Ford Motor Company spent the last few years cutting experienced engineers and leaning on artificial intelligence to catch quality problems before cars left the factory. Last week the company admitted what that actually produced: recalls, dependability ratings sliding, and a scramble to rehire the very engineers it had let go. Their own vice president of vehicle hardware engineering put it plainly — they’d assumed that introducing AI and feeding it the design requirements would produce a high-quality product. It didn’t. The tool worked fine. What was missing was the judgment of the people who used to catch what the tool couldn’t.

Ford isn’t alone. Commonwealth Bank of Australia replaced human customer service reps with an AI voice bot, then reversed course when complaints spiked. IBM’s AI-driven HR system handled 94% of routine requests fine — and had no answer for the 6% that involved a judgment call, so IBM announced it’s tripling entry-level hiring to rebuild the human layer it had cut. A recent industry survey found 29% of companies that laid off workers because of AI have already rehired for the same jobs. Nearly a third.

None of this means AI doesn’t work. It means something more specific, and more useful: every one of these failures happened at the exact same seam — the point where a machine’s job ends and a human being’s judgment is supposed to begin. And in every case, nobody had actually decided, in advance, where that seam was.

That’s the real question about AI, and almost nobody in public life is asking it. The debate we’re having is “is AI good or is AI dangerous” — a binary that generates a lot of heat and almost no light. The question that........

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