Institutional support received from SKEMA Business School, Université Paris-Dauphine, University of Cincinnati, WU Vienna.