Re:The dawn of post-theory science?
by programmarchy on Friday January 14, 2022 @01:46AM
(#29931321)
You could say the same about humans; that we do not understand anything ourselves; that we’re mechanisms that do work. But it’s a moot point.
What I’m saying is that “reason” is an anthropocentric concept and is not a prerequisite for the production of knowledge, or even conducting science for that matter.
Reason isn't an anthropocentric concept at all. Knowledge isn't even produced. Knowledge is the subjective representation of facts, objects, skills and so forth. What's being produced by something like Alphafold is data, interpreting that data by means of reason and abstracting it into a model is what we call knowledge. The entire process is science.
And the first point you make is very important. The fact that we have neural nets in our heads that we didn't and don't really understand hasn't changed anything about what science is. We reason about the world and we do science because having general models about the world we are in is more powerful than merely collecting or correlating data. And that will be the case for any kind of intelligence.
ML systems as they exist do not produce knowledge for humans, and they do not understand anything themselves. They're mechanisms that do work. A chess computer doesn't understand chess any more than a lever understands physics, even if they can beat humans or lift heavy objects. Your TI-83 is not a mathematician despite the fact that it can calculate much quicker than you can.
If you're suggesting that at some point we may built some sort of AGI-scientist that can actually reason about something, potentially at a level we can't understand, sure. But that is not what ML is, that is science fiction, and it is not how ML systems will be used in the scientific process, they will aid as tools as they're doing right now, and that is what everyone will tell you who worked on AlphaFold.