RDMlab Research

The focus of RDMlab is not just on applying RDM to a wide range of disciplines and problems, but on developing RDM to meet the increasing needs of policymakers to help make decisions in conditions of deep uncertainty. In this section we present examples of research into developing RDM and applying it, as well as publications that showcase RDM.

Featured Publications

  • Business decision making concept, photo by mantinov/AdobeStock

    Engaging Multiple Worldviews With Quantitative Decision Support

    Many of today's pressing policy challenges—such as climate change and inequality—are characterized as wicked problems. How might decision making under deep uncertainty be used to demonstrate methods that may help resolve the tension between differing approaches for addressing these problems?

  •  BiCity life with eco transportation, photo by Golden Sikorka/AdobeStock

    Sacramento Area Council of Governments Peer Review

    The Southern California Association of Governments held a peer review to promote information exchange in the transportation planning and modeling community. The primary objective of the peer review was to help agencies understand the use of models to better manage uncertainties in long-range planning.

  • Intelligent robot cyborg using digital globe interface 3D rendering, photo by sdecoret/Adobe Stock

    A World-Building Workshop on the Future of Artificial Intelligence

    How might artificial intelligence (AI) be used to shape a new world? A workshop engaged a group of innovative thinkers in an approach called large-scale speculative design to sketch desirable, AI-enabled future worlds.

  • Melting icebergs by the coast of Greenland

    Deep Decarbonization as a Risk Management Challenge

    Deep decarbonization is the idea of reducing net human greenhouse gas emissions to zero in the 21st century. There are three concepts that help explain the full scope of deep decarbonization as a risk management challenge.

All Publications