Short answer:

Donate to MIRI, or split between MIRI and GiveWell charities if you want some fuzzies for short-term helping.

Long answer:

I'm a negative utilitarian (NU) and have been thinking since 2007 about the sign of MIRI for NUs. (Here's some relevant discussion.) I give ~70% chance that MIRI's impact is net good by NU lights and ~30% that it's net bad, but given MIRI's high impact, the expected value of MIRI is still very positive.

As far as your question: I'd put the probability of uncontrolled AI creating hells higher than 1 in 10,000 and the probability that MIRI as a whole prevents that from happening higher than 1 in 10,000,000. Say such hells used 10^-15 of the AI's total computing resources. Assuming computing power to create ~10^30 humans for ~10^10 years, MIRI would prevent in expectation ~10^18 hell-years. Assuming MIRI's total budget ever is $1 billion (too high), that's ~10^9 hell-years prevented per dollar. Now apply rigorous discounts to account for priors against astronomical impacts and various other far-future-dampening effects. MIRI still seems very promising at the end of the calculation.

I had a look at this: the KCA (Kolmogorov Complexity) approach seems to match my own thoughts best.

I'm not convinced about the "George Washington" objection. It strikes me that a program which extracts George Washington as an observer from insider a wider program "u" (modelling the universe) wouldn't be significantly shorter than a program which extracts any other human observer living at about the same time. Or indeed, any other animal meeting some crude definition of an observer.

Searching for features of human interest (like "leader of a nation") is likely to be pretty complicated, and require a long program. To reduce the program size as much as possible, it ought to just scan for physical quantities which are easy to specify but very diagnostic of a observer. For example, scan for a physical mass with persistent low entropy compared to its surroundings, persistent matter and energy throughput (low entropy in, high entropy out, maintaining its own low entropy state), a large number of internally structured electrical discharges, and high correlation between said discharges and events surrounding said mass. The program then builds a long list of such "observers" encountered while stepping through u, and simply picks out the nth entry on the list, giving the "nth" observer complexity about K(n). Unless George Washington happened to be a very special n (why would he be?) he would be no simpler to find than anyone else.

I think I did not explain my proposal clearly enough. What I'm claiming is if that you could see intermediate steps suggesting that a worst-type future is imminent, or merely crosses your probability threshold as "too likely", then you could enumerate those and request to be removed from biostasis then. Before those who are resuscitating you would have a chance to do so.

A "do not resuscitate" kind of request would probably help with some futures that are mildly bad in virtue of some disconnect between your old self and the future (e.g., extreme future shock). But in those cases, you could always just kill yourself.

In the worst futures, presumably those resuscitating you wouldn't care about your wishes. These are the scenarios where a terrible future existence could continue for a very long time without the option of suicide.

Birth Year vs Foom:

A bit less striking than the famous enough to have Google pop up their birth year subset (green).

The subset that you can get birth years off the first page of a google search of their name (n=9), has a pretty clear correlation with younger people believing in harder takeoff. (I'll update if I get time to dig out other's birth years.)

How different would this be with age as the x axis?

Side note: I keep seeing a bizarre assumption (which I can only assume is a Hollywood trope) from a lot of people here that even a merely human-level AI would automatically be awesome at dealing with software just because they're made of software. (like how humans are automatically experts in advanced genetic engineering just because we're made of DNA)

Not "just because they're made of software" - but because there are many useful things that a computer is already better than a human at (notably, vastly greater "working memory"), so a human-level AI can be expected to have those and whatever humans can do now. And a programmer who could easily do things like "check all lines of code to see if they seem like they can be used", or systematically checking from where a function could be called, or "annotating" each variable, function or class by why it exists ... all things that a human programmer could do, but that either require a lot of working memory, or are mind-numblingly boring.

This has a very low n=16, and so presumably some strong selection biases. (Surely these are not the only people who have published thought-out opinions on the the likelihood of fooming.) Without an analysis of the reasons these people give for their views, I don't think this correlation is very interesting.

Something feels very,very wrong that Elon Musk is on the left-hand side of the chart, and Ben Goertzel on the right. I'd reckon that Elon Musk is a more reliable source about the timelines of engineering projects in general (with no offense meant to Goertzel). Maybe this axis isn't measuring the right thing?