By Tania Lopez-Cantu
Throughout progress in scientific discovery and technological advancement, engineers and scientists have learned how to approach modeling of a specific physical phenomena bounded by a set of unknown but well-defined rules or choosing the best alternative out of a constrained set of possible alternatives. Under these and similar circumstances, we can apply different techniques that we have successfully applied in the past: the scientific method, statistical analysis, mathematical programming, and others. However, it is not always the case that we know with confidence and in advance the distribution of values for a given variable, their interactions with other variables, or if we are modeling a system that evolves with time, the specific outcome of variables that change over time in the modeled system. This gets even more challenging when experts can’t agree on the likely distribution of values, and when the outcomes of these modeled problems are very important to societal decision-making. All of these of these unknowns create “deep uncertainty”. In this case, many of the techniques that we are used to applying are no longer valid, but fortunately, there exist methodologies and tools within the Decision Making Under Deep Uncertainty framework that we can apply when we face deep uncertainty.
In recent years, many researchers have explored the application of DMDU methodologies and tools to complex problems with deep uncertainty, from river basin planning to the adoption of electric vehicles, among others. However, the practical application of DMDU still poses great challenges. For example, the treatment of uncertainty, the specification of the interactions between organizations and individuals, experts, stakeholders, and the public sector, the technical interactions in systems models, and other challenges related to the definition of policy and technical options, etc. Therefore, it is critical to understand what kind of challenges arise when applying DMDU methodologies and how to overcome them.
In the upcoming annual meeting, experts across the world will present their work applying DMDU approaches, highlighting the specific challenges they faced during this process in the session “Practical challenges in the applications of DMDU”.
In this session, Joseph Guillaume and colleagues will present a framework for improving uncertainty management in practice. M.S. Wisz, R. Kelly, and A. Polejack will present an application of robust decision-making on the potential governance and harvest of deep-sea rich marine ecosystems. Paola Gómez-Priego and Luis Bojórquez-Tapia will discuss how the determination of impact significance of environmental impact assessments between experts, decision-makers, and public participants can shape their success and propose to address the discovery of impact significance through an analytic deliberation based on DMDU approaches. Finally, Josué Morales Sandoval will present an application of DMDU to the Mexican economy network structure. We hope that you will join us in this discussion.
About this Blog Post:
This blog post is part of a series of posts contributed by the chairs of the 2020 DMDU Annual Meeting. For more information about the Annual Meeting, including registration, visit our website at 2020.deepuncertainty.org. We hope to (virtually) see you soon!