Headline: Comparative, collaborative, and integrative risk governance for emerging technologies

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.

Wissenschaftliche Aufsätze

Linkov, I., Trump, B. D., Anklam, E., Berube, D., Boisseasu, P., Cummings, C., Ferson, S., Florin, M.-V., Goldstein, B., Hristozov, D., Jensen, K. A., Katalagarianakis, G., Kuzma, J., Lambert, J. H., Malloy, T., Malsch, I., Marcomini, A., Merad, M., Palma-Oliveira, J., Perkins, E., Renn, O., Seager, T., Stone, V., Vallero, D., & Vermeire, T. (2018). Comparative, collaborative, and integrative risk governance for emerging technologies. Environment Systems and Decisions, 38(2), 170-176. doi:10.1007/s10669-018-9686-5.

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