The Nonlinear Library LW - Secondary Risk Markets by Vaniver
Dec 12, 2023
07:20
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Secondary Risk Markets, published by Vaniver on December 12, 2023 on LessWrong.
This idea is half-baked; it has some nice properties but doesn't seem to me like a solution to the problem I most care about. I'm publishing it because maybe it points someone else towards a full solution, or solves a problem they care about, and out of a general sense that people should publish negative results.
Many risky activities impact not just the person doing the activity, but also bystanders or the public at large. Governments often require ability to compensate others as a precondition for engaging in the risky activity, with requirements to have car insurance to drive as a common example.
In most situations, this works out fine:
A competitive insurance market means that customers aren't overcharged too much (since they'll switch insurance providers to whoever estimates their risk as being the lowest).
Accidents are common enough that insurance companies that are bad at pricing quickly lose too much money and adjust their prices upwards (so customers aren't undercharged either).
Accidents are small enough that insurance companies can easily absorb the losses from mispriced insurance.
Accidents are predictable enough that insurers can price premiums by driver moderately well.
Drivers are common enough that simple prediction rules make more sense than putting dedicated thought into how much to charge each driver.
Suppose we adjust the parameters of the situation, and now instead of insuring drivers doing everyday trips, we're trying to insure rare, potentially catastrophic events, like launching nuclear material into orbit to power deep space probes. Now a launch failure potentially affects millions of people, and estimating the chance of failure is well worth more than a single formula's attention.
As a brief aside, why try to solve this with insurance? Why not just have regulators decide whether you can or can't do something? Basically, I believe that prices transmit information, and allow you to make globally correct decisions by only attending to local considerations.
If the potential downside of something is a billion dollars, and you have a way to estimate micro-failures, you can price each micro-failure at a thousand dollars and answer whether or not mitigations are worth it (if it reduces the microfailures by 4 and costs $5,000, it's not worth it, but if it's 6 microfailures instead then it is worth it) and whether or not it's worth doing the whole project at all. It seems more flexible to have people codesign their launch with their insurer than with the regulator.
But the title of this post is Secondary Risk Markets. If there's a price on the risk that's allowed to float, then it's also more robust; if Geico disagrees with State Farm's estimates, then we want them to bet against each other and reach a consensus price, rather than the person doing the risky activity just choosing the lowest bidder. [That is, we'd like this to be able to counteract the Unilateralist's Curse.]
For example, suppose Alice want to borrow a fragile thousand dollar camera to do a cool photoshoot, and there's some probability she ruins it. By default, this requires that she post $1,000, which she probably doesn't want to do on her own; instead she goes to Bob, who estimates her risk at 5%, and Carol, who estimates her risk at 9%. Alice offers to pay Bob $51 if he puts up the $1,000, with $1 in expected profit for Bob.
If Bob would say yes to that, Carol would want to take that bet too; she would like to give Bob $51 in exchange for $1,000 if Alice breaks the camera, since that's $39 in expected profit for Carol. And Bob, if actually betting with Carol, would want to set the price at something more like $70, since that equalizes the profit for the two of them, with the actual price depending on ho...
This idea is half-baked; it has some nice properties but doesn't seem to me like a solution to the problem I most care about. I'm publishing it because maybe it points someone else towards a full solution, or solves a problem they care about, and out of a general sense that people should publish negative results.
Many risky activities impact not just the person doing the activity, but also bystanders or the public at large. Governments often require ability to compensate others as a precondition for engaging in the risky activity, with requirements to have car insurance to drive as a common example.
In most situations, this works out fine:
A competitive insurance market means that customers aren't overcharged too much (since they'll switch insurance providers to whoever estimates their risk as being the lowest).
Accidents are common enough that insurance companies that are bad at pricing quickly lose too much money and adjust their prices upwards (so customers aren't undercharged either).
Accidents are small enough that insurance companies can easily absorb the losses from mispriced insurance.
Accidents are predictable enough that insurers can price premiums by driver moderately well.
Drivers are common enough that simple prediction rules make more sense than putting dedicated thought into how much to charge each driver.
Suppose we adjust the parameters of the situation, and now instead of insuring drivers doing everyday trips, we're trying to insure rare, potentially catastrophic events, like launching nuclear material into orbit to power deep space probes. Now a launch failure potentially affects millions of people, and estimating the chance of failure is well worth more than a single formula's attention.
As a brief aside, why try to solve this with insurance? Why not just have regulators decide whether you can or can't do something? Basically, I believe that prices transmit information, and allow you to make globally correct decisions by only attending to local considerations.
If the potential downside of something is a billion dollars, and you have a way to estimate micro-failures, you can price each micro-failure at a thousand dollars and answer whether or not mitigations are worth it (if it reduces the microfailures by 4 and costs $5,000, it's not worth it, but if it's 6 microfailures instead then it is worth it) and whether or not it's worth doing the whole project at all. It seems more flexible to have people codesign their launch with their insurer than with the regulator.
But the title of this post is Secondary Risk Markets. If there's a price on the risk that's allowed to float, then it's also more robust; if Geico disagrees with State Farm's estimates, then we want them to bet against each other and reach a consensus price, rather than the person doing the risky activity just choosing the lowest bidder. [That is, we'd like this to be able to counteract the Unilateralist's Curse.]
For example, suppose Alice want to borrow a fragile thousand dollar camera to do a cool photoshoot, and there's some probability she ruins it. By default, this requires that she post $1,000, which she probably doesn't want to do on her own; instead she goes to Bob, who estimates her risk at 5%, and Carol, who estimates her risk at 9%. Alice offers to pay Bob $51 if he puts up the $1,000, with $1 in expected profit for Bob.
If Bob would say yes to that, Carol would want to take that bet too; she would like to give Bob $51 in exchange for $1,000 if Alice breaks the camera, since that's $39 in expected profit for Carol. And Bob, if actually betting with Carol, would want to set the price at something more like $70, since that equalizes the profit for the two of them, with the actual price depending on ho...