Risk Science Contributions: Three Illustrating Examples

Abstract

This article aims to demonstrate that risk science is important for society, industry and all of us. Rather few people today, including scientists and managers, are familiar with what this science is about-its foundation and main features-and how it is used to gain knowledge and improve communication and decision making in real-life situations. The article seeks to meet this challenge, by presenting three examples, showing how risk science works to gain new generic, fundamental knowledge on risk concepts, principles, and methods, as well as supporting the practical tackling of actual risk problems.

Increasing Preparedness for Extreme Events using Plausibility‐Based Scenario Planning: Lessons from COVID‐19

“…Conversely however, a type II precautionary error (Aven, 2020) would occur where a strict quarantine is not implemented because the focal virus is not deemed a threat, but is then proven to have been necessary because the virus spreads causing great harm. Here, the gains from the decision not to implement a strict quarantine being proven correct are minimal in terms of continued business-as-usual.…”

“…Plausibility-based scenario planning, because of its theoretical foundations in PST (Derbyshire, 2017), would place the focus squarely on these focal gains and losses and by doing so would emphasize the avoidance of a type II precautionary error. A type I precautionary error emphasizes the costs of erroneously taken precautionary measures, whereas a type II precautionary error emphasizes the costs of an erroneous lack of precautionary measures (Aven, 2020). While there is no "scientifically optimal formula" (Aven, 2020(Aven, , p. 1892 for making such a decision, where there is danger of exponentially increasing harm, the payoffs to alternative actions described above clearly favor avoiding a type II precautionary error, as Norman, Bar-Yam, and Taleb (2020) have emphasized.…”

“…A type I precautionary error emphasizes the costs of erroneously taken precautionary measures, whereas a type II precautionary error emphasizes the costs of an erroneous lack of precautionary measures (Aven, 2020). While there is no "scientifically optimal formula" (Aven, 2020(Aven, , p. 1892 for making such a decision, where there is danger of exponentially increasing harm, the payoffs to alternative actions described above clearly favor avoiding a type II precautionary error, as Norman, Bar-Yam, and Taleb (2020) have emphasized. Plausibility-based scenario planning places the emphasis on avoidance of type II precautionary errors.…”

“…It also discusses, for the first time in any forum, the role of plausibility-based scenario planning in precautionary decision making. In so doing, the article contributes to what Aven (2020Aven ( , p. 1889) calls "type B," "generic and fundamental" risk science, which is concerned with identifying better ways to present and communicate uncertainties.…”

Adapting risk assessments for a complex future

“…However, it is a concept with many different and diverging meanings. While this diversity of definitions and assessment approaches is explicitly discussed within risk science, [10][11][12] it has not been widely acknowledged in sustainability science. This is unfortunate, since sustainability challenges are generally complex and multidimensional and would benefit from the different strengths of multiple disciplinary approaches to risk that exist.…”