[HN Gopher] AI assistants misrepresent news content 45% of the time
___________________________________________________________________
AI assistants misrepresent news content 45% of the time
Author : sohkamyung
Score : 389 points
Date : 2025-10-22 13:39 UTC (9 hours ago)
(HTM) web link (www.bbc.co.uk)
(TXT) w3m dump (www.bbc.co.uk)
| fallingfrog wrote:
| Yeah I don't know why people pay attention to those things, in
| terms of accuracy you might as well give your uncle 5 or 6 beers
| and tell him to just go off.
| MangoToupe wrote:
| Now let's run this experiment against the editorial boards in
| newsrooms.
|
| Obviously, AI isn't an improvement, but people who blindly trust
| the news have always been credulous rubes. It's just that the
| alternative is being completely ignorant of the worldviews of
| everyone around you.
|
| Peer-reviewed science is as close as we can get to good consensus
| and there's a lot of reasons this doesn't work for reporting.
| n4r9 wrote:
| I guess the claim is not that rubes did not used to exist, but
| rather that technology is increasingly encouraging and
| streamlining rubism.
| MangoToupe wrote:
| I agree with that assessment, or at least that this is indeed
| the claim.
|
| But, technology also gave us the internet, and social media.
| Yes, both are used to propagate misinformation, but it also
| laid bare how _bad_ traditional media was at both a)
| representing the world competently and b) representing the
| opinions and views of our neighbors. Manufacturing consent
| has never been so difficult (or, I suppose, so irrelevant to
| the actions of the states that claim to represent us).
| intended wrote:
| Technology has been used to absolutely decimate the news
| media. Organizations like Fox have blazed the path forward
| for how news organizations succeed in the cable and later
| internet worlds.
|
| You just give up on uneconomical efforts at accuracy and
| you sell narratives that work for one political party or
| the other.
|
| It is a model that has been taken up world over. It just
| works. "The world is too complex to explain, so why
| bother?"
|
| And what will you or me do about it? Subscribe to the NYT?
| Most of us would rather spend that money on a GenAI
| subscription because that is bucketed differently in our
| heads.
| walkabout wrote:
| I decided about a decade ago that McLuhan was a prophet, and
| that the "message" of the Internet may not include
| compatibility with democracy, as it turns out.
| raincole wrote:
| Yep.
|
| How could a candidate who yelling "Fake News" like an idiot get
| elected? Because of the state of journalism.
|
| How could people turn to AI slop? Because of the state of human
| slop.
| falcor84 wrote:
| > Peer-reviewed science is as close as we can get to good
| consensus
|
| I think we're on the same side of this, but I just want to say
| that we can do a lot better. As per studies around the
| Replication Crisis over the last decade [0], and particularly
| this 2016 survey conducted by Monya Baker from Nature [1]:
|
| > 1,576 researchers who took a brief online questionnaire on
| reproducibility found that more than 70% of researchers have
| tried and failed to reproduce another scientist's experiment
| results (including 87% of chemists, 77% of biologists, 69% of
| physicists and engineers, 67% of medical researchers, 64% of
| earth and environmental scientists, and 62% of all others), and
| more than half have failed to reproduce their own experiments.
|
| We need to expect better, needing both better incentives and
| better evaluation, and I think that AI can help with this.
|
| [0] https://en.wikipedia.org/wiki/Replication_crisis
|
| [1] https://www.nature.com/articles/533452a
| vidarh wrote:
| > Now let's run this experiment against the editorial boards in
| newsrooms.
|
| Or against people in general.
|
| It's a pet peeve of mine that we get these kinds of articles
| without a _baseline_ established of how _people_ do on the same
| measure.
|
| Is misrepresenting news content 45% of the time better or worse
| than the average person? I don't know.
|
| By extension: Would a person _using_ an AI assistant
| misrepresent news more or less _after_ having read a summary of
| the news provided by an AI assistant? I don 't know that
| either.
|
| When they have a "Why this distortion matters" section, those
| things matter. They've not established if this will make things
| better or worse.
|
| (the cynic in me want another question answered too: How often
| does _reporters_ misrepresent the news? Would it be better or
| worse if AI reviewed the facts and presented them vs. letting
| reporters do it? again: no idea)
| JumpCrisscross wrote:
| > _It 's a pet peeve of mine that we get these kinds of
| articles without a baseline established of how people do on
| the same measure_
|
| I don't have a personal human news summarizer?
|
| The comparison is between a human reading the primary source
| against the same human reading an LLM hallucination mixed
| with an LLM referring the primary source.
