Imagine if someone proposed the following model for assessing force: F=ma
(Yes, this is Newton's Second Law, and yes, I am using words like "model" and "assess" to reflect the risk assessment modeling problem.)
I could see two problems with using this model to assess force.
- Reality check: The model does not reflect reality. In other words, an accurate measurement of mass times an accurate measurement of acceleration does not result in an accurate measurement of force.
- Input check: To accurately measure force, the values for m and a must not be arbitrary. Otherwise, the value for F is arbitrary.
With respect to FAIR, I make the following judgments.
- Reality check: The jury is out on whether FAIR reflects reality. It certainly might. It might not.
- Input check: I have not seen any evidence that FAIR expects or requires anything other than arbitrary inputs. Arbitrary inputs to a model that passes the reality check does not produce anything valuable as far as I am concerned.
If you personally like feeding your own opinions into a model to see what comes out the other end, have at it. It's nice to play around by making assumptions, seeing the result, and then altering the inputs to suit whatever output you really wanted to see.
One of the previous post commenters mentioned the book Uncertainty, which looks fascinating. If you read the excerpt you'll notice this line:
In the early 1970s what was then the U.S. Atomic Energy Commission (AEC) asked Norman C. Rasmussen, a professor of nuclear engineering at the Massachusetts Institute of Technology, to undertake a quantitative study of the safety of light-water reactors...
Rasmussen assembled a team of roughly sixty people, who undertook to identify and formally describe, in terms of event trees, the various scenarios they believed might lead to major accidents in each of the two reactors studied. Fault trees were developed to estimate the probabilities of the various events.
A combination of historical evidence from the nuclear and other industries, together with expert judgment, were used to construct the probability estimates, most of which were taken to be log-normally distributed. (emphasis added)
I've seen no commitment to including real evidence in FAIR, and I submit that those who lack evidence will have their so-called "expert judgment" fail due to soccer-goal security. Therefore, they possess neither historical evidence nor really expert judgment. So, even if FAIR meets my reality check, the results are only a feel-good exercise.
So how can I defend the use of this model?
Risk = Vulnerability X Threat X Impact (or Cost)
As I've said before, it is useful for showing the effects on Risk if you change one of the factors, ceteris paribus. This assumes that the model passes the reality check, which I believe it does.
I am not trying to calculate absolute values for Risk when I cite this equation. I am trying to conceptually show how Risk decreases when Threat decreases (ceteris paribus), or how Risk increases as Vulnerability increases (ceteris paribus), and so on.
You could take the same approach with F=ma if you were trying to explain to someone how it would hurt more to be struck by an object whose mass is larger than another object, assuming constant acceleration for each event. I am not trying to calculate F in such a case; I'm only using the model to describe the relationship between the components.