Institute for Advanced Sustainability Studies (IASS), Potsdam, Germany.
Arizona State University, Phoenix, AZ, USA.
Risk Anal. 2022 Sep;42(9):1902-1920. doi: 10.1111/risa.13657. Epub 2020 Dec 16.
Systemic risks are characterized by high complexity, multiple uncertainties, major ambiguities, and transgressive effects on other systems outside of the system of origin. Due to these characteristics, systemic risks are overextending established risk management and create new, unsolved challenges for policymaking in risk assessment and risk governance. Their negative effects are often pervasive, impacting fields beyond the obvious primary areas of harm. This article addresses these challenges of systemic risks from different disciplinary and sectorial perspectives. It highlights the special contributions of these perspectives and approaches and provides a synthesis for an interdisciplinary understanding of systemic risks and effective governance. The main argument is that understanding systemic risks and providing good governance advice relies on an approach that integrates novel modeling tools from complexity sciences with empirical data from observations, experiments, or simulations and evidence-based insights about social and cultural response patterns revealed by quantitative (e.g., surveys) or qualitative (e.g., participatory appraisals) investigations. Systemic risks cannot be easily characterized by single numerical estimations but can be assessed by using multiple indicators and including several dynamic gradients that can be aggregated into diverse but coherent scenarios. Lastly, governance of systemic risks requires interdisciplinary and cross-sectoral cooperation, a close monitoring system, and the engagement of scientists, regulators, and stakeholders to be effective as well as socially acceptable.
系统性风险的特点是高度复杂性、多重不确定性、重大模糊性以及对起源系统以外的其他系统的越界影响。由于这些特征，系统性风险超越了既定的风险管理范围，给风险评估和风险治理的政策制定带来了新的、未解决的挑战。其负面影响往往普遍存在，影响到明显的主要伤害领域以外的领域。本文从不同的学科和部门角度探讨了系统性风险的这些挑战。它强调了这些观点和方法的特殊贡献，并为系统风险的跨学科理解和有效治理提供了综合。主要观点是，理解系统性风险并提供良好的治理建议依赖于一种方法，该方法将复杂性科学的新颖建模工具与观察、实验或模拟的经验数据以及关于社会和文化反应模式的循证见解（通过定量方法揭示，例如调查）或定性方法（例如，参与性评估）相结合。系统性风险不能仅通过单个数值估计来轻易描述，而是可以通过使用多个指标并包括几个可以汇总到不同但一致的情景中的动态梯度来评估。最后，系统性风险的治理需要跨学科和跨部门的合作、密切的监测系统以及科学家、监管机构和利益相关者的参与，以确保其有效且为社会所接受。
