Anticipating the Risks and Benefits of Counterfactual World Simulation Models (Extended Abstract)

This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs.