“Technology empowerment” means that innovation is increasingly accessible to ordinary people of limited means. As powerful technologies become more affordable and accessible, and as people are increasingly connected around the world, ordinary people are empowered to participate in the process of innovation and share the fruits of collaborative innovation. This annotated briefing describes technology empowerment and focuses on how empowerment may create challenges to U.S. national security. U.S. defense research as a share of global innovation has dwindled in recent years. With technology empowerment, the role of U.S. defense research is likely to shrink even further while technology empowerment will continue to increase the speed of innovation. To avoid falling too far behind potential technology threats to U.S. national security, U.S. national security institutions will need to adopt many of the tools of technology empowerment.
This report provides an overview of the scenarios used in strategic futures workshops conducted at Sandia on September 21 and 29, 2016. The workshops, designed and facilitated by analysts in Center 100, used scenarios to enable thought leaders to think collectively about the changing aspects of global nuclear security and the potential implications for the US Government and Sandia National Laboratories.
Decisions made to address climate change must start with an understanding of the risk of an uncertain future to human systems, which in turn means understanding both the consequence as well as the probability of a climate induced impact occurring. In other words, addressing climate change is an exercise in risk-informed policy making, which implies that there is no single correct answer or even a way to be certain about a single answer; the uncertainty in future climate conditions will always be present and must be taken as a working-condition for decision making. In order to better understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, this study estimates the impacts from responses to climate change on U.S. state- and national-level economic activity by employing a risk-assessment methodology for evaluating uncertain future climatic conditions. Using the results from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report (AR4) as a proxy for climate uncertainty, changes in hydrology over the next 40 years were mapped and then modeled to determine the physical consequences on economic activity and to perform a detailed 70-industry analysis of the economic impacts among the interacting lower-48 states. The analysis determines industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. The conclusions show that the average risk of damage to the U.S. economy from climate change is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Further analysis shows that an increase in uncertainty raises this risk. This paper will present the methodology behind the approach, a summary of the underlying models, as well as the path forward for improving the approach.
Sandia National Laboratories has developed several models to analyze potential consequences of homeland security incidents. Two of these models (the National Infrastructure Simulation and Analysis Center Agent-Based Laboratory for Economics, N-ABLE{trademark}, and Loki) simulate detailed facility- and product-level consequences of simulated disruptions to supply chains. Disruptions in supply chains are likely to reduce production of some commodities, which may reduce economic activity across many other types of supply chains throughout the national economy. The detailed nature of Sandia's models means that simulations are limited to specific supply chains in which detailed facility-level data has been collected, but policymakers are often concerned with the national-level economic impacts of supply-chain disruptions. A preliminary input-output methodology has been developed to estimate national-level economic impacts based upon the results of supply-chain-level simulations. This methodology overcomes two primary challenges. First, the methodology must be relatively simple to integrate successfully with existing models; it must be easily understood, easily applied to the supply-chain models without user intervention, and run quickly. The second challenge is more fundamental: the methodology must account for both upstream and downstream impacts that result from supply-chain disruptions. Input-output modeling typically estimates only upstream impacts, but shortages resulting from disruptions in many supply chains (for example, energy, communications, and chemicals) are likely to have large downstream impacts. In overcoming these challenges, the input-output methodology makes strong assumptions about technology and substitution. This paper concludes by applying the methodology to chemical supply chains.
In recent years, the nation has recognized that critical infrastructure protection should consider not only the prevention of disruptive events, but also the processes that infrastructure systems undergo to maintain functionality following disruptions. This more comprehensive approach has been termed critical infrastructure resilience. Given the occurrence of a particular disruptive event, the resilience of a system to that event is the system's ability to efficiently reduce both the magnitude and duration of the deviation from targeted system performance levels. Under the direction of the U. S. Department of Homeland Security's Science and Technology Directorate, Sandia National Laboratories has developed a comprehensive resilience assessment framework for evaluating the resilience of infrastructure and economic systems. The framework includes a quantitative methodology that measures resilience costs that result from a disruption to infrastructure function. The framework also includes a qualitative analysis methodology that assesses system characteristics affecting resilience to provide insight and direction for potential improvements. This paper describes the resilience assessment framework and demonstrates the utility of the assessment framework through application to two hypothetical scenarios involving the disruption of a petrochemical supply chain by hurricanes.
Pandemic influenza has become a serious global health concern; in response, governments around the world have allocated increasing funds to containment of public health threats from this disease. Pandemic influenza is also recognized to have serious economic implications, causing illness and absence that reduces worker productivity and economic output and, through mortality, robs nations of their most valuable assets - human resources. This paper reports two studies that investigate both the short- and long-term economic implications of a pandemic flu outbreak. Policy makers can use the growing number of economic impact estimates to decide how much to spend to combat the pandemic influenza outbreaks. Experts recognize that pandemic influenza has serious global economic implications. The illness causes absenteeism, reduced worker productivity, and therefore reduced economic output. This, combined with the associated mortality rate, robs nations of valuable human resources. Policy makers can use economic impact estimates to decide how much to spend to combat the pandemic influenza outbreaks. In this paper economists examine two studies which investigate both the short- and long-term economic implications of a pandemic influenza outbreak. Resulting policy implications are also discussed. The research uses the Regional Economic Modeling, Inc. (REMI) Policy Insight + Model. This model provides a dynamic, regional, North America Industrial Classification System (NAICS) industry-structured framework for forecasting. It is supported by a population dynamics model that is well-adapted to investigating macro-economic implications of pandemic influenza, including possible demand side effects. The studies reported in this paper exercise all of these capabilities.
While climate-change models have done a reasonable job of forecasting changes in global climate conditions over the past decades, recent data indicate that actual climate change may be much more severe. To better understand some of the potential economic impacts of these severe climate changes, Sandia economists estimated the impacts to the U.S. economy of climate change-induced impacts to U.S. precipitation over the 2010 to 2050 time period. The economists developed an impact methodology that converts changes in precipitation and water availability to changes in economic activity, and conducted simulations of economic impacts using a large-scale macroeconomic model of the U.S. economy.
This report gives an overview of the types of economic methodologies and models used by Sandia economists in their consequence analysis work for the National Infrastructure Simulation & Analysis Center and other DHS programs. It describes the three primary resolutions at which analysis is conducted (microeconomic, mesoeconomic, and macroeconomic), the tools used at these three levels (from data analysis to internally developed and publicly available tools), and how they are used individually and in concert with each other and other infrastructure tools.
The goal of the work discussed in this document is to understand the risk to the nation of cyber attacks on critical infrastructures. The large body of research results on cyber attacks against physical infrastructure vulnerabilities has not resulted in clear understanding of the cascading effects a cyber-caused disruption can have on critical national infrastructures and the ability of these affected infrastructures to deliver services. This document discusses current research and methodologies aimed at assessing the translation of a cyber-based effect into a physical disruption of infrastructure and thence into quantification of the economic consequences of the resultant disruption and damage. The document discusses the deficiencies of the existing methods in correlating cyber attacks with physical consequences. The document then outlines a research plan to correct those deficiencies. When completed, the research plan will result in a fully supported methodology to quantify the economic consequences of events that begin with cyber effects, cascade into other physical infrastructure impacts, and result in degradation of the critical infrastructure's ability to deliver services and products. This methodology enables quantification of the risks to national critical infrastructure of cyber threats. The work addresses the electric power sector as an example of how the methodology can be applied.