Paul Bachmann 

Date/Time: 08.04.2026, 12:00 

Location: D2.2.094 

Abstract 

With the growing adoption of AI systems reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work on democratic control largely focuses on macro-level governance. In contrast we propose a new approach grounded in social choice theory which we term collective control of artificial intelligence. We argue that collective input can and should be incorporated at multiple points across the ML development pipeline from data collection through objective design to alignment. We further demonstrate that social choice provides a well-suited modelling language for the treatment of collective input across all stages and that its axiomatic methodology yields principled criteria for evaluating various control mechanisms. Overall our conceptual contribution provides a mathematically grounded framework to implement and analyse collective control of AI systems. 

Bio 

Paul Anton Bachmann is a Doctorate Student at Databases and Artificial Intelligence at TU Wien (Cluster of Excellence Bilateral AI), Supervisor: Prof. Stefan Woltran. Master’s and Bachelor’s degree in Informatics at TU Munich with a focus on formal methods and computational social choice.