|
| > _cynic in me want another question answered too: How often
| does reporters misrepresent the news?_
|
| The fact that you mark as cynical a question answered pretty
| reliably for most countries sort of tanks the point.
| vidarh wrote:
| > I don't have a personal human news summarizer?
|
| Not a personal one. You do however have reporters sitting
| between you and the source material a lot of the time, and
| sometimes _multiple levels_ of reporters playing games of
| telephone with the source material.
|
| > The comparison is between a human reading the primary
| source against the same human reading an LLM hallucination
| mixed with an LLM referring the primary source.
|
| In modern news reporting, a fairly substantial proportion
| of what we digest is not primary sources. It's not at all
| clear whether an LLM summarising primary sources would be
| better or worse than reading a reporter passing on primary
| sources. And in fact, in many cases the news is not even
| secondary sources - e.g. a wire service report on primary
| sources getting rewritten by a reporter is not uncommon.
|
| > The fact that you mark as cynical a question answered
| pretty reliably for most countries sort of tanks the point.
|
| It's a cynical point within the context of this article to
| point out that it is meaningless to report on the accuracy
| of AI in isolation because it's not clear that human
| reporting is better for us. I find it kinda funny that you
| dismiss this here, after having downplayed the games of
| telephone that news reporting often is earlier in your
| reply, thereby making it quite clear I am in fact being a
| lot more cynical than you about it.
| JumpCrisscross wrote:
| > _You do however have reporters sitting between you and
| the source material a lot of the time_
|
| In cases where a reporter is just summarising _e.g._ a
| court case, sure. Stock market news has been automated
| since the 2000s.
|
| More broadly, AI assistants misrepresenting news content
| may _sometimes_ direct reference a court case. But they
| often don 't. Even if they only could, that covers a
| small fraction of the news, much of which the AI will
| _need_ to rely on reporters detailing the primary sources
| they 're interfacing with.
|
| Reporter error is somewhat orthogonal to AI assistants'
| accuracy.
| MangoToupe wrote:
| > Reporter error is somewhat orthogonal to AI assistants'
| accuracy.
|
| It is not at all. Journalists are wrong all the time, but
| you still treat news like record and not a sample. In
| fact I'd put money that AI mischaracterizes events at a
| LOWER rate than AI does: narratives shift over time, and
| journalists are more likely to succumb to this shift.
| MangoToupe wrote:
| > I don't have a personal human news summarizer?
|
| Is this not the editorial board and journalist? I'm not
| sure what the gripe is here.
| n4r9 wrote:
| The difference is the ease with which AI can be rolled out,
| scaled up, and woven into the fabric of our interactions with
| society.
| vidarh wrote:
| That makes understanding the baseline all the more
| important. It could be a disaster, or it could in fact be a
| distinct improvement. Every time someone pushes a
| breathless headline about failure rates of AI without
| comparing it to a human baseline, they are in essence
| _potentially misleading us_ because without that baseline
| we don 't know whether it's better or worse.
| n4r9 wrote:
| I disagree. Comparison with human baseline is basically
| irrelevant. AI will be used in so many more ways and at
| so much greater scale that the failure rate has to stand
| alone as extraordinarily low regardless of human
| abilities.
| falcor84 wrote:
| > 45% of all AI answers had at least one significant issue.
|
| > 31% of responses showed serious sourcing problems - missing,
| misleading, or incorrect attributions.
|
| > 20% contained major accuracy issues, including hallucinated
| details and outdated information.
|
| I'm generally against whataboutism, but here I think we
| absolutely have to compare it to human-written news reports.
| Famously, Michael Crichton introduced the "Gell-Mann amnesia
| effect" [0], saying:
|
| > Briefly stated, the Gell-Mann Amnesia effect works as follows.
| You open the newspaper to an article on some subject you know
| well. In Murray's case, physics. In mine, show business. You read
| the article and see the journalist has absolutely no
| understanding of either the facts or the issues. Often, the
| article is so wrong it actually presents the story backward--
| reversing cause and effect. I call these the "wet streets cause
| rain" stories. Paper's full of them.
|
| This has absolutely been my experience. I couldn't find proper
| figures, but I would put good money on significantly over 45% of
| articles written in human-written news articles having "at least
| one significant issue".
|
| [0] https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect
| AyyEye wrote:
| Human news isn't a good comparison because this is second order
| -- LMMs are downstream of human news. It's a game of stochastic
| telephone. All the human error is carried through with
| additional hallucinations on top.
