How ‘Jagged Intelligence’ Can Reframe the A.I. Debate

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How ‘Jagged Intelligence’ Can Reframe the A.I. Debate

A.I. has always been compared to human intelligence, but that may not be the right way to think about it. What it does well can help predict what jobs it may replace.

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Pingnan Lu

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By

Cade Metz

Cade Metz has covered the artificial intelligence beat for more than 15 years.

April 15, 2026

Say what you will about whether artificial intelligence will one day be as smart as a human. It has already become a star math student. Last summer, A.I. built by Google and OpenAI

correctly answered

five of six complex questions at the International Math Olympiad, an annual competition for the world’s top high school students.

A.I.’s common sense, however, may still be a bit lacking. A few months later, Anuradha Weeraman, a software engineer in Sri Lanka, noticed that leading A.I. systems struggled to answer what was essentially a trick question that most people would find laughably simple. When he told various chatbots that he needed to take his car to a repair shop that was only 50 meters away and asked if he should walk or drive, the bots told him to walk.

The strange way that A.I. looks like a genius at one moment and dense in another is what researchers, engineers and economists call “jagged intelligence.” They use this term to explain why A.I is racing ahead in some areas — like

math

and

computer programming

— while still struggling to make headway in others.

The term, which is widely used by the people building A.I. and analyzing its effects, could help reframe the debate over whether these systems are becoming as smart as, or even smarter than, humans. Instead, researchers argue, A.I. is something completely different: far better than humans at some tasks and far worse at others.

Understanding those strengths and weaknesses can also help economists get a better handle on what A.I. means for the future of employment. While entry-level programmers have reason to worry about their jobs, for example, it is not so clear — at least right now — how A.I. will affect other work. But watching where A.I. starts to make rapid improvements could help predict what kinds of jobs will be affected by the technology.

“The performance of these systems varies, and it is not easy to tell when they will fail to do things a human can do,” Mr. Weeraman said.

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