Excellent start and setup, but I diverge from your line of thought here:
We will use a lower estimate of 1 in 100 for the ratio of near-miss to real case, because the type of phenomena for which the level of near-miss is very high will dominate the probability landscape. (For example, if an epidemic is catastrophic in 1 to 1000 cases, and for nuclear disasters the ratio is 1 to 100, the near miss in the nuclear field will dominate).
I’m not sure I buy this. We have two types of near misses (biological and nuclear). Suppose we construct some probability distribution for near-misses, ramping up around 1⁄100 and ramping back down at 1/1000. That’s what we have to assume for any near-miss scenario, if we know nothing additional. I’ll grant that if we roll the dice enough times, the 1⁄100 cases will start to dominate, but we only have 2 categories of near misses. That doesn’t seem like enough to let us assume a 1⁄100 ratio of catastrophes to near misses.
Additionally, there does seem to be good reason to believe that the rate of near misses has gone down since the cold war ended. (Although if any happened, they’d likely still be classified.) That’s not to say that our current low rate is a good indicator, either. I would expect our probability of catastrophe to be dominated by the probability of WWIII or another cold war.
We had 2 world wars in the first 50 years of last century, before nuclear deterrence substantially lowered the probability of a third. If that’s a 10x reduction, then we can expect 0.4 a century instead of 4 a century. If there’s a 100x reduction, then we might expect 0.04 world wars a century. Multiply that by the probability of nuclear winter given WWIII to get the probability of disaster.
However, I suspect that another cold war is more likely. We spent ~44 of the past 70 years in a cold war. If that’s more or less standard, then on average we might expect to spend 63% of any given century in a cold war. This can give us a rough range of probabilities of armageddon:
1 near miss a year spent in cold war 63 years spent in cold war per century 1 nuclear winter per 100 near misses = 63% chance of nuclear winter per century
0.1 near miss a year spent in cold war 63 years spent in cold war per century 1 nuclear winter per 3000 near misses = 0.21% chance of nuclear winter per century
For the record, this range corresponds to a projected half life between roughly 1 century and ~100 centuries. That’s much more broad then your 50-100 year prediction. I’m not even sure where to start to guesstimate the risk of an engineered pandemic.
“I’ll grant that if we roll the dice enough times, the 1⁄100 cases will start to dominate, but we only have 2 categories of near misses. That doesn’t seem like enough to let us assume a 1⁄100 ratio of catastrophes to near misses.”
In this case total probability of near misses will be something like (1/100 +1/3000)/2 = almost 1⁄200. If we look into nature of cold war near misses we could see that 1⁄100 estimate is more probable.
More research need to estimate what field is more equal to cold war. Probably it would be nuclear accidents on power stations.
Large research on the topic is here.http://www-pub.iaea.org/MTCD/Publications/PDF/Pub1545_web.pdf But it doesn’t give exacxt estimate of the frequency of NM, stating it as few to thousands.
They define NM as chain of events and they also stated that rising security measures help to reduce NM frequency.
On my first link near-miss frequency is already aggregated: “Studies
in several industries indicate that there are between 50 and 100 near misses for every accident. Also,
data indicates that there are perhaps 100 erroneous acts or conditions for every near miss. This gives
a total population of roughly 10,000 errors for every accident. Figure 1 illustrates the relationships
between accidents, near misses and non-incidents.” http://www.process-improvement-institute.com/_downloads/Gains_from_Getting_Near_Misses_Reported_website.pdf
Ah, thanks for the explanation. I interpreted the statement as you trying to demonstrate that number of nuclear winters / number of near misses = 1⁄100. You are actually asserting this instead, and using the statement to justify ignoring other categories of near misses, since the largest will dominate. That’s a completely reasonable approach.
I really wish there was a good way to estimate the accidents per near miss ratio. Maybe medical mistakes? They have drastic consequences if you mess up, but involve a lot of routine paperwork. But this assumes that the dominant factors in the ratio are severity of consequences. (Probably a reasonable assumption. Spikes on steering wheels make better drivers, and bumpers make less careful forklift operators.) I’ll look into this when I get a chance.
