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A Frequency/Consequence‐based Technique for Visualizing and Communicating Uncertainty and Perception of Risk
Author(s) -
Slavin David,
Troy Tucker W.,
Ferson Scott
Publication year - 2008
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1399.008
Subject(s) - harm , ordinal scale , risk perception , hazard , scale (ratio) , risk assessment , computer science , perception , risk management , measurement uncertainty , multiple exposure , risk analysis (engineering) , psychology , data mining , statistics , artificial intelligence , social psychology , mathematics , medicine , geography , computer security , cartography , chemistry , organic chemistry , neuroscience , management , economics
This chapter presents an approach under development for communicating uncertainty regarding risk. The approach relies on a risk imaging technology that decomposes risk into two basic elements: (i) the frequency of each kind of harm associated with a hazard and (ii) the adversity of each of those harms. Because different kinds of harm are often measured along incompatible dimensions, adversity is quantified on an ordinal scale. Frequency is quantified on a ratio scale. Sampling error, measurement error, and bias all contribute to uncertainty about frequency. Differences in opinion, measurement error, and choice of dimensions lead to uncertainty about adversity. In this chapter, risk is imaged as an area circumscribed by uncertainty bounds around all of the harms. This area is called the risk profile of a hazard. Different individuals and groups respond to uncertainty and risk differently, and the risk profile can be further focused to visualize particular risk perceptions. These alternate risk visualizations may be contrasted and compared across management choices or across different risk perceivers to facilitate communication and decision making. To illustrate the method, we image published clinical trial data.