| falcor84 wrote:
| But the issue is that the vast majority of "human news" is
| second order (at best), essentially paraphrasing releases by
| news agencies like Reuters or Associated Press, or scientific
| articles, and typically doing a horrible job at it.
|
| Regarding scientific reporting, there's as usual a relevant
| xkcd ("New Study") [0], and in this case even better, there's
| a fabulous one from PhD Comics ("Science News Cycle") [1].
|
| [0] https://xkcd.com/1295/
|
| [1] https://phdcomics.com/comics/archive.php?comicid=1174
| Vetch wrote:
| Then the point still stands, this makes things even worse
| given that it's adding its own hallucinations on top,
| instead of simply relaying the content or idealistically,
| identifying issues in the reporting.
| dgfitz wrote:
| You understand that an LLM can only poorly regurgitate
| whatever it's fed right? An LLM will _always_ be less
| useful than a primary/secondary source, because they can't
| fucking think.
| falcor84 wrote:
| Regardless of how you define "think", you still need to
| get a baseline of whether human reporters do that
| effectively.
| bgwalter wrote:
| I'd say the 45% is on top of mistakes by Journalists
| themselves. "AI" takes certain newspapers as gospel, and it is
| easy to find omissions, hallucinations, misunderstandings etc.
| without even fact checking the original articles.
| bux93 wrote:
| The problem highlighted here is that AI summaries misrepresent
| the original stories. This just opens a flood gate of slop that
| is 45% worse than the source, which wasn't stellar to begin
| with as you point out.
| vidarh wrote:
| A whole lot of news is regurgiated wire service reports, so
| how reporters do matters greatly - if they're doing badly,
| then it's entirely possible that an AI summary of the wire
| service releases would be an improvement (probably not, but
| without a baseline we don't know)
|
| It's also not clear if humans do better when consuming
| either, and whether the effect of an AI summary, even with
| substantial issues, is to make the human reading them better
| or worse informed.
|
| E.g. if it helps a person digest more material by getting
| more focused reports, it's entirely possible that flawed
| summaries would still in aggregate lead to a better
| understanding of a subject.
|
| On its own, this article is just pure sensationalism.
| intended wrote:
| Yes, I absolutely see the case for the faster, cheaper, more
| efficient solution at making random content.
|
| Why stop at what humans can do? AND to not be fettered by any
| expectations of accuracy, or even feasibility of retractions.
|
| Truly, efficiency unbound.
| wat10000 wrote:
| That's not comparable. Reading news reports and summarizing
| them is about a thousand times easier than writing those news
| reports in the first place. If you want to see how humans fare
| at this task, have some people answer questions about the news
| and then compare their answers to the original reporting. I'm
| not sure if the average human would fare too well at this
| either, but it's completely different from the question of how
| accurate the original news itself is.
| more_corn wrote:
| Only 45%? That seems low from my experience.
| delaminator wrote:
| According to PEW that's about the same % that trust the BBC's
| reporting.
|
| https://www.pewresearch.org/journalism/fact-sheet/news-media...
| afavour wrote:
| Which is a completely different issue. "Do I trust this news
| network?" is a subjective opinion. Flat out misstating facts
| and inventing sources is a much more significant problem.
| sofixa wrote:
| You seem to be looking at the wrong chart. Around ~50% each of
| each politically leaning group use BBC as their primary news
| source.
|
| However, 79% of Brits trust the BBC as per this chart:
|
| https://legacy.pewresearch.org/wp-content/uploads/sites/2/20...
| GordonS wrote:
| That was back in 2017, if I'm reading the chart correctly. A
| _lot_ has changed since then, so I 'd be genuinely curious to
| see what more recent figures looked like.
| parineum wrote:
| And if they made up 45% of their stories, I imagine their trust
| would be 0%.
| myrmidon wrote:
| Did you mean the Guardian? Because trust in BBC is at ~80%
| according to what you linked.
| alcide wrote:
| Kagi News has been pretty accurate. Source information is
| provided along with the summary and key details too.
|
| AI summarizes are good for getting a feel of if you want to read
| an article or not. Even with Kagi News I verify key facts myself.
| delusional wrote:
| What if the AI makes an interesting or important article sound
| like one you don't want to read? You'd never cross check the
| fact, and you'd never discover how wrong the AI was.
| alcide wrote:
| Integrity of words and author intent is important. I
| understand the intent of your hypothetical but I haven't run
| into this issue in practice with Kagi News.
