Linkov Igor, Trump Benjamin D, Anklam Elke, Berube David, Boisseasu Patrick, Cummings Christopher, Ferson Scott, Florin Marie-Valentine, Goldstein Bernard, Hristozov Danail, Jensen Keld Alstrup, Katalagarianakis Georgios, Kuzma Jennifer, Lambert James H, Malloy Timothy, Malsch Ineke, Marcomini Antonio, Merad Myriam, Palma-Oliveira José, Perkins Edward, Renn Ortwin, Seager Thomas, Stone Vicki, Vallero Daniel, Vermeire Theo
Risk & Decision Science Team, Environmental Risk Assessment Branch, US Army Engineer Research and Development Center, 696 Virginia Road, Concord, MA 01742, USA.
European Commission, Joint Research Centre, Antwerp, Belgium.
Environ Syst Decis. 2018 May 4;38(2):170-176. doi: 10.1007/s10669-018-9686-5.
Various emerging technologies challenge existing governance processes to identify, assess, and manage risk. Though the existing risk-based paradigm has been essential for assessment of many chemical, biological, radiological, and nuclear technologies, a complementary approach may be warranted for the early-stage assessment and management challenges of high uncertainty technologies ranging from nanotechnology to synthetic biology to artificial intelligence, among many others. This paper argues for a risk governance approach that integrates quantitative experimental information alongside qualitative expert insight to characterize and balance the risks, benefits, costs, and societal implications of emerging technologies. Various articles in scholarly literature have highlighted differing points of how to address technological uncertainty, and this article builds upon such knowledge to explain how an emerging technology risk governance process should be driven by a multi-stakeholder effort, incorporate various disparate sources of information, review various endpoints and outcomes, and comparatively assess emerging technology performance against existing conventional products in a given application area. At least in the early stages of development when quantitative data for risk assessment remain incomplete or limited, such an approach can be valuable for policymakers and decision makers to evaluate the impact that such technologies may have upon human and environmental health.
各种新兴技术对现有的治理流程提出了挑战，要求其识别、评估和管理风险。尽管现有的基于风险的范式对于评估许多化学、生物、放射和核技术至关重要，但对于从纳米技术到合成生物学再到人工智能等众多高不确定性技术的早期评估和管理挑战，可能需要一种补充方法。本文主张采用一种风险治理方法，将定量实验信息与定性专家见解相结合，以描述和平衡新兴技术的风险、益处、成本和社会影响。学术文献中的各种文章强调了应对技术不确定性的不同观点，本文基于这些知识来解释新兴技术风险治理过程应如何由多方利益相关者共同推动，纳入各种不同的信息来源，审查各种终点和结果，并在给定应用领域中将新兴技术的性能与现有传统产品进行比较评估。至少在开发的早期阶段，当风险评估的定量数据仍然不完整或有限时，这种方法对于政策制定者和决策者评估此类技术可能对人类和环境健康产生的影响具有重要价值。
