Detection Is Not a Strategy

Every few weeks, someone announces a tool that detects AI hallucinations. A startup, a research lab, a hyperscaler bolting a “trust layer” onto its chatbot. The release uses the word “guardrails.” Everyone nods. Another brick in the road to safe, reliable AI.

I want to argue that we are cheering for the wrong thing — that hallucination detection, however clever, cannot be the strategy. It can be a backstop. It can be a monitor. It cannot be the plan. And the reason is older than computing.

Start with the trap at the center of the whole idea.

To catch a hallucination, your detector has to know the right answer. Sit with what that means. The original model produced a confident falsehood because it did not have the […]

By |June 5th, 2026|2026, Uncategorized|3 Comments
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Knowing What You Don’t Know

Why the next real breakthrough in AI isn’t a bigger brain — it’s a machine that can admit ignorance.

A reader caught me out.

Last column I argued that the great AI buildout — the hundreds of billions pouring into data centers and the GPUs that fill them — is aimed at the wrong layer. We are spending as if the bottleneck were the size of the model’s brain, when the real bottleneck is getting the right information in front of it. Cheap retrieval, I said, not expensive cognition.

A reader replied, pointing out the name Jevons.

In 1865, a young English economist named William Stanley Jevons noticed something strange about coal. As steam engines got more efficient — as they wrung more work out of every lump […]

By |June 4th, 2026|2026, Artificial Intelligence, Jevons, Uncategorized|10 Comments
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The Most Expensive Mistake in the History of Computing

I promised to show you why the whole industry’s answer to its own problem — buy a bigger brain — is the most expensive mistake in the history of computing. To do that I have to take you back to 1999, because I was there, and if you’re old enough to be reading me, maybe you were too.

And I wasn’t only watching. In 1999 I put $10,000 into a young company called E-Loan, run by a founder named Chris Larsen. After the IPO I cashed out for $400,000 and bought a house. Chris kept playing — E-Loan to Prosper to Ripple — and did rather better than a house; he’s a crypto billionaire now. (Chris, if you’re reading this: we should talk.) Those are […]

By |June 3rd, 2026|2026, Artificial Intelligence|2 Comments
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The Thirty Percent Confession

 

Last time I told you the AI industry is paying a tax it doesn’t have to pay — that a great deal of what we grandly call “AI” is really just looking things up, and we’ve chosen to do that looking-up on the most expensive silicon ever manufactured. A number of you wrote to say I was overstating it. Surely, you said, the people setting hundreds of billions of dollars on fire know something I don’t.

So this week I won’t argue with you. I’ll let one of the largest companies in enterprise software argue with you instead — because it already has, in a research paper it published itself and seems to have hoped you wouldn’t read too closely.

The company is Salesforce. The same […]

By |June 2nd, 2026|2026, Artificial Intelligence, Uncategorized|3 Comments
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The Lying Machine

There is a lawsuit grinding through a federal court in Minnesota that every insurance executive in America should be reading instead of their quarterly AI roadmap.

The case is Estate of Lokken v. UnitedHealth Group. It was filed in late 2023 by the families of two deceased Medicare Advantage members, and it alleges that UnitedHealthcare used an artificial-intelligence tool called nH Predict to decide how much post-acute care its members were entitled to — and that the tool was wrong roughly nine times out of ten, a figure the plaintiffs draw from how often its denials were reversed on appeal. UnitedHealth denies that the tool makes coverage decisions at all; it calls nH Predict “a guide” and says the real decisions are made by clinicians […]

By |June 1st, 2026|2026, Artificial Intelligence|6 Comments
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