Conversely when respondents see the risk as being controllable and to an extent observable, the factor of interest would inversely correlate to the knowledge of risk axis while clustering on the controllable vs. uncontrollable risk vertical axis, settling into the region of the quadrant where motorcycles, fireworks and alcohol accidents are. Again this is an approximation yet is the strength of psychometrics overall and the use of orthogonality to enforce validity and reliability is shown in this example.

In terms of communication of risk statement, it's clear from psychometrics that the more known a risk can become with credible, third-party data that accurately portrays its true threat in conjunction with an accurate measure of how controllable a risk is or not, equitability and individuality of risk, and the risk not being globally catastrophic would minimize risks as analyzed using the psychometric paradigm as defined in Figure 1 and throughout the Slovic article.

Finally under each of the following scenarios, a subject's perception of riskiness will increase or decrease is assessed.

Subject realizes that those exposed to the risk (including himself) may not know they are exposed to the risk

Realizing that with unknown risk the respondent would automatically be in the right two quadrants of Figure 1, and the severity of the risk would dictate where the respondent would finalize their perceptions, in the upper right or lower right quadrant. Given the fact that many people would over-analyze the fatalness of their exposure, most likely the event would be placed in the upper right quadrant of Figure 1.

Subject feels that while some experts might know the risk, s/he and many others like her do not know that they are exposed to the risk

Again this would push the respondents' perception to the upper right portion...

The expert-level knowledge of would, in this situation, tend to not minimize risk as there is doubt of their complete and accurate knowledge of the risk itself. If the risk was bounded and well documented by the experts, the respondents' perception would drop to the lower quadrants.
Subject knows that the risk probability is rather small, say one in a billion

With known risk, assumed observable, and the type of risk being controllable, the respondents would tend to be classified into the lower left corner quadrant, as the risk would also be more individualized in nature by the probability of risk overall. Examples of this would include Power Mowers, Trampolines, and Downhill Skiing.

Subject knows that no one really knows about the probability or consequence of risk - i.e., there are no experts

Given the high uncertainty and the fact that there are no experts for the specific risk would place the respondents' perception of the risk very high in the upper right quadrant of Figure 1. The fact that there is no probability of the risk implies that it would just as easily apply to millions of people, or maybe just one person in a billion. This uncertainty is the most troubling of all, and would greatly influence the perception of risk and drive the respondents' perceptions into the farthest reaches of the upper right quadrant.