|
| Never share information about an article you have not read.
| Likewise, never draw definitive conclusions from an article
| that is not of interest.
|
| If you do not find a headline interesting, the take away is
| that you did not find the headline interesting. Nothing more,
| nothing less. You should read the key insights before
| dismissing an article entirely.
|
| I can imagine AI summarizes being problematic for a class of
| people that do not cross check if an article is of value to
| them.
| latexr wrote:
| > I can imagine AI summarizes being problematic for a class
| of people that do not cross check if an article is of value
| to them.
|
| I feel like that's "the majority of people" or at least "a
| large enough group for it to be a societal problem".
| unshavedyak wrote:
| That's fair, but i also don't cross check news sources on
| average either. I should, but there in lies the real problem
| imo. Information is war these days, and we've not yet
| developed tools for wading through immense piles of subtly
| inaccurate or biased data.
|
| We're in a weird time. It's always been like this, it's just
| much.. more, now. I'm not sure how we'll adapt.
| delusional wrote:
| > Information is war these days
|
| I don't know If i can agree with that. I think we make an
| error when we aggregate news in the way we do. We claim
| that "the right wing media" says something when a single
| outlet associated with the right says a thing, and vice
| versa. That's not how I enjoy reading the news. I have a
| couple of newspapers I like reading, and I follow the
| arguments they make. I don't agree with what they say half
| the time, but I enjoy their perspective. I get a sense of
| the "editorial personality" of the paper. When we aggregate
| the news, we don't get that sense, because there's no
| editorial. I think that makes the news poorer, and I think
| it makes people's views of what newspapers can be poorer.
|
| The news shouldn't a stream of happenings. The newspaper is
| best when it's a coherent day-to-day conversation. Like a
| pen-pal you don't respond to.
| jabroni_salad wrote:
| There is more written material produced every hour than I
| could read in a lifetime, I am going to miss 99.9999% of
| everything no matter what I do. It's not like the
| headline+blurb you usually get is any better in this regard.
| thm wrote:
| Or https://rawdiary.com
| jjtheblunt wrote:
| agreed on Kagi News, and Particle News has been good, but they
| accepted funding from The Atlantic which evidently earns
| "Featured Article" positioning to articles from funding
| sources, muddying the clarity of biases, which Particle News
| has a nice graphic indicator for, though i've not seen it under
| promoted Feature Articles. Surely applies to other funding
| sources, but The Atlantic one was pretty recent.
| brabel wrote:
| How do you verify a fact? Do you travel to the location and
| interview the locals? Or read scientific papers in various
| fields, including their own references, to validate summaries
| published by news sources? At some point you need to just trust
| that someone is telling the truth.
| latexr wrote:
| I'm pretty sure what the what your parent comment means is
| they verify that key facts outputted by the summary match
| what's written in the source.
| pwlm wrote:
| It may help to set penalties for someone not telling the
| truth.
| dan_h wrote:
| I've has a similar experience with my own project that
| summarizes rss articles--the results have largely been pretty
| good, but I found using a "reasoning" model had much better
| results.
| raffael_de wrote:
| Kagi News is basically a summary of news articles fed into the
| context. It's different from what the op is about, that is just
| asking an LLM with web access to query the news.
| Spivak wrote:
| I hate saying people are holding it wrong but given just
| given how LLMs work, how did anyone expect that this would go
| right? Managing the LLM's context is the game. I feel like
| ChatGPT has done such a disservice for teaching users how to
| actually use these tools and what their failure modes are.
| visarga wrote:
| I recently tried to get Gemini to collect fresh news and show
| them to me, and instead of using search it hallucinated
| everything wholesale, titles, abstracts and links. Not just once,
| multiple times. I am kind of afraid of using Gemini now for
| anything related to web search.
|
| Here is a sample:
|
| > [1] Google DeepMind and Harvard researchers propose a new
| method for testing the 'theory of mind' of LLMs - Researchers
| have introduced a novel framework for evaluating the "theory of
| mind" capabilities in large language models. Rather than relying
| on traditional false-belief tasks, this new method assesses an
| LLM's ability to infer the mental states of other agents
| (including other LLMs) within complex social scenarios. It
| provides a more nuanced benchmark for understanding if these
| systems are merely mimicking theory of mind through pattern
| recognition or developing a more robust, generalizable model of
| other minds. This directly provides material for the
| construct_metaphysics position by offering a new empirical tool
| to stress-test the computational foundations of consciousness-
| related phenomena.
