SDP Public Curated Content

Persistent misinformation poses serious challenges to risk communication, public understanding, and effective coordinated decision-making. Traditional models of misinformation spread such as informational cascades, opinion dynamics, and Social Amplification of Risk frameworks help explain how beliefs propagate through social systems. However, they do not explain why locally reasonable beliefs can still fail to produce a coherent and accurate shared understanding of risk.

This webinar introduces a new perspective based on sheaf theory, a branch of applied mathematics concerned with how local pieces of information can (or cannot) be consistently integrated into global structures. The presentation will suggest how sheaf-theoretic tools can be used to diagnose and help repair failures in risk communication systems, including information silos, echo chambers, semantic misalignment, and fragile consensus generated by informational cascades.

Using examples drawn from public health, environmental risk communication, and networked decision systems, the webinar will illustrate how misinformation can arise not only from false content or irrational behavior, but also from inconsistencies in how beliefs are translated, filtered, and combined across organizations and social networks. The discussion will introduce concepts such as global coherence, restriction maps, and cohomological obstructions in intuitive, application-oriented terms accessible to decision analysts and risk professionals.

The webinar will also discuss practical implications for improving risk communication, including trust-based bridge agents, semantic alignment strategies, and network interventions designed to improve the coherence and resilience of distributed decision systems. The overall aim is to show how mathematical tools developed for information integration can help support more reliable collective understanding and better-coordinated risk management decisions.