We investigate the regional economic consequences of a hypothetical catastrophic event-attack via radiological dispersal device (RDD)-centered on the downtown Los Angeles area. We distinguish two routes via which such an event might affect regional economic activity: (i) reduction in effective resource supply (the resource loss effect) and (ii) shifts in the perceptions of economic agents (the behavioral effect). The resource loss effect relates to the physical destructiveness of the event, while the behavioral effect relates to changes in fear and risk perception. Both affect the size of the regional economy. RDD detonation causes little capital damage and few casualties, but generates substantial short-run resource loss via business interruption. Changes in fear and risk perception increase the supply cost of resources to the affected region, while simultaneously reducing demand for goods produced in the region. We use results from a nationwide survey, tailored to our RDD scenario, to inform our model values for behavioral effects. Survey results, supplemented by findings from previous research on stigmatized asset values, suggest that in the region affected by the RDD, households may require higher wages, investors may require higher returns, and customers may require price discounts. We show that because behavioral effects may have lingering long-term deleterious impacts on both the supply-cost of resources to a region and willingness to pay for regional output, they can generate changes in regional gross domestic product (GDP) much greater than those generated by resource loss effects. Implications for policies that have the potential to mitigate these effects are discussed.

This article develops a mathematical modeling framework using fault trees and Poisson processes for analyzing the risks of inadvertent nuclear war from U.S. or Russian misinterpretation of false alarms in early warning systems, and for assessing the potential value of options to reduce the risks of inadvertent nuclear war. The model also uses publicly available information on early warning systems, near-miss incidents, and other factors to estimate probabilities of a U.S.-Russia crisis, the rates of false alarms, and the probabilities that leaders will launch missiles in response to a false alarm.

We develop and apply an integrated modeling system to estimate fatalities from intentional release of 17 tons of chlorine from a tank truck in a generic urban area. A public response model specifies locations and actions of the populace. A chemical source term model predicts initial characteristics of the chlorine vapor and aerosol cloud. An atmospheric dispersion model predicts cloud spreading and movement. A building air exchange model simulates movement of chlorine from outdoors into buildings at each location. A dose-response model translates chlorine exposures into predicted fatalities. Important parameters outside defender control include wind speed, atmospheric stability class, amount of chlorine released, and dose-response model parameters. Without fast and effective defense response, with 2.5 m/sec wind and stability class F, we estimate approximately 4,000 (half within ∼10 minutes) to 30,000 fatalities (half within ∼20 minutes), depending on dose-response model. Although we assume 7% of the population was outdoors, they represent 60-90% of fatalities. Changing weather conditions result in approximately 50-90% lower total fatalities. Measures such as sheltering in place, evacuation, and use of security barriers and cryogenic storage can reduce fatalities, sometimes by 50% or more, depending on response speed and other factors.

An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe. ARTICLE HISTORY

A chlorine tank truck attack could cause thousands of fatalities. As a means of preventing chlorine truck attacks, I consider the on-site generation of chlorine or hypochlorite at all U.S. facilities currently receiving chlorine by truck. I develop and apply mathematical models to estimate the amount of chlorine shipped by truck in the United States and the cost of generating chlorine at each facility. I then calculate system costs, as well as cost effectiveness in terms of expected cost per death avoided. The median estimated amount of chlorine trucked in the United States is 500 thousand tons/year, with 80% going to water and wastewater treatment. The median net cost of on-site generation totals $800 million/year for the United States as a whole. On-site generation would pass a cost-effectiveness test requiring median estimated cost per death averted to be $6.5 million or less if the investment reduces the annual probability of a chlorine truck attack in the United States by at least 0.03, depending on the chlorine attack simulation dose–response model and other factors. The expected value of the reduction of fatality risk from truck accidents causing chlorine releases would be $8 million per year, too low for cost effectiveness if that is the only benefit of on-site chlorine generation.