|
| > https://venturebeat.com/ai/google-deepmind-and-harvard-resea...
|
| The link does not work, the title is not found in Google Search
| either.
| luckydata wrote:
| Gemini is notoriously bad at tool calling and it's also widely
| speculated that 3.0 will put an emphasis on fixing that.
| wat10000 wrote:
| They can be good for search, but you _must_ click through the
| provided links and verify that they actually say what it says
| they do.
| bloppe wrote:
| The problem is that 90% of people will not do that once
| they've satisfied their confirmation bias. Hard to say if
| that's going to be better or worse than the current echo
| chamber effects of the Internet. I'm still holding out for
| better, but certainly this is shaking that assumption
| hunterpayne wrote:
| So this probably is valid. However, so is Gell-Mann amnesia
| and both phenomena happen a lot. There are topics where one
| side is the group of people who have attempted to
| understand a problem and the other side are people who
| either do not or won't due to emotions. Acting as if it is
| all confirmation bias feels good but probably isn't the
| best way to look at the media.
| reaperducer wrote:
| _They can be good for search, but you must click through the
| provided links and verify that they actually say what it says
| they do._
|
| Then they're not very good at search.
|
| It's like saying the proverbial million monkeys at
| typewriters are good at search because eventually they type
| something right.
| wat10000 wrote:
| Huh? All the classic search engines required you to click
| through the results and read them. There's nothing wrong
| with that. What's different is that LLMs will give you a
| summary that might make you think you can get away with not
| clicking through anymore. This is a mistake. But that
| doesn't mean that the search itself is bad. I've had plenty
| of cases where an LLM gave me incorrect summaries of search
| results, and plenty of cases where it found stuff I had a
| hard time finding on my own because it was better at
| figuring out what to search for.
| Yizahi wrote:
| But LLM can't collect anything. It can generate the most likely
| characters in a row. What exactly did you expect from it?
| layer8 wrote:
| Current LLM offerings use realtime web search to collect
| information and answer questions.
| bongodongobob wrote:
| LLMs have been able to search the web for a couple years now.
| HWR_14 wrote:
| Why would you want Gemini to do this instead of just going to a
| news site (or several news sites) and reading what the
| headlines they wrote?
| visarga wrote:
| I wanted to use the agentic powers of the model to dig for
| specific kinds of news, and use iterative search as well. I
| think when LLMs use tools correctly this kind of search is
| more powerful than simple web search. It also has better
| semantic capabilities, so in a way I wanted to make my own
| LLM powered news feed.
| HWR_14 wrote:
| That's makes sense. Thanks for explaining!
| SrslyJosh wrote:
| > I wanted to use the agentic powers of the model
|
| Do you have an in-depth understanding of how those "agentic
| powers" are implemented? If not, you should probably
| research it yourself. Understanding what's underneath the
| buzzwords will save you some disappointment in the future.
| ModernMech wrote:
| They're selling it as having this ability, so it really
| doesn't matter what people _want_. We should be holding these
| companies to account for selling software that doesn 't live
| up to what they say it does.
| mckngbrd wrote:
| What version of Gemini were you using? i.e. were you calling it
| locally via the API or thru their Gemini or AI Studio web apps?
|
| Not every LLM app has access to web / news search capabilities
| turned on by default. This makes a huge difference in what kind
| of results you should expect. Of course, the AI should be aware
| that it doesn't have access to web / news search, and it should
| tell you as much rather than hallucinating fake links. If
| access to web search was turned on, and it still didn't
| properly search the web for you, that's a problem as well.
| visarga wrote:
| Gemini 2.5 Pro and it was this month, so probably the latest
| version.
| burnte wrote:
| About 75% of the time I look at the Gemini answer, it's wrong.
| Maybe 80%. Sometimes it's a little wrong, like giving the
| correct answer for another product/item, or the times that a
| business is open wrong. There's a local business I took my wife
| to, Gemini told her it's open monday to friday, but it's open
| tuesday to saturday, so we showed up on a monday to see them
| closed. But sometimes it's insanely wrong making up dozens of
| wrong "facts". My wife started looked more carefully now. My
| boss will even say "Gemini says X so it's probably Y" these
| days.
| everdrive wrote:
| It's important to bear this in mind whenever you find out that
| someone uses an LLM to summarize a meeting, email, or other
| communication you've held. That person is not really getting the
| message you were conveying.
| delusional wrote:
| That's a scary thought to me. They're not just outsourcing
| their thinking. They are actively sabotaging the only tool in
| their arsenal that could ever supplant it.
