Bridging Distribution Shift and AI Safety: Conceptual and Methodological Synergies

This paper presents a comprehensive analysis of the synergies between distribution shift and AI safety, establishing two key connections: methods for addressing specific types of distribution shifts can aid in achieving related safety goals, and some shifts and safety issues can be formally reduced to one another, allowing for mutual adaptation of methodologies. This unified perspective promotes deeper integration of research efforts in both areas, which is crucial for practitioners aiming to enhance the robustness and safety of AI systems in the face of distributional changes.