You probably already agreed with "Ghosts in the Machine" before reading it since obviously, a program executes exactly its code even in the context of AI. Also obviously, the program can still appear to not do what it's supposed to if "supposed" is taken to mean to programmer's intent.
These statements don't ignore machine learning; they imply that we should not try to build an FAI using current machine learning techniques. You're right, we understand (program + parameters learned from dataset) even less than (program). So while the outside view might say: "current machine learning techniques are very powerful, so they are likely to be used for FAI," that piece of inside view says: "actually, they aren't. Or at least they shouldn't." ("learn" has a precise operational meaning here, so this is unrelated to whether an FAI should "learn" in some other sense of the word).
Again, whether a development has been successful or promising in some field doesn't mean it will be as successful in FAI, so imitation of the human brain isn't necessarily good here. Reasoning by analogy and thinking about evolution is also unlikely to help; nature may have given us "goals", but they are not goals in the same sense as : "The goal of this function is to add 2 to its input," or "The goal of this program is to play chess well," or "The goal of this FAI is to maximize human utility."
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Ooh ooh I have one:
That Thiel's real reason for saying such things is pure self-promotion.
Straussian thinking seems like a deep well full of status moves !