Extending Analysis of Current and Future Catastrophic Risks from Emerging-Threat Technologies

Principal Investigator: 
Performance Period: 
July 2014 to June 2015
Commercialization Status: 
N/A
Abstract: 
In this project, we further develop a methodology for analyzing risks and risk-management tradeoffs of potential emerging threats by systematically identifying potential catastrophe-enabling developments and indicators of precursor events; estimating probabilities of facing precursors; assessing tradeoffs of available options; and continually monitoring for potential indicators of catastrophe precursors and updating probability estimates with new information and new judgments.  The approach employs fault trees, event trees, expert elicitation, decision analysis, and Bayesian methods to allow updating of estimates using new information.  The methodology is designed for implementation by risk practitioners.  We apply this methodology to an illustrative example in a potential emerging-threat technology area: the use of synthetic biology to produce bio-weapon agents.  While some methodology components have been applied in terrorism or technology-development assessments, to the best of our knowledge, they have not previously been developed into a single integrated methodology, nor has such a methodology been applied to real-world emerging-threat problems.   The DHS end customer, NBIC, has indicated that our project would enhance their ongoing efforts to create and implement a risk-based framework for biosurveillance by helping them to systematically focus on key risk indicators.  This project’s methodology components for analyzing tradeoffs of risk management options, such as intelligence resource allocations, is intended to support prioritization of NBIC’s biosurveillance activities and associated DHS risk-reduction options.  The methodology application case scenario sets involve use of emerging risks and synthetic biology technologies, which NBIC indicated they are interested in.    The methodology and/or information from the application case are intended to be useful to other potential end customers besides NBIC (e.g. to inform medical countermeasure acquisition decisions, which are made by agencies other than NBIC).  Other potential users include the DHS Office of Policy’s Strategy, Planning, Analysis and Risk (SPAR) unit, the DHS Bio & Chem Division, the DHS S&T Emerging Threats Branch, and members of the Intelligence Community (including the FBI, which already has some engagement with synthetic-biology communities).   In the first year of work, we developed and prototyped a basic methodology for analyzing risks and risk-management tradeoffs of potential emerging threats by systematically identifying potential catastrophe-enabling developments and indicators of precursor events; estimating probabilities of facing precursors; assessing tradeoffs of available options; and continually monitoring for potential indicators of catastrophe precursors and updating probability estimates with new information and new judgments.  While some methodology components have been applied in terrorism or technology-development assessments, to the best of our knowledge, they have not been developed into a single integrated methodology for use by risk practitioners, nor has such a methodology been applied to real-world emerging-threat problems.    In this second year of work, we further apply the first-year project methodology to a potential emerging-threat technology area: synthetic biology to produce bio-weapon agents.  This second year of work has value in terms of both methodology extension and application-case improvement.  Items intended to better develop an operationally-useful application case include further stakeholder engagement, further use of expert elicitation, and more extensive gathering of relevant information from literature.  Methodological extensions include increased use of empirical technology-development information from the literature to evaluate both present and past technology-development projections, to help produce more accurate and more useful technology development projections.