In general and across all instances I can think of so far, I do not agree with the part of your futurological forecast in which you reason, "After event W happens, everyone will see the truth of proposition X, leading them to endorse Y and agree with me about policy decision Z."
Example 1: "After a 2-year-old mouse is rejuvenated to allow 3 years of additional life, society will realize that human rejuvenation is possible, turn against deathism as the prospect of lifespan / healthspan extension starts to seem real, and demand a huge Manhattan Project to get it done." (EDIT: This has not happened, and the hypothetical is mouse healthspan extension, not anything cryonic. It's being cited because this is Aubrey de Grey's reasoning behind the Methuselah Mouse Prize.)
Alternative projection: Some media brouhaha. Lots of bioethicists acting concerned. Discussion dies off after a week. Nobody thinks about it afterward. The rest of society does not reason the same way Aubrey de Grey does.
Example 2: "As AI gets more sophisticated, everyone will realize that real AI is on the way and then they'll start taking Friendly AI development seriously."
Alternative projection: As AI gets more sophisticated, the rest of society can't see any difference between the latest breakthrough reported in a press release and that business earlier with Watson beating Ken Jennings or Deep Blue beating Kasparov; it seems like the same sort of press release to them. The same people who were talking about robot overlords earlier continue to talk about robot overlords. The same people who were talking about human irreproducibility continue to talk about human specialness. Concern is expressed over technological unemployment the same as today or Keynes in 1930, and this is used to fuel someone's previous ideological commitment to a basic income guarantee, inequality reduction, or whatever. The same tiny segment of unusually consequentialist people are concerned about Friendly AI as before. If anyone in the science community does start thinking that superintelligent AI is on the way, they exhibit the same distribution of performance as modern scientists who think it's on the way, e.g. Hugo de Garis, Ben Goertzel, etc.
Consider the situation in macroeconomics. When the Federal Reserve dropped interest rates to nearly zero and started printing money via quantitative easing, we had some people loudly predicting hyperinflation just because the monetary base had, you know, gone up by a factor of 10 or whatever it was. Which is kind of understandable. But still, a lot of mainstream economists (such as the Fed) thought we would not get hyperinflation, the implied spread on inflation-protected Treasuries and numerous other indicators showed that the free market thought we were due for below-trend inflation, and then in actual reality we got below-trend inflation. It's one thing to disagree with economists, another thing to disagree with implied market forecasts (why aren't you betting, if you really believe?) but you can still do it sometimes; but when conventional economics, market forecasts, and reality all agree on something, it's time to shut up and ask the economists how they knew. I had some credence in inflationary worries before that experience, but not afterward... So what about the rest of the world? In the heavily scientific community you live in, or if you read econblogs, you will find that a number of people actually have started to worry less about inflation and more about sub-trend nominal GDP growth. You will also find that right now these econblogs are having worry-fits about the Fed prematurely exiting QE and choking off the recovery because the elderly senior people with power have updated more slowly than the econblogs. And in larger society, if you look at what happens when Congresscritters question Bernanke, you will find that they are all terribly, terribly concerned about inflation. Still. The same as before. Some econblogs are very harsh on Bernanke because the Fed did not print enough money, but when I look at the kind of pressure Bernanke was getting from Congress, he starts to look to me like something of a hero just for following conventional macroeconomics as much as he did.
That issue is a hell of a lot more clear-cut than the medical science for human rejuvenation, which in turn is far more clear-cut ethically and policy-wise than issues in AI.
After event W happens, a few more relatively young scientists will see the truth of proposition X, and the larger society won't be able to tell a damn difference. This won't change the situation very much, there are probably already some scientists who endorse X, since X is probably pretty predictable even today if you're unbiased. The scientists who see the truth of X won't all rush to endorse Y, any more than current scientists who take X seriously all rush to endorse Y. As for people in power lining up behind your preferred policy option Z, forget it, they're old and set in their ways and Z is relatively novel without a large existing constituency favoring it. Expect W to be used as argument fodder to support conventional policy options that already have political force behind them, and for Z to not even be on the table.
I'm not connected to the Singularity Institute or anything, so this is my idiosyncratic view.
Think about theorem provers such as Isabelle or ACL2. They are typically structured a bit like an expert system with a rule base and an inference engine. The axioms play the role of rule base and the theorem prover plays the role of the inference engine. While it is easy to change the axioms, this implies a degree of interpretive overhead when it come to trying to prove a theorem.
One way to reduce the interpretative overhead is to use a partial evaluator to specialize the prover to the particular set of axioms.
Indeed, if one has a self-applicable partial evaluator one could use the second Futamura projection and, specializing the partial evaluator to the theorem prover, produce a theorem prover compiler. Axioms go in, an efficient theorem prover for those axioms comes out.
Self-applicable partial evaluators are bleeding-edge software technology and current ambitions are limited to stripping out interpretive overhead. They only give linear speed ups. In principle a partial evaluator could recognise algorithmic inefficiencies and, rewriting the code more aggressively produce super-linear speed ups.
This is my example of a critical event in AI: using a self-applicative partial evaluator and the second Futamura projection to obtain a theorem prover compiler with a super-linear speed up compared to proving theorems in interpretive mode. This would convince me that there was progress on self-improving AI and that the clock had started counting down towards an intelligence explosion that changes everything.
How long would be on the clock? A year? A decade? A century? Guessing wildly I'd put my critical event at the halfway point. AI research started in 1960, so if the critical event happens in 2020 that puts the singularity at 2080.
Notice how I am both more optimistic and more pessimistic about the prospects for AI than most commentators.
I'm more pessimistic because I don't see the current crop of wonderful, hand crafted, AI achievements, such as playing chess and driving cars as lying on the path towards recursively improving AI. These are the Faberge egg's of AI. They will not hatch into chickens that lay even more fabulous eggs...
I'm more optimistic because I'm willing to accept a technical achievement, internal to AI research, as a critical event. It could show that things are really moving, and that we can start to expect earth-shattering consequences, even before we've seen real-world impacts from the internal technical developments.
Vampire uses specialisation according to wikipedia: