You can't judge the value of a project by how smart or hardworking the people on it are. Doing a brilliant job on something inherently futile just means you're *really good* at wasting resources.
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Replying to @s_r_constantin
What are examples of this? Because this sounds fake to me.
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Replying to @drethelin
1.) Optimizing the hell out of target discovery & "rational drug design" is futile for discovering drugs, because most of the risk is later in the pipeline, when the drugs don't work on the disease in vivo. Very attractive topic for smart people, not very useful.
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Replying to @s_r_constantin @drethelin
2.) fancier math/statistics for analyzing inadequate data is often futile. You can't detect a signal that ain't there. (Yes, mathematical innovations can expand the range of what data counts as "usable", basic point still stands.)
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Replying to @s_r_constantin @drethelin
3.) really good execution of a product nobody wants is the canonical example of futile efforts by smart hardworking people.
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Replying to @s_r_constantin @drethelin
4.) I don't know that much military history, but afaik "the soldiers were brave and hardworking" is *really* no guarantee of victory. In war, good people doing good work on the wrong thing just leads to dead good people.
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Replying to @s_r_constantin
That’s a completely different topic though. The question isn’t really if random employees are smart or hard working, but if it’s run by smart and hard working people. And soldiers who are smart regularly know when the project is futile.
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Replying to @drethelin
some people's definition of "smart" seems to include "occasionally looking up from your task to ask if it's futile." Is that your perspective? If so, then yeah, being "smart" means avoiding futility.
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But, e.g. in scientific fields with "math envy", I see a lot of work that demonstrates painstakingly achieved technical competence but absolutely can't lead to better understanding/control of the phenomena being studied.
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Replying to @drethelin
...yes. Way more than the people who are actually "humble" enough about standard assumptions in the field.
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