A Voting-Based System for Ethical Decision Making

We present a general approach to automating ethical decisions, drawing on machine learning and computational social choice. In a nutshell, we propose to learn a model of societal preferences, and, when faced with a specific ethical dilemma at runtime, efficiently aggregate those preferences to identify a desirable choice. We provide a concrete algorithm that instantiates our approach; some of its crucial steps are informed by a new theory of swap-dominance efficient voting rules. Finally, we implement and evaluate a system for ethical decision making in the autonomous vehicle domain, using preference data collected from 1. 3 million people through the Moral Machine website.

Authors

• Ritesh Noothigattu
• Snehalkumar Gaikwad
• Edmond Awad
• Sohan Dsouza
• Iyad Rahwan Center for Humans and Machines, Max-Planck Institute for Human Development
• Pradeep Ravikumar
• Ariel Procaccia

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