Tecnológico de Monterrey and RAND Corporation researchers help develop an adaptive water management strategy for Mexico's third-largest metropolitan area, Monterrey, using RAND's Robust Decision Making (RDM) methods.
This interactive tool allows users to explore data and analysis developed by the RAND Corporation and Tecnológico de Monterrey in support of Fondo de Agua Metropolitano de Monterrey's Monterrey Water Plan for 2050.
Expert peer review is considered the gold standard for assessing the validity, significance and originality of research. When it comes to grant applications, however, peer review is not without its shortcomings. Addressing some of the challenges that peer review poses could ensure that the best research receives the financial support it deserves.
Social institutions increasingly use algorithms for decisionmaking purposes. How do different perspectives on equity or fairness inform the use of algorithms in the context of auto insurance pricing, job recruitment, and criminal justice?
This report summarizes a 2018 workshop that gathered a small group of innovative thinkers to engage in an approach called large-scale speculative design to sketch desirable future worlds that could be enabled by artificial intelligence.
This study used the RUAM to determine the appropriateness of spinal mobilization and manipulation for different types of patients with CLBP, and the key patient characteristics associated with appropriateness.
This study evaluates the performance of Lima, Peru's current drought management plan against future droughts and proposes augmentations, and it recommends ways to ensure that the drought management plan performs will in the uncertain future.
This report provides an inventory of U.S. Department of Homeland Security (DHS) analytic capabilities in the including current capabilities in use for decisionmaking, as DHS establishes an Analytic Agenda.
Decisionmakers often seek predictions about the future to inform policy choices. But a reliance upon analytic methods that require them can prove counter-productive and sometimes dangerous in a fast-changing, complex world.
In this report, RAND researchers use a structured comparison game to examine the value proposition of different analytic inputs (scenario-based versus Robust Decision Making) on a sample U.S. Department of Defense decision about force structure.
This essay explores how AI might be used to enable fundamentally different future worlds and how one such future might be enabled by AI algorithms with different goals and functions than those most common today.
Policy decisions are increasingly informed (or expected to be informed) by research evidence. Making the process as systematic, transparent and explicit as possible provides users with ways to understand, question and contribute to the eventual policy recommendation, and gives policymakers and practitioners confidence in its credibility.