People currently understand the physical world sufficiently to see that supernatural claims are bogus, and so there is certainty about impossibility of developments predicated on supernatural. People know robust and general laws of physics that imply impossibility of perpetual motion, and so we can conclude in advance with great certainty that any perpetual motion engineering project is going to fail. Some long-standing problems in mathematics were attacked unsuccessfully for a long time, and so we know that making further progress on them is hard. In all these cases, there are specific pieces of positive knowledge that enable the inference of impossibility or futility of certain endeavors.
In contrast, a lot of questions concerning Friendly AI remain confusing and unexplored. It might turn out to be impossibly difficult to make progress on them, or else a simple matter of figuring out how to apply standard tools of mainstream mathematics. We don't know, but neither do we have positive knowledge that implies impossibility or extreme difficulty of progress on these questions. In particular, the enormity of consequences does not imply extreme improbability of influencing those consequences. It looks plausible that the problem can be solved.
Nick Szabo on acting on extremely long odds with claimed high payoffs:
Beware of what I call Pascal's scams: movements or belief systems that ask you to hope for or worry about very improbable outcomes that could have very large positive or negative consequences. (The name comes of course from the infinite-reward Wager proposed by Pascal: these days the large-but-finite versions are far more pernicious). Naive expected value reasoning implies that they are worth the effort: if the odds are 1 in 1,000 that I could win $1 billion, and I am risk and time neutral, then I should expend up to nearly $1 million dollars worth of effort to gain this boon. The problems with these beliefs tend to be at least threefold, all stemming from the general uncertainty, i.e. the poor information or lack of information, from which we abstracted the low probability estimate in the first place: because in the messy real world the low probability estimate is almost always due to low or poor evidence rather than being a lottery with well-defined odds.
Nick clarifies in the comments that he is indeed talking about singularitarians, including his GMU colleague Robin Hanson. This post appears to revisit a comment on an earlier post:
In other words, just because one comes up with quasi-plausible catastrophic scenarios does not put the burden of proof on the skeptics to debunk them or else cough up substantial funds to supposedly combat these alleged threats.