They are then asked if they agree or disagree with a (presumably hypothetical?) company's proposal to reduce employees' welfare, such as replacing a meal with a shake. Two groups showed a different preference.
This makes me think about that old question of whether you thank LLM or not. That is treating LLMs more like humans, so if what this paper found holds, maybe that'd nudge our brain subtly toward dehumanizing other real humans!? That's so counter intuitive...
But that's beside the point of the paper. They are talking about how the humans perciving the "socio-emotional capabilities of autonomous agents" change their behavior toward other humans. Whether people get that perception because "LLMs hack our brain" or something else is largely irrelevant.
I don't think the point of SLO = flakiness out of control. The point of framing it as SLO is the realization that neither extremes are good. Flakiness cannot be allowed to get out of control that some efforts must be spent to contain it, but it's also unnecessarily perfectionist and thus the waste of precious engineering bandwidth to eliminate them completely. The whole point is to avoid "bureaucratic games", as you call it.
My theory is that the lack of easy mechanism to measure the flakiness is stalling the progress. If the overall flakiness can be measured, and the top offending tests identified, then I think it becomes no brainer to spend efforts curtailing them back when the flakiness gets too high, but otherwise exclude flaky tests from, say, PR merge gate.
This is indeed a religion, because in my experience people tend to feel strongly holding very different positions. You can already see it in this thread.
I think quantifying and prioritizing is key, like you wrote. Respected engineering organizations like Google and GitHub all came to the same place. Flakiness is often unevenly distributed, so find & tackle ones that are the worst. Don't try to eliminate the flakiness because that's not economically viable.
I'm trying to put my money where my mouth is... we'll see how it goes.