Imagine asking an AI like Claude to solve a simple math problem: What’s 36 plus 59? Claude quickly replies: “95.” So you follow up with a natural next question: How did you get that answer?

Claude responds with the kind of explanation you’d expect from a middle school student—or a calculator with charm: “I added the ones—6 and 9—to get 15, carried the 1, and then added the tens—3, 5, and the 1—to get 9, resulting in 95.”

It sounds perfectly reasonable. Logical. Familiar. Exactly how we’d want Claude to explain it.

But here’s the catch: That’s not what Claude actually did.

According to recent research by Anthropic (2025a and 2025b),1 Claude’s real reasoning process was far less orderly. It approximated values—adding things like “40ish and 60ish” or “36ish and 57ish”—and then separately processed the last digits before cobbling together a final answer. And the explanation it gave? That wasn’t a transparent report of its internal steps. It was a narrative—a plausible-sounding reconstruction based on the kinds of things people tend to say when asked to explain basic math.

It’s easy to chalk this up as a limitation of artificial intelligence (AI). But the reality is more unsettling: We do the same thing.

Sometimes our reasoning is exactly what it appears to be: deliberate, logical, and consciously constructed. But other times—especially when we don’t really know why we made a decision—we tell ourselves a story after the fact. And we believe it.

Back in 1977, Nisbett and Wilson reviewed a variety of studies and concluded that we often lack direct access to the mental processes that produce our behavior. When those processes operate outside conscious awareness, we still offer explanations—but those explanations tend to reflect our assumptions or implicit theories........

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