You seem to have used the price of the shutgun directly without factoring in the likelihood of actually dying. I would be interested in how you would model the underlying probabilities.
This is true. I would rate the odds of actually dying ‘very low’, which my gut wants to ballpark in the <5% region. However, I do have some information that would let us make this a little more precise, so here goes:
I was in-country for a little under 90 days. The first 30 of them were acclimatization and specialized training, which didn’t involve being exposed to any real risk of combat. According to the paperwork associated with the incident, we were involved in 19 ambushes while I was there, which includes things like IEDs, but also just people spraying the vehicles with their guns to show us they are not afraid (this is almost zero risk to us). This leaves 19 ambushes over 60 days of operations, going out on average once per day.
So my prior is ~1/3 chance of someone trying to kill us each trip. Now there are two additional factors to consider: one, trips along the same route are not independent; two, the likelihood of dying in an attack is low. As it happens, ‘never take the same way twice’ is the literal first rule they taught us about movement when I went through training, perhaps because all of the cadre had been deployed previously. The more you drive a route, the more likely the enemy is to be prepared for you to drive the route—so each time you go out, the risk of attack is higher than it was before. When I was trained, they told us it was a given you would be hit the second time around—this is definitely an exaggeration, but I’ll say it is half again as likely as the previous trip at a guess, for a multiplier of 3⁄2. The likelihood of dying in an attack is low because everyone has first-responder training and medical kits, and we have medical evacuation helicopters, so dying usually needs one of three things: dying instantly; being so badly injured you die before medical evacuation; medical error (overlooked internal bleeding, or the like). Further, relatively few attacks are bad enough that someone is injured. I don’t actually know how to model these, though I know the Army has statistics for all of them.
Naively I can take a stab and say something like 1⁄20 attacks where someone is injured lead to one of the death conditions, with the proviso that it is only a guess. I can make a better guess for the probability of injury given an attack—of the 19 ambushes, I think there were 3 events where someone was injured (each corresponding to an IED blowing up a truck, incidentally). So this is what we have currently:
Prior for being attacked on a given trip: 1⁄3
Additional trips on the same route multiplier: 3⁄2
Likelihood of someone being injured during an attack: 3⁄19
This comes out to a little over 0.02 probability of someone dying, for four trips over the same route. Such is the power of history’s mightiest civilization.
Of course there’s plenty of stuff we left out: dying isn’t the only risk, being crippled is much more common; risk of injury is not equal throughout the group, and injuries tend to be clumpy because most of them come from trucks of people getting blown up; I knew none of these calculations at the time.
This doesn’t change the underlying intuition. In example, in the rational guesser game it does not matter what fraction of the average-of-guesses is given; the difference between 2⁄3 and 99⁄100 is only the number of iterations to 0.
The United States Army is probably the foremost institution of its kind in history. It has high prestige, enormous resources, and a great deal of experience. The feedback loops of violence are tight; the risks to personnel are immediate; the decisions it makes are as close as humanity gets to a stock market for death. And yet, at the point of decision, we will risk our lives for zero gain.
This causes me to view the approach for valuation of lives in X-risk uneasily, and from the opposite direction of sacredness.
You seem to have used the price of the shutgun directly without factoring in the likelihood of actually dying. I would be interested in how you would model the underlying probabilities.
This is true. I would rate the odds of actually dying ‘very low’, which my gut wants to ballpark in the <5% region. However, I do have some information that would let us make this a little more precise, so here goes:
I was in-country for a little under 90 days. The first 30 of them were acclimatization and specialized training, which didn’t involve being exposed to any real risk of combat. According to the paperwork associated with the incident, we were involved in 19 ambushes while I was there, which includes things like IEDs, but also just people spraying the vehicles with their guns to show us they are not afraid (this is almost zero risk to us). This leaves 19 ambushes over 60 days of operations, going out on average once per day.
So my prior is ~1/3 chance of someone trying to kill us each trip. Now there are two additional factors to consider: one, trips along the same route are not independent; two, the likelihood of dying in an attack is low. As it happens, ‘never take the same way twice’ is the literal first rule they taught us about movement when I went through training, perhaps because all of the cadre had been deployed previously. The more you drive a route, the more likely the enemy is to be prepared for you to drive the route—so each time you go out, the risk of attack is higher than it was before. When I was trained, they told us it was a given you would be hit the second time around—this is definitely an exaggeration, but I’ll say it is half again as likely as the previous trip at a guess, for a multiplier of 3⁄2. The likelihood of dying in an attack is low because everyone has first-responder training and medical kits, and we have medical evacuation helicopters, so dying usually needs one of three things: dying instantly; being so badly injured you die before medical evacuation; medical error (overlooked internal bleeding, or the like). Further, relatively few attacks are bad enough that someone is injured. I don’t actually know how to model these, though I know the Army has statistics for all of them.
Naively I can take a stab and say something like 1⁄20 attacks where someone is injured lead to one of the death conditions, with the proviso that it is only a guess. I can make a better guess for the probability of injury given an attack—of the 19 ambushes, I think there were 3 events where someone was injured (each corresponding to an IED blowing up a truck, incidentally). So this is what we have currently:
Prior for being attacked on a given trip: 1⁄3
Additional trips on the same route multiplier: 3⁄2
Likelihood of someone being injured during an attack: 3⁄19
Estimated likelihood of death given injury: 1⁄20
So that looks like:
(1/3)(3/19)(1/20) + (1/3)(3/2)(3/19)(1/20) + (1/3)(3/2)(3/2)(3/19)(1/20) + (1/3)(3/2)(3/2)(3/2)(3/19)(1/20)
This comes out to a little over 0.02 probability of someone dying, for four trips over the same route. Such is the power of history’s mightiest civilization.
Of course there’s plenty of stuff we left out: dying isn’t the only risk, being crippled is much more common; risk of injury is not equal throughout the group, and injuries tend to be clumpy because most of them come from trucks of people getting blown up; I knew none of these calculations at the time.
This doesn’t change the underlying intuition. In example, in the rational guesser game it does not matter what fraction of the average-of-guesses is given; the difference between 2⁄3 and 99⁄100 is only the number of iterations to 0.
The United States Army is probably the foremost institution of its kind in history. It has high prestige, enormous resources, and a great deal of experience. The feedback loops of violence are tight; the risks to personnel are immediate; the decisions it makes are as close as humanity gets to a stock market for death. And yet, at the point of decision, we will risk our lives for zero gain.
This causes me to view the approach for valuation of lives in X-risk uneasily, and from the opposite direction of sacredness.