Forecasting Emergent Phenomena with Human Computer Collaboration
Abstract
Our ultimate goal of this research is to utilize data crowd-sourced from the experts to gain a quantitative model of the state of global risk networks that may provide some actionable insights for the U.S. government and the U.S. Army. The global risk network by definition is composed of risks of varying complexity, potential economical damage, and probability of activating. Hence, the need for risk mitigation processes may vary from difficult to extremely complicated for various risks and impose various costs. The risk activation probabilities constantly evolve. Accordingly, our quantification of the activation probabilities and their impacts could provide a timely and invaluable guide to any cost-benefit analysis involved in the design of policies or strategies aimed at global risk minimization. The insights provided by our model may also enable the domain experts to provide tailor-made recommendations for the pertinent risks to curb the likelihood of systemic failures. The effects of such recommendations can also be tested using our model. Accordingly, the final contribution of the research is to provide insights for the current state of the risks, guidance for curbing the probability of global failures and the tool for evaluating the proposed solutions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 18, 2021
- Accession Number
- AD1203891
Entities
People
- Boleslaw Szymanski
Organizations
- Rensselaer Polytechnic Institute