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MM: "One strange thing about AI is that we built it—we trained it—but we don’t understand how it works. It’s so complex. Even the engineers at OpenAI who made ChatGPT don’t fully understand why it behaves the way it does.
It’s not unlike how we don’t fully understand ourselves. I can’t open up someone’s brain and figure out how they think—it’s just too complex.
When we study human intelligence, we use both psychology—controlled experiments that analyze behavior—and neuroscience, where we stick probes in the brain and try to understand what neurons or groups of neurons are doing.
I think the analogy applies to AI too: some people evaluate AI by looking at behavior, while others “stick probes” into neural networks to try to understand what’s going on internally. These are complementary approaches.
But there are problems with both. With the behavioral approach, we see that these systems pass things like the bar exam or the medical licensing exam—but what does that really tell us?
Unfortunately, passing those exams doesn’t mean the systems can do the other things we’d expect from a human who passed them. So just looking at behavior on tests or benchmarks isn’t always informative. That’s something people in the field have referred to as a crisis of evaluation."
@remixtures It’s not unlike how we don’t fully understand ourselves. I can’t open up someone’s brain and figure out how they think—it’s just too complex. When we study human intelligence, we use both psychology—controlled experiments that analyze behavior—and neuroscience, where we stick probes in the brain and try to understand what neurons or groups of neurons are doing. I think the analogy applies to AI too (…).