Excellent start and setup, but I diverge from your line of thought here:
I’m not sure I buy this. We have two types of near misses (biological and nuclear). Suppose we construct some probability distribution for near-misses, ramping up around 1⁄100 and ramping back down at 1/1000. That’s what we have to assume for any near-miss scenario, if we know nothing additional. I’ll grant that if we roll the dice enough times, the 1⁄100 cases will start to dominate, but we only have 2 categories of near misses. That doesn’t seem like enough to let us assume a 1⁄100 ratio of catastrophes to near misses.
Additionally, there does seem to be good reason to believe that the rate of near misses has gone down since the cold war ended. (Although if any happened, they’d likely still be classified.) That’s not to say that our current low rate is a good indicator, either. I would expect our probability of catastrophe to be dominated by the probability of WWIII or another cold war.
We had 2 world wars in the first 50 years of last century, before nuclear deterrence substantially lowered the probability of a third. If that’s a 10x reduction, then we can expect 0.4 a century instead of 4 a century. If there’s a 100x reduction, then we might expect 0.04 world wars a century. Multiply that by the probability of nuclear winter given WWIII to get the probability of disaster.
However, I suspect that another cold war is more likely. We spent ~44 of the past 70 years in a cold war. If that’s more or less standard, then on average we might expect to spend 63% of any given century in a cold war. This can give us a rough range of probabilities of armageddon:
1 near miss a year spent in cold war 63 years spent in cold war per century 1 nuclear winter per 100 near misses = 63% chance of nuclear winter per century
0.1 near miss a year spent in cold war 63 years spent in cold war per century 1 nuclear winter per 3000 near misses = 0.21% chance of nuclear winter per century
For the record, this range corresponds to a projected half life between roughly 1 century and ~100 centuries. That’s much more broad then your 50-100 year prediction. I’m not even sure where to start to guesstimate the risk of an engineered pandemic.
“I’ll grant that if we roll the dice enough times, the 1⁄100 cases will start to dominate, but we only have 2 categories of near misses. That doesn’t seem like enough to let us assume a 1⁄100 ratio of catastrophes to near misses.”
In this case total probability of near misses will be something like (1/100 +1/3000)/2 = almost 1⁄200. If we look into nature of cold war near misses we could see that 1⁄100 estimate is more probable. More research need to estimate what field is more equal to cold war. Probably it would be nuclear accidents on power stations. Large research on the topic is here.http://www-pub.iaea.org/MTCD/Publications/PDF/Pub1545_web.pdf But it doesn’t give exacxt estimate of the frequency of NM, stating it as few to thousands. They define NM as chain of events and they also stated that rising security measures help to reduce NM frequency.
On my first link near-miss frequency is already aggregated: “Studies in several industries indicate that there are between 50 and 100 near misses for every accident. Also, data indicates that there are perhaps 100 erroneous acts or conditions for every near miss. This gives a total population of roughly 10,000 errors for every accident. Figure 1 illustrates the relationships between accidents, near misses and non-incidents.” http://www.process-improvement-institute.com/_downloads/Gains_from_Getting_Near_Misses_Reported_website.pdf
Ah, thanks for the explanation. I interpreted the statement as you trying to demonstrate that number of nuclear winters / number of near misses = 1⁄100. You are actually asserting this instead, and using the statement to justify ignoring other categories of near misses, since the largest will dominate. That’s a completely reasonable approach.
I really wish there was a good way to estimate the accidents per near miss ratio. Maybe medical mistakes? They have drastic consequences if you mess up, but involve a lot of routine paperwork. But this assumes that the dominant factors in the ratio are severity of consequences. (Probably a reasonable assumption. Spikes on steering wheels make better drivers, and bumpers make less careful forklift operators.) I’ll look into this when I get a chance.