But it might be that some of these banks had a blind spot there.
Every model has blind spots. That’s the nature of models. If you price risk by a specific model, people take less risk in your model and often take more risk that’s not part of the model.
It’s a systematic issue and if you want to get deeper into it read Antifragile or The Black Swan.
If you launch rockets, than it might be okay to assume that your risk model is good enough to optimize for it. If you are on the other hand talking about risk from UFAI there’s no reason to assume that you understand the problem well enough to model it and there a good chance that you take less risk in your model but increase the chance of the Black Swan event that kills you.
I’m quite aware of Black Swans. My suggestion was that some actors might kow about unknown unknowns and be able to make at least some predictions about this. Surely not inside systems that have opposing incentives. But e.g. reinsurer have some need to hedge these. These principles might be built upon. Maybe markets today price in black swans to some degree already.
Math can only tell you about what happens inside your model.
True by construction. Apparently I meant something else.
And I don’t mean it in the sense that a model of physics allows in principle to quantify that. But as a check of premises: Can we agree that known physics would in principle be model that would include the unknown unknowns are a quantifiable term (in principle)?
The known physics don’t allow you to say things about things unknown to model of known physics. Unknown variables that you can describe with the model of physics are known unknowns.
I agree to that. But we can’t get any further if we can’t agree on an intermediate point.
Would you argue about a system where we do not know the specifics of of some behavior of the system (to avoid the word ‘unknown’) but where we can know something about the (e.g. the probability mass) outside of the known specific behavior but still inside some general model of the system.
The known specific behavior is “known knowns” and not “known unknowns”. There are certainly known unknowns over which you can make valuable statements.
But we can’t get any further if we can’t agree on an intermediate point.
Accepting the limits of what one can know is important. That does often mean that one can’t go further.
Yes, the known specific behavior is known known. But I’m talking about the general behavior. Where we do not know specifics of but which is still within the general model? How do you call these?
Every model has blind spots. That’s the nature of models. If you price risk by a specific model, people take less risk in your model and often take more risk that’s not part of the model.
It’s a systematic issue and if you want to get deeper into it read Antifragile or The Black Swan.
If you launch rockets, than it might be okay to assume that your risk model is good enough to optimize for it. If you are on the other hand talking about risk from UFAI there’s no reason to assume that you understand the problem well enough to model it and there a good chance that you take less risk in your model but increase the chance of the Black Swan event that kills you.
I’m quite aware of Black Swans. My suggestion was that some actors might kow about unknown unknowns and be able to make at least some predictions about this. Surely not inside systems that have opposing incentives. But e.g. reinsurer have some need to hedge these. These principles might be built upon. Maybe markets today price in black swans to some degree already.
By the definition of unknown unknowns, they aren’t known.
Long-Term Capital Management did hedge their risk with their “Noble prize”-winning formulas.
Math. Can sometimes surprisingly say something about the unknown.
Social effects. Long-Term Capital Management maybe didn’t want to see the limits of their approach.
Math can only tell you about what happens inside your model. It can tell you something about known unknowns.
Their approach was that they thought risk can be measured with modern portfolio theory for which their funders got the “Nobel”.
It’s not that different from how you don’t want to see the limits.
And I don’t mean it in the sense that a model of physics allows in principle to quantify that. But as a check of premises: Can we agree that known physics would in principle be model that would include the unknown unknowns are a quantifiable term (in principle)?
The known physics don’t allow you to say things about things unknown to model of known physics. Unknown variables that you can describe with the model of physics are known unknowns.
I agree to that. But we can’t get any further if we can’t agree on an intermediate point.
Would you argue about a system where we do not know the specifics of of some behavior of the system (to avoid the word ‘unknown’) but where we can know something about the (e.g. the probability mass) outside of the known specific behavior but still inside some general model of the system.
The known specific behavior is “known knowns” and not “known unknowns”. There are certainly known unknowns over which you can make valuable statements.
Accepting the limits of what one can know is important. That does often mean that one can’t go further.
Yes, the known specific behavior is known known. But I’m talking about the general behavior. Where we do not know specifics of but which is still within the general model? How do you call these?
“known unknowns” describes a model where you have unknown variables but you know which variables you don’t know.
OK with that terminology we can agree.