Apr 15, 2012
Risk Assessment is Hard (computationally and otherwise)
Posted by John Cassel in categories: existential risks, information science, policy
How hard is to assess which risks to mitigate? It turns out to be pretty hard.
Let’s start with a model of risk so simplified as to be completely unrealistic, yet will still retain a key feature. Suppose that we managed to translate every risk into some single normalized unit of “cost of expected harm”. Let us also suppose that we could bring together all of the payments that could be made to avoid risks. A mitigation policy given these simplifications must be pretty easy: just buy each of the “biggest for your dollar” risks.
Not so fast.
The problem with this is that many risk mitigation measures are discrete. Either you buy the air filter or you don’t. Either your town filters its water a certain way or it doesn’t. Either we have the infrastructure to divert the asteroid or we don’t. When risk mitigation measures become discrete, then allocating the costs becomes trickier. Given a budget of 80 “harms” to reduce, and risks of 50, 40, and 35, then buying the 50 leaves 15 “harms” that you were willing to pay to avoid left on the table.
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