this post was submitted on 08 Jul 2024
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I agree with your first paragraph, but unwinding that emergent behavior really can be impossible. It's not just a matter of taking spaghetti code and deciphering it, ML usually works by generating weights in something like a decision tree, neural network, or statistical model.
Assigning any sort of human logic to why particular weights ended up where they are is educated guesswork at best.
You know what we do in engineering when we need to understand a system a lot of the time? We instrument it.
Please explain why this can't be instrumented. Please explain why the trace data could not be analtzed offline at different timescales as a way to start understanding what is happening in the models.
I'm fucking embarassed for CS lately.
... but they just said that it can. You check it, and you will receive gibberish. Congrats, your value is .67845278462 and if you change that by .000000001 in either direction things break. Tell me why it ended up at that number. The numbers, what do they mean?
It's not always as simple as measuring an observable system or simulating the parameters the best you can. Lots of parameters + lots of variables = we have a good idea how it should go, we can get close, but don't actually know. That's part of why emergent behavior and chaos theory are so difficult, even in theoretically closed systems.
That field is called Explainable AI and the answer is because that costs money and the only reason AI is being used is to cut costs
☝️
Thank you. I am fucking exhausted from hearing people claim these things are somehow magically impossible when the real issue is cost.
Computers and technology are amazing, but they are not magic. They are the most direct piece of reality where you can reliably say that every single action taken can be broken into discrete steps, even if that means tracing individual CPU operations on data registers like an insane person.