Program

Please find the workshop program here.

Topics

• traditional or computational social choice that might be relevant in the AI context

• aspects of AI that might profit from some form of collective decision making

• concrete applications of social choice methods in AI.  

Examples of topics at the intersection of social choice theory and AI ethics/safety include, but are not limited to, the following:

• Reinforcement Learning from Collective Human Feedback or multiple teachers

• Social Choice Rules for higher-level steering of AI systems and Scalable Oversight

• Democratic Inputs to AI, Constitutional AI, Iterated Amplification, Debate, Recursive Reward Modeling, etc. 

• Mechanism Design for Human-AI/AI-AI cooperation, Human-Compatible AI, corrigibility

• Formal representation of values, ethical principles, legal concepts, and possibly incomplete or conflicting preferences

• Standardization vs individualization, cooperation vs competition

• Individual and collective decision theories under risk, uncertainty, and ambiguity

• Scalable software tools for eliciting preferences and collective choice