I did fake Bayesian math with some plausible numbers, and found that if I started out believing there was a 20% per decade chance of a lab leak pandemic, then if COVID was proven to be a lab leak, I should update to 27.5%, and if COVID was proven not to be a lab leak, I should stay around 19-20%
This is so confusing: why bother doing “fake” math? How does he justify these numbers? Let’s look at the footnote:
Assume that before COVID, you were considering two theories:
- Lab Leaks Common: There is a 33% chance of a lab-leak-caused pandemic per decade.
- Lab Leaks Rare: There is a 10% chance of a lab-leak-caused pandemic per decade.
And suppose before COVID you were 50-50 about which of these were true. If your first decade of observations includes a lab-leak-caused pandemic, you should update your probability over theories to 76-24, which changes your overall probability of pandemic per decade from 21% to 27.5%.
Oh, he doesn’t, he just made the numbers up! “I don’t have actual evidence to support my claims, so I’ll just make up data and call myself a ‘good Bayesian’ to look smart.” Seriously, how could a reasonable person have been expected to be concerned about lab leaks before COVID? It simply wasn’t something in the public consciousness. This looks like some serious hindsight bias to me.
I don’t entirely accept this argument - I think whether or not it was a lab leak matters in order to convince stupid people, who don’t know how to use probabilities and don’t believe anything can go wrong until it’s gone wrong before. But in a world without stupid people, no, it wouldn’t matter.
Ah, no need to make the numbers make sense, because stupid people wouldn’t understand the argument anyway. Quite literally: “To be fair, you have to have a really high IQ to understand my shitty blog posts. The Bayesian math is is extremely subtle…” And, convince stupid people of what, exactly? He doesn’t say, so what was the point of all the fake probabilities? What a prick.
@swlabr @Tar_alcaran
Well, because (most) governments (mostly) *don’t* throw money at the problems that *could* be solved by throwing money at them.
Look at the malaria prevention or guinea worm eradication programs, for instance. Ten years ago or so, my first encounter with EA was a website talking about how many lives you could save or improve by giving money to NGOs focused on those issues.
Hell, look at homelessness in most “Western” countries, except Finland. Look at UBI. etc.
Ok, so to be clear, I would (perhaps naively) prefer it if we didn’t have charities/NGOs and that governments would handle solving problems and helping people entirely. Of course, this is reductive; there are probably plenty of spaces where NGOs and charities are better suited for approaching some issues.
That being said, while money (or a lack thereof) is the main issue in solving many problems, you still need all kinds of work to make it effective. In the case of malaria prevention, a cause EA deems to be cost-effective, you still need to pay staff to carry out logistics to deliver whatever nets or vaccines you buy with money. You wouldn’t want someone incompetent at the helm; that could cause your cost-effectiveness to go down. And how do you incentivize competent people to stay in leadership positions? There are plenty of ways, but executive bonuses will be at the top of that list.
Anyway, my main issue with EA has gotta be how it launders false morality and money into morality. The false morality is the X-risk shit. The money is the money from working in tech.