The reason for this hardline stance is that we believe in the value of human thought and experience, as told by people with first-hand knowledge. It’s also about the audience: The “audience” for AI-written code is usually a machine, whereas the writing in Pragmatic Engineer is for humans, by humans. AI produces a statistical average in its output which creates uniform, dull text that’s an inferior reading experience to human writing – at least today it is.
It may still be the case, and I guess it is, that immune traits are the most selected category, but is not at all the case, and in fact, we can prove it's not the case that behavioral traits are not selected.
And really from a statistical point of view, what happens at these times of migration is there's just huge fluctuations in frequencies, and these are extremely uninformative times for looking and detecting natural selection.
Over the past few decades, journal editors and peer-reviewers have increasingly insisted that papers must present large datasets that have been treated using complex statistical methods in order to make even the mildest claims about what caused what.
will the error rate ever be controllable or manageable will you ever get to a model that knows when it's wrong which to me seems like given a stat statistical system seems like a contradiction in terms
But their latest study is for only 7.1 million miles. They need something like 40 times more data prove they are actually saving lives with statistical confidence (likely even more).
They frame the situation as a choice between continued human drivers killing people (without statistical context) vs. immature robotaxis who don't drink and drive (but make other mistakes).
If you're curious how Google built it's culture and the processes thanks to their extremely data & engineering driven nature, this is a great book. What held it back was being ~100 pages too long and Bock didn't always understand where what they did only fit at a $100Bn+, mega-profitable company. Still, the insights on the studies on their 50,000+ employees is well worth the read since so few of us can get similar statistical significance to apply to our teams.
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