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AI assistants misrepresent news content 45% of the time

(www.bbc.co.uk)
421 points sohkamyung | 2 comments | 22 Oct 25 13:39 UTC | HN request time: 0s | source
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scarmig ◴[22 Oct 25 14:46 UTC] No.45669929[source]▶
If you dig into the actual report (I know, I know, how passe), you see how they get the numbers. Most of the errors are "sourcing issues": the AI assistant doesn't cite a claim, or it (shocking) cites Wikipedia instead of the BBC.

Other issues: the report doesn't even say which particular models it's querying [ETA: discovered they do list this in an appendix], aside from saying it's the consumer tier. And it leaves off Anthropic (in my experience, by far the best at this type of task), favoring Perplexity and (perplexingly) Copilot. The article also intermingles claims from the recent report and the one on research conducted a year ago, leaving out critical context that... things have changed.

This article contains significant issues.

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afavour ◴[22 Oct 25 14:47 UTC] No.45669943[source]▶
> or it (shocking) cites Wikipedia instead of the BBC.

No... the problem is that it cites Wikipedia articles that don't exist.

> ChatGPT linked to a non-existent Wikipedia article on the “European Union Enlargement Goals for 2040”. In fact, there is no official EU policy under that name. The response hallucinates a URL but also, indirectly, an EU goal and policy.

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hnuser123456 ◴[22 Oct 25 15:01 UTC] No.45670184[source]▶
Do we have any good research on how much less often larger, newer models will just make stuff up like this? As it is, it's pretty clear LLMs are categorically not a good idea for directly querying for information in any non-fiction-writing context. If you're using an LLM to research something that needs to be accurate, the LLM needs to be doing a tool call to a web search and only asked to summarize relevant facts from the existing information it can find, and have them be cited by hard-coding the UI to link the pages the LLM reviewed. The LLM itself cannot be trusted to generate its own citations. It will just generate something that looks like a relevant citation, along with whatever imaginary content it wants to attribute to this non-existent source.
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jacobolus ◴[22 Oct 25 15:18 UTC] No.45670469[source]▶
A further problem is that Wikipedia is chock full of nonsense, with a large proportion of articles that were never fact checked by an expert, and many that were written to promote various biased points of view, inadvertently uncritically repeat claims from slanted sources, or mischaracterize claims made in good sources. Many if not most articles have poor choice of emphasis of subtopics, omit important basic topics, and make routine factual errors. (This problem is not unique to Wikipedia by any means, and despite its flaws Wikipedia is an amazing achievement.)

A critical human reader can go as deep as they like in examining claims there: can look at the source listed for a claim, can often click through to read the claim in the source, can examine the talk page and article history, can search through the research literature trying to figure out where the claim came from or how it mutated in passing from source to source, etc. But an AI "reader" is a predictive statistical model, not a critical consumer of information.

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hunterpayne ◴[22 Oct 25 18:33 UTC] No.45673271[source]▶
Wikipedia is pretty good for most topics. Anything even remotely political somewhere however, it isn't just bad, it is one of the worst sources out there. And therein lies the problem, its wildly different levels of quality depending on the topic.
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1. mikkupikku ◴[22 Oct 25 20:27 UTC] No.45674728[source]▶
Wikipedia is bad even for topics that aren't particularly political, not even because the editor was trying to be misleading but rather was being lazy and wrote up their own misconception and either made up a source or pulled a source without bothering to actually read it. These kind of errors can stay in place for years.

I have one example that I check periodically just to see if anybody else has noticed. I've been checking it for several years and it's still there; the SDI page claims that Brilliant Pebbles was designed to use "watermelon sized" tungsten projectiles. This is completely made up; whoever wrote it up was probably confusing "rods from god" proposals that commonly use tungsten and synthesizing that confusion with "pebbles". The sentence is cited but the sources don't back it up. It's been up like this for years. This error has been repeated on many websites now, all post-dating the change on wikipedia.

If you're reading this and are the sort to edit wikipedia.. Don't fix it. That would be cheating.

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2. wahern ◴[22 Oct 25 23:28 UTC] No.45676455[source]▶
> If you're reading this and are the sort to edit wikipedia.. Don't fix it. That would be cheating.

Imagine if this was the ethos regarding open source software projects. Imaging Microsoft saying 20 years ago, "Linux has this and that bug, but you're not allowed to go fix it because that detracts from our criticism of open source." (Actually, I wouldn't be surprised if Microsoft or similar detractors literally said this.)

Of course Wikipedia has wrong information. Most open source software projects, even the best, have buggy, shite code. But these things are better understood not as products, but as processes, and in many (but not all) contexts the product at any point in time has generally proven, in a broad sense, to outperform their cathedral alternatives. But the process breaks down when pervasive cynicism and nihilism reduce the number of well-intentioned people who positively engage and contribute, rather than complain from the sidelines. Then we land right back to square 0. And maybe you're too young to remember what the world was like at square 0, but it sucked in terms of knowledge accessibility, notwithstanding the small number of outstanding resources--but which were often inaccessible because of cost or other barriers.