How would I explain the event of my left arm being replaced by a blue tentacle? The answer is that I wouldn’t. It isn’t going to happen.
If a miracle happens, then a miracle happens. I’m not holding my breath.
The ways in which I do expect Vaniver_2021 to look back at Vaniver_2020 and think “yeah, he was worried about that but it didn’t turn out to be relevant” are various unknowns about the virus that might be fine or might be bad. For example, we don’t know how bad surface transmission will be, but that’s a big factor in what sort of isolation protocols you need to have. We don’t know whether existing anti-virals will be effective. We don’t know how long immunity will last, but that’s a big factor in whether or not ‘herd immunity’ strategies will work, and how valuable it is to not catch it. We don’t know how big a deal antibody-dependent enhancement will be, or how that will interact with the duration of immunity. We don’t know what long-term effects of infection (think fatigue, disability, infertility, etc.) look like. We don’t know how long people are infectious before they show noticeable symptoms.
For all of those things, I put significant probability on the “it’s fine” side of the uncertainty. But it being not fine is quite bad compared to it being fine, such that the expected utility shakes out that I should take it seriously until we know more. For example, I now think that if you’re taking your temperature every day, the “infectious before noticeable symptoms” window is probably about a day, which seems pretty tolerable, but don’t think I made a mistake in my assessment before. If the long-term disability risk turns out to be closer to 1% than 10%, then I’ll adjust my prior on long-term disability for next time (in the obvious way that I’ll have two datapoints instead of one), but I won’t think “oh, I cried wolf.”
From A Technical Explanation of Technical Explanation:
If a miracle happens, then a miracle happens. I’m not holding my breath.
The ways in which I do expect Vaniver_2021 to look back at Vaniver_2020 and think “yeah, he was worried about that but it didn’t turn out to be relevant” are various unknowns about the virus that might be fine or might be bad. For example, we don’t know how bad surface transmission will be, but that’s a big factor in what sort of isolation protocols you need to have. We don’t know whether existing anti-virals will be effective. We don’t know how long immunity will last, but that’s a big factor in whether or not ‘herd immunity’ strategies will work, and how valuable it is to not catch it. We don’t know how big a deal antibody-dependent enhancement will be, or how that will interact with the duration of immunity. We don’t know what long-term effects of infection (think fatigue, disability, infertility, etc.) look like. We don’t know how long people are infectious before they show noticeable symptoms.
For all of those things, I put significant probability on the “it’s fine” side of the uncertainty. But it being not fine is quite bad compared to it being fine, such that the expected utility shakes out that I should take it seriously until we know more. For example, I now think that if you’re taking your temperature every day, the “infectious before noticeable symptoms” window is probably about a day, which seems pretty tolerable, but don’t think I made a mistake in my assessment before. If the long-term disability risk turns out to be closer to 1% than 10%, then I’ll adjust my prior on long-term disability for next time (in the obvious way that I’ll have two datapoints instead of one), but I won’t think “oh, I cried wolf.”