The problem with the “no scientific evidence” line of thought is it devolves to:
“We know nothing at all unless a credentialed scientist conducted a blind RCT at the cost of millions of dollars and years of time. And the only information we learned from the RCT was a probability update for a binary question. And the results had to be reviewed by peer scientists, manually, and then published in a high impact journal or they are not credible”.
Otherwise we are going to pretend we know absolutely nothing and will continue to do things per decades old tradition. (Even though those traditions were never checked with the same algorithm)
This is not a system that will develop effective treatments for aging and human disease.
Moreover the math says it is morally evil and kills millions.
My proposed fix is we develop automated systems to do all the above and we have the algorithms reviewed by all of the above but then reuse the same automated systems for thousands of experiments. And instead of explicit rcts we usually find the data by mining or proxy experiments.
I definitely share your concern that evidence which isn’t “scientific” matters, but I still think whether or not there is scientific evidence isn’t entirely irrelevant to decision-making when we care about creating organizations that consistently make good decisions.
Currently, we definitely care far too much about scientific evidence, but I disagree that the concept is entirely bullshit.
I am not saying it is bullshit. But failing to consider information also has a cost. And for some fields, “consistently good decisions” may not even be possible.
The problem with the “no scientific evidence” line of thought is it devolves to:
“We know nothing at all unless a credentialed scientist conducted a blind RCT at the cost of millions of dollars and years of time. And the only information we learned from the RCT was a probability update for a binary question. And the results had to be reviewed by peer scientists, manually, and then published in a high impact journal or they are not credible”.
Otherwise we are going to pretend we know absolutely nothing and will continue to do things per decades old tradition. (Even though those traditions were never checked with the same algorithm)
This is not a system that will develop effective treatments for aging and human disease.
Moreover the math says it is morally evil and kills millions.
My proposed fix is we develop automated systems to do all the above and we have the algorithms reviewed by all of the above but then reuse the same automated systems for thousands of experiments. And instead of explicit rcts we usually find the data by mining or proxy experiments.
I definitely share your concern that evidence which isn’t “scientific” matters, but I still think whether or not there is scientific evidence isn’t entirely irrelevant to decision-making when we care about creating organizations that consistently make good decisions.
Currently, we definitely care far too much about scientific evidence, but I disagree that the concept is entirely bullshit.
I am not saying it is bullshit. But failing to consider information also has a cost. And for some fields, “consistently good decisions” may not even be possible.