chanceinformed
Chanceinformed is a decision-support perspective that treats probabilistic knowledge as a central input to planning and policy. It frames uncertainty not merely as a risk to be mitigated but as information that can guide choices, with emphasis on how likelihoods, distributions, and stochastic dynamics shape expected outcomes.
Core concepts of chanceinformed include probabilistic modeling of uncertainty, iterative learning, and the use of simulations
Applications of chanceinformed analysis span public policy, finance, engineering, healthcare, and environmental management. Chanceinformed analysis supports
Relation to related ideas: it complements risk-informed approaches by foregrounding how information accrues from random processes;
Limitations and challenges include data requirements for reliable probability estimates, computational demands for complex models, and