Carter C. Price - Profile (2024)

Carter C. Price (he/him) is the research quality assurance manager for the Homeland Security Research Division, and a senior mathematician at RAND. He was previously co-director of RAND's Center for Scalable Computing and Analysis. Some of his major projects include work on the COMPARE microsimulation model to study the impact of health care reform, assessments of terrorism risk models, analyses of defense budgets, and studies of acquisition policies. He has also studied predictive policing and assessments of forest fire fighting capabilities. His project leadership experience includes studies of the macroeconomic impact of the Affordable Care Act on states, issues related to immigration fraud, trends in economic inequality, and analytic support for the Commonwealth of Virginia on COVID-19. Price has submitted testimony to the U.S. Congress and testified in front of state legislatures. His work has appeared in the Washington Post, CNN, USA Today, and the New Republic. He has a Ph.D. in applied mathematics from the University of Maryland, College Park, and a B.A. in mathematics and physics from Hendrix College.

Education

Ph.D. in applied mathematics, University of Maryland; M.S. in applied mathematics, University of Maryland; B.A. in mathematics and physics, Hendrix College

Authored by Carter C. Price

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Multimedia Aug 16, 2024 Artificial Intelligence and Homeland Security: How AI Impacts the Homeland Security Enterprise A panel of experts from RAND's Homeland Security Research Division examined the impact of artificial intelligence on the Department of Homeland Security and the homeland security enterprise more broadly.
Commentary Jan 29, 2024 Demystifying the Wealth Gap to Inform Military Talent Management Decisions This publication provides Department of the Air Force leaders and policymakers with an interdisciplinary framework to better see and understand the wealth gap when considering potential candidates from groups with historic disparities.
Commentary Jan 12, 2024 Policymaking Needs to Get Ahead of Artificial Intelligence President Biden's executive order on AI is a key step toward a regulatory regime that protects against AI's possible perils while balancing its potential. But more policies are needed—especially when it comes to security issues.
Report Sep 27, 2023 The Budgetary Effects of Climate Change and Their Potential Influence on Legislation: Recommendations for a Model of the Federal Budget The authors examine the ways that climate change and climate change mitigation policy affect the federal budget, recommend ways to improve the modeling of such effects, and provide an overview of a budget model that can be used to score legislation.
Commentary Jul 11, 2023 Tackling the Existential Threats from Artificial Intelligence Addressing potential risks posed by artificial intelligence (AI) could begin with simple steps like finding appropriate risk-management approaches, conducting research to determine how AI can better meet designers' intent, and devising responses to issues related to racism, sexism, and other biases within AI systems.
Commentary Jun 20, 2023 How Should the U.S. Government Buy AI Tools? The need for AI-readiness in federal procurement will continue to grow with the capabilities of AI tools. There are concrete steps the government could take to ensure all development and implementation of AI-related laws, regulations, and executive branch policies include appropriate considerations.
Commentary May 8, 2023 ChatGPT's Work Lacks Transparency and That Is a Problem In a world with Large Language Models such as ChatGPT, there is a growing need for modernized data literacy. Developers need to be more transparent about their algorithms and data sources so that people can assess the inherent sources of bias or problems with the approach.
Report Jun 24, 2022 Streamlining Emergency Management: Issues, Impacts, and Options for Improvement Researchers sought ways to streamline, simplify, and strengthen the U.S. emergency management system, assessing how overlap, duplication, and fragmentation could affect implementation and outcomes. They propose options and discuss trade-offs of each.
Report Nov 12, 2021 Temporary Safety-Net Policies and Pandemic-Related Insurance Loss in New York State Researchers assess the importance of temporary provisions relative to long-standing policies in stabilizing health insurance enrollment in New York state despite heavy job loss during the coronavirus disease 2019 pandemic.
Research Brief Apr 29, 2021 A New Approach to Measuring Income Inequality Over Recent Decades RAND researchers identified a new, intuitive way to measure income inequality and compare income growth over time.
Research Brief Feb 25, 2021 10Plan, How Would It Affect Health Care Spending by Consumers and the Federal Government The 10Plan is a self-pay plan for individuals currently uninsured or covered by a private nongroup health insurance plan. The authors built a microsimulation model to estimate health care spending under both the status quo and the 10Plan.
Report Jan 25, 2021 Analysis of the 10Plan: A Self-Pay System Designed to Minimize the Burden of Health Care Costs The 10Plan is a self-pay plan for individuals currently uninsured or covered by a private nongroup health insurance plan. The authors built a microsimulation model to estimate health care spending under both the status quo and the 10Plan.