Suchergebnisse

Intro -- Disclaimer -- Acknowledgments -- Contents -- About the Editors -- Chapter 1: Biosecurity for Synthetic Biology and Emerging Biotechnologies: Critical Challenges for Governance -- 1.1 An Introduction to the Dual-Use Nature of Emerging Biotechnology -- 1.2 History -- 1.3 Effective Governance and Policy for Biosecurity -- 1.4 Conclusion -- References -- Chapter 2: Emerging Biosecurity Threats and Responses: A Review of Published and Gray Literature -- 2.1 Introduction -- 2.2 Methods -- 2.3 Results and Discussion -- 2.3.1 US and EU Governmental Frameworks -- 2.3.1.1 US Framework -- 2.3.1.2 EU Framework -- 2.3.2 Threats Identified in the Literature -- 2.3.3 Responses Identified in the Literature -- 2.4 Conclusion -- References -- Chapter 3: Opportunities, Challenges, and Future Considerations for Top-Down Governance for Biosecurity and Synthetic Biology -- 3.1 Introduction -- 3.2 Understanding the Scope and Limitations of Top-Down Governance for Biosecurity and Synthetic Biology -- 3.2.1 International Instruments for Biosecurity -- 3.2.1.1 Biological Weapons Convention (BWC) -- 3.2.1.2 Chemical Weapons Convention (CWC) -- 3.2.1.3 Australia Group, United Nations Security Council Resolution 1540 and Others -- 3.2.2 National Implementation -- 3.2.2.1 Hard Law vs. Soft Law -- 3.2.2.2 Biosafety vs. Biosecurity, GMOs vs. Synthetic Biology -- 3.2.2.3 National Implementation: An Inevitable Patchwork -- 3.3 Key Novelties and Tensions Introduced by Synthetic Biology -- 3.3.1 Convergence -- 3.3.2 Democratization -- 3.3.3 Intangibility -- 3.4 Conclusions and Recommendations -- References -- Chapter 4: Biological Standards and Biosecurity: The Unexplored Link -- 4.1 Standards in Biology -- 4.2 Implications of Standards in Biosecurity in Terms of Risks -- 4.3 Universality -- 4.4 Chassis and Trojan Horses -- 4.5 Breaking Down the Species Barrier.

AbstractTechnology innovation is inherently uncertain. The risk–benefit divide for such innovation is a classical debate within scholarly literature and is often framed on a monetary scale where innovation approval is granted if benefit outweighs risk. However, such discussion leaves out a critical yet subjective vein of discussion within the innovation evaluation process — stakeholder context. Specifically, regulators and technology developers are often described as having respective motivations that are often at odds with one another. In theory, efforts towards balancing risk and benefit for technology evaluation should be driven by relatively efficient, inexpensive, robust methods, and processes. In practice, however, technology evaluation is often expensive, slow, and often of questionable quality for new and emerging technologies. Literature often frames the innovation-regulation tradeoff as a zero-sum game driven by regulators and developers that are inherently at odds with one another. However, we argue that such a relationship is actually worse than zero-sum and is a classic framing problem as described by Kahneman and Tversky. Specifically, the divergent frames adopted by regulators and technology developers, respectively, can drastically affect their perception of risk and tolerance for further development and commercialization of a given technology. There are known and natural solutions to such problems that can smooth the path towards realizing the societal potential of emerging technologies.

Infrastructure development of volatile regions is a significant investment by international government and nongovernment organizations, with attendant requirements for risk management. Global development banks may be tasked to manage these investments and provide a channel between donors and borrowers. Moreover, various stakeholders from the private sector, local and international agencies, and the military can be engaged in conception, planning, and implementation of constituent projects. Emergent and future conditions of military conflict, politics, economics, technology, environment, behaviors, institutions, and society that stress infrastructure development are prevalent, and funding mechanisms are vulnerable to fraud, waste, and abuse. This article will apply resilience analytics with scenario‐based preferences to identify the stressors that most influence a prioritization of initiatives in the electric power sector of Afghanistan. The resilience in this article is conceived in terms of the degree of disruption of priorities when stressors influence the preferences of stakeholders, and ultimately a prioritization of initiatives. The ancillary results include an understanding of which initiatives contribute most and least across strategic criteria and which criteria have the most impact for the analysis. The article concludes with recommendations for risk monitoring and risk management of the portfolio of stressors through the life cycle and horizon of grid capacity expansion.

