"Look at this child. She will die, unless you donate now" - an identified life. Humans are very sensitive to these.
"If we fund this drug, outlook for patients who get this type of cancer (Z cases per year) will improve from 50% to 80% survival over 5 years" - These are "more predictable" statistical lives. We don't know exactly who will be saved but we think we have a good handle on how many people it will be.
"If we don't put this control in the plant, we believe there's a 0.1% chance of an accident per year, which could cause up to 100,000 deaths in the surrounding area" - these are "less predictable" statistical lives. We know the impact is large, but we don't _really_ know how large. We know the probability is quite low, but we don't have an exact figure for that, either.
Numerically, if 100 people were dropping dead next to the plant per year that would be a pretty big deal, but instead this (in spherical cow terms) identical issue remains on the risk register, for now. Most likely, no one will come to any harm.
My intuition is that decision makers feel the risk (to them) of being blamed for unlikely events is quite low. The odds of a given tail risk manifesting during any given leader's tenure are also correspondingly low. The main exception seems to be terrorism; political leaders seem to be very sensitive to that.
Sometimes I think human risk estimates are primarily driven by how easily we can imagine the risk occurring to us, and the vividness of that imagining.
Most people seem to prefer the very diffuse but predictable risk of particulate emissions from coal plants over the minute but less predictable tail risk of a nuclear plant next door (i.e, the exact opposite preference to that described in the paper).
IMHO this can largely be explained at a population level by the fact that there are lots of movies about reactor meltdowns, but (as far as I know) no movies which show a particle emitted from a coal plant entering a person's lungs and their ensuing battle with cancer.
"If we fund this drug, outlook for patients who get this type of cancer (Z cases per year) will improve from 50% to 80% survival over 5 years" - These are "more predictable" statistical lives. We don't know exactly who will be saved but we think we have a good handle on how many people it will be.
"If we don't put this control in the plant, we believe there's a 0.1% chance of an accident per year, which could cause up to 100,000 deaths in the surrounding area" - these are "less predictable" statistical lives. We know the impact is large, but we don't _really_ know how large. We know the probability is quite low, but we don't have an exact figure for that, either.
Numerically, if 100 people were dropping dead next to the plant per year that would be a pretty big deal, but instead this (in spherical cow terms) identical issue remains on the risk register, for now. Most likely, no one will come to any harm.
My intuition is that decision makers feel the risk (to them) of being blamed for unlikely events is quite low. The odds of a given tail risk manifesting during any given leader's tenure are also correspondingly low. The main exception seems to be terrorism; political leaders seem to be very sensitive to that.
Sometimes I think human risk estimates are primarily driven by how easily we can imagine the risk occurring to us, and the vividness of that imagining.
Most people seem to prefer the very diffuse but predictable risk of particulate emissions from coal plants over the minute but less predictable tail risk of a nuclear plant next door (i.e, the exact opposite preference to that described in the paper).
IMHO this can largely be explained at a population level by the fact that there are lots of movies about reactor meltdowns, but (as far as I know) no movies which show a particle emitted from a coal plant entering a person's lungs and their ensuing battle with cancer.