Decision-making under deep uncertainty

DMDU practitioners employ a variety of descriptions for levels of certainty. As Donald Rumsfeld remarked, there are known unknowns (what we know we do not know) and unknown unknowns (what we do not know that we do not know). The Clean Air Task Force describes these levels as: Uncertainty that can be quantified or characterized by specific questions: • Level 1: Virtual certainty • Level 2: Alternate futures with probabilities • Level 3: Alterative futures with ranked possibilities Deep uncertainties: • Level 4: Multiple plausible futures (where possible outcomes are known, but their likelihood cannot be predicted) • Level 5: Unknown unknowns (where the full range of possible outcomes is unknown and the likelihood of any of these outcomes cannot be predicted). == Applications ==

DMDU methods can help develop plans when there is a wide range of unknown futures. These methods are widely applicable to many sectors. Climate scenario planning The Intergovernmental Panel on Climate Change (IPCC) has used DMDU concepts to examine risks and scenarios in multiple future storylines since the early 2000s. The Science Advisory Board for the National Oceanic and Atmospheric Administration (NOAA) recommended that NOAA use DMDU techniques in its strategic planning: "The benefits of DMDU techniques include systematic and deliberative exploration of possible futures for management applications that could reduce the potential for unanticipated and unintended consequences. Because DMDU techniques seek to identify 'low-regret' and/or robust solutions that are beneficial over a broad set of potential future situations, they have the potential to improve confidence that proposed policy and program actions are worthwhile." Transportation planning The RAND Corporation partnered with the Federal Emergency Management Agency to develop a guide for using DMDU in transportation planning. The Sacramento Area Council of Governments (SACOG) used DMDU in its 2016 Metropolitan Transportation Plan to stress test the plan against 10,000 modeled futures with different combination for gas prices, fuel efficiency, employment, zero emissions vehicles emissions, customer behavior, and vehicle miles traveled. Water Water conditions rely on temperature and precipitation patterns. DMDU provides a way to visualize how water operations could be optimized or could be used to avert water shortages and to handle droughts or floods. RAND partnered with the Bureau of Reclamation to develop case studies, including the Colorado River and the Pecos River. Energy Energy decisions involve many uncertainties including future climates (decarbonization pathways), technological advances, economic development; many stakeholders. Decisions must be made quickly as well as decisions to invest in long-term infrastructures. Therefore, DMDU analyses have proven useful in the energy sector. Community and urban planning == Initiatives and organizations ==

The Society for Decision Making Under Deep Uncertainty brings professionals together to improve DMDU tools and practices. DMDU conferences and workshops The Transportation Research Board hosted a DMDU Initiative meeting at its 2024 annual meeting to rename their planning initiative to DMDU. DMDU Society meetings include: • The 11th Annual Conference of the Society for Decision Making Under Deep Uncertainty (DMDU) took place November 19–21, 2024 and was hosted by University of Denver and the Bureau of Reclamation. • 2020 online (Hosted by Tecnológico de Monterrey) • 2019 in Delft • 2018 in Southern California • 2017 in Oxford • 2016 in Washington, D.C. • 2015 in Delft • 2014 in Santa Monica • 2013 in Washington, D.C. == See also ==