Due to persistent and serious threats from natural disasters around the globe, many have turned to resilience and vulnerability research to guide disaster preparation, recovery, and adaptation decisions. In response, scholars and practitioners have put forth a variety of disaster indices, based on quantifiable metrics, to gauge levels of resilience and vulnerability. However, few indices are empirically validated using observed disaster impacts and, as a result, it is often unclear which index should be preferred for each decision at hand. Thus, we compare and empirically validate five of the top U.S. disaster indices, including three resilience indices and two vulnerability indices. We use observed disaster losses, fatalities, and disaster declarations from the southeastern United States to empirically validate each index. We find that disaster indices, though thoughtfully substantiated by literature and theoretically persuasive, are not all created equal. While four of the five indices perform as predicted in explaining damages, only three explain fatalities and only two explain disaster declarations as expected by theory. These results highlight the need for disaster indices to clearly state index objectives and structure underlying metrics to support validation of the results based on these goals. Further, policymakers should use index results carefully when developing regional policy or investing in resilience and vulnerability improvement projects.

Recent severe storm experiences in the U.S. Gulf Coast illustrate the importance of an integrated approach to flood preparedness planning that harmonizes stakeholder and agency efforts. Risk management decisions that are informed by and address decision maker and stakeholder risk perceptions and behavior are essential for effective risk management policy. A literature review and two expert models/mental models studies were undertaken to identify areas of importance in the flood risk management process for layperson, non‐USACE‐expert, and two USACE‐expert groups. In characterizing and mapping stakeholder beliefs about risks in the literature onto current risk management practice, recommendations for accommodating and changing stakeholder perceptions of flood risks and their management are identified. Needs of the U.S. Army Corps of Engineers (USACE) flood preparedness and response program are discussed in the context of flood risk mental models.

AbstractDesirable system performance in the face of threats has been characterized by various management concepts. Through semistructured interviews with editors of journals in the fields of emergency response and systems management, a literature review, and professional judgment, we identified nine related and often interchangeably used system performance concepts: adaptability, agility, reliability, resilience, resistance, robustness, safety, security, and sustainability. A better understanding of these concepts will allow system planners to pursue management strategies best suited to their unique system dynamics and specific objectives of good performance. We analyze expert responses and review the linguistic definitions and mathematical framing of these concepts to understand their applications. We find a lack of consensus on their usage between interview subjects, but by using the mathematical framing to enrich the linguistic definitions, we formulate comparative visualizations and propose distinct definitions for the nine concepts. We present a conceptual framing to relate the concepts for management purposes.

AbstractRecent cyber attacks provide evidence of increased threats to our critical systems and infrastructure. A common reaction to a new threat is to harden the system by adding new rules and regulations. As federal and state governments request new procedures to follow, each of their organizations implements their own cyber defense strategies. This unintentionally increases time and effort that employees spend on training and policy implementation and decreases the time and latitude to perform critical job functions, thus raising overall levels of stress. People's performance under stress, coupled with an overabundance of information, results in even more vulnerabilities for adversaries to exploit. In this article, we embed a simple regulatory model that accounts for cybersecurity human factors and an organization's regulatory environment in a model of a corporate cyber network under attack. The resulting model demonstrates the effect of under‐ and overregulation on an organization's resilience with respect to insider threats. Currently, there is a tendency to usead‐hocapproaches to account for human factors rather than to incorporate them into cyber resilience modeling. It is clear that using a systematic approach utilizing behavioral science, which already exists in cyber resilience assessment, would provide a more holistic view for decisionmakers.

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi‐criteria decision analysis (MCDA) and life‐cycle assessment (LCA) results (LCA‐MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi‐attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary.

Background: The development of horizontal drilling and hydraulic fracturing methods has dramatically increased the potential for the extraction of previously unrecoverable natural gas. Nonetheless, the potential risks and hazards associated with such technologies are not without controversy and are compounded by frequently changing information and an uncertain landscape of international politics and laws. Where each nation has its own energy policies and laws, predicting how a state with natural gas reserves that require hydraulic fracturing will regulate the industry is of paramount importance for potential developers and extractors. We present a method for predicting hydraulic fracturing decisions using multiple-criteria decision analysis. The case study evaluates the decisions of five hypothetical countries with differing political, social, environmental, and economic priorities, choosing among four policy alternatives: open hydraulic fracturing, limited hydraulic fracturing, completely banned hydraulic fracturing, and a cap and trade program. Results: The result is a model that identifies the preferred policy alternative for each archetypal country and demonstrates the sensitivity the decision to particular metrics. Armed with such information, observers can predict each country's likely decisions related to natural gas exploration as more data become available or political situations change. Conclusions: Decision analysis provides a method to manage uncertainty and address forecasting concerns where rich and objective data may be lacking. For the case of hydraulic fracturing, the various political pressures and extreme uncertainty regarding the technology's risks and benefits serve as a prime platform to demonstrate how decision analysis can be used to predict future behaviors.