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The Economist Problem and AI

Matthew Guay

Wednesday, August 5, 2026

They're good at covering the basics. They appear worse, the more expertise you have on a subject.

The Economist keeps readers generally informed of what’s happening in the world around them, in a way that increasingly reminds me of the bell-curve of AI’s outputs.<br>The Economist is not the paper with headlines that bleed and lead, nor is it the best place for detailed analysis that analyzes what caused a thing to happen and the second-order effects. The Economist is, instead, the paper to read for a well-rounded perspective. It’s more detailed than an average newspaper, less like an academic journal, written professionally yet approachable.<br>It’s slow news, produced once a week, giving events a bit of time to settle before they’re reported on. I like that. It fits my general goals of trying to avoid clickbait and take a calmer, less emotional approach to news. Plus, it keeps me informed generally of things outside my general knowledge and expertise. I'm unlikely otherwise to think about the economy of Kazakhstan or the minutiae of oil trades.<br>Yet The Economist has a problem. If you’re an expert in a topic covered in its pages, you might find that its coverage is merely cursory. Generally, the broad strokes are correct, and more detailed and on the money than you might expect from another newspaper. What it isn’t is an expert opinion on every plausible topic, and so you read The Economist for the things that are outside of your locale and industry.<br>For the things closer to your heart, you likely have better sources: industry journals, trade magazines, Substacks, and the like. It’s an effect not limited to The Economist; “Everything you read in the newspapers is absolutely true except for the rare story of which you happen to have firsthand knowledge,” journalist Erwin Knoll is said to have quipped, and the effect is only amplified by The Economist’s broad range of coverage.<br>The Economist lets you know generally what’s going on in the world and converse with a mid-level knowledge of that topic without having to dig all the way in. And that’s enough for most topics (or, at least, as the Gell-Mann amnesia effect theory posits, it feels like it is—enough that I still turn to it for general world knowledge).<br>Which is strikingly similar to AI. AI feels brilliant at the tasks other people do. It feels considerably worse at doing the tasks in which you’re an expert. And while it’s easy to discount its skills at our expert tasks, it’s equally easy for those experiences to not temper usage of AI for other tasks in which we’re less capable.<br>Take it from me, who whipped up an internal dashboard with Cursor in an hour, one that would have taken me significant time to hand-code. Who also coded a quick bit of data-parsing Javascript for a Zapier workflow with AI, found the first output wanting, and poked the AI until it generated what I wanted. AI’s good enough at such tasks for me to hand them off without a second thought. But I also feel like AI’s terrible, relatively speaking, at consistently finding accurate quotes, doing deep research, testing software, and writing prose—the tasks to which I’ve dedicated the majority of my working hours for well over a decade.<br>I can tell at a glance when it’s making up a Steve Jobs quote, or at least know well enough to double-check the source each time. It can both find rare needles-in-the-haystack in research sometimes and fail to find things a cursory Google search would uncover at other times. And so I use AI for those tasks but take its responses with a grain of salt. But then, perhaps scarily, I’ll ask AI for one-off medical advice, and forget to similarly discount its answers based on its prior quote-hunting hallucinations.<br>Yet here’s the thing: AI is genuinely good at some tasks. Scoped tasks, especially. AI is great as fuzzy search, good at finding “this and things similar to this” in a text that you’d never find with standard exact-word search. It’s good as a first-pass proofreader, as long as you ask it for suggestions and don’t let it rewrite your text for you. It just feels worse—or rather, its generalizations and mistakes are more apparent—the more expertise you have in a field. Thus how impressive AI seems at proofreading, programming, or prose is likely inversely correlated with how proficient you are in those skills.<br>The Economist doesn’t have to publish inaccuracies to run up against Knoll’s observation. It’s that everything contains multitudes, and that there is more nuance to almost everything than any cursory coverage could detail. Thus the expert reader recognizes the causes and potential effects, and feels that the piece doesn’t cover enough detail to make the full case. But when you don’t...