|
| I've felt it myself. Recently I was looking as some
| documentation without a clear edit history. I thought about
| feeding it into an AI and having it generate one for me, but
| didn't because I didn't have the time. To think, if I had done
| that, it probably would have generated a perfectly acceptable
| edit history but one that would have obscured what changes were
| actually made. I wouldn't just lack knowledge (like I do now) I
| would have obtained anti knowledge.
| zamadatix wrote:
| You've gotta be careful using "not just X, but Y" these days
| ;).
| senordevnyc wrote:
| It would be important to bear this in mind if it was true, but
| it's not.
|
| I do sales meetings all day every day, and I've tried different
| AI note takers that send a summary of the meeting afterwards. I
| skim them when they get dumped into my CRM and they're almost
| always quite accurate. And I can verify it, because _I was in
| the meeting_.
| cheeze wrote:
| It makes me think that a lot of the folks commenting on this
| stuff haven't actually used the tooling.
|
| Agreed, it's generally quite accurate. I find for hectic
| meetings, it can get some things wrong... But the notes are
| generally still higher quality than human generated notes.
|
| Is it perfect? No. Is it good enough? IMO absolutely.
|
| Similar to many other things, the key is that you don't just
| blindly trust it. Have the LLM take notes and summarize, and
| then _proofread_ them, just as you would if you were writing
| them yourself...
| hunterpayne wrote:
| I think the cost of inaccuracy is very a important factor
| in if it works for a specific use case. Meeting notes
| probably don't have much cost of inaccuracy. Medical
| records on the other hand...
| bongodongobob wrote:
| We have been using MS Copilot in our meetings for months and it
| does a very good job summarizing who said what and who has what
| deliverables. It's extremely useful and I've found it to be
| very accurate.
| ajsnigrutin wrote:
| Considering it's EBU with national media (usually taxpayer paid,
| or paid by some other mandatory way), it would be more
| interesting if they focused on what the media is reporting now,
| with human reporters and misleading and other kinds of false
| reportings. If the frontpage article said something wrong (either
| by malice or accident), there should be a frontpage article
| reporting about their error too.
|
| Optimistically that could be extended "twitter-style" by
| mandatory basic fact checking and reports when they just copy a
| statement by some politician or misrepresented science stuff
| (xkcd 1217, X cures cancer), and add the corrections.
|
| But yeah... in my country, with all the 5G-danger craze, we had
| TV debates with a PhD in telecommunications on one side, and a
| "building biologist" on the other, so yeah...
| retinaros wrote:
| In other words they are more factual than the bbc
| jsheard wrote:
| LLMs aren't doing journalism on their own, whatever mistakes
| they make are compounded _on top of_ any mistakes that the
| actual sources (such as the BBC) might have made.
| bparsons wrote:
| One thing that makes me pessimistic about the short term utility
| of LLMs has been their inability to produce basic media
| monitoring documents. This is an intern type entry level task
| that it simply cannot complete with any reliability or
| consistency. It doesn't matter if I use the expensive paid
| services or spend dozens of prompts trying to configure, it
| simply wont produce a document that is of any use to me.
|
| If that is the case with a task so simple, why would we rely on
| these tools for high risk applications like medical diagnosis or
| analyzing financial data?
| cek wrote:
| From the report:
|
| > This time, we used the free/consumer versions of ChatGPT,
| Copilot, Perplexity and Gemini.
|
| IOW, they tested ChatGPT twice (Copilot uses ChatGPT's models)
| and didn't test Grok (or others).
| scarmig wrote:
| 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.
| afavour wrote:
| > 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.
| scarmig wrote:
| > Participating organizations raised concerns about responses
| that relied heavily or solely on Wikipedia content - Radio-
| Canada calculated that of 108 sources cited in responses from
| ChatGPT, 58% were from Wikipedia. CBC-Radio-Canada are
| amongst a number of Canadian media organisations suing
| ChatGPT's creator, OpenAI, for copyright infringement.
| Although the impact of this on ChatGPT's approach to sourcing
| is not explicitly known, it may explain the high use of
| Wikipedia sources.
|
| Also, is attributing, without any citation, ChatGPT's
| preference for Wikipedia to a reprisal to an active lawsuit a
| significant issue? Or do the authors get off scot-free
| because they caged it in "we don't know, but maybe it's the
| case"?
| ffsm8 wrote:
| Literally constantly? It takes both careful prompting and
| throughout double-checking to really notice however.
| Because often the links also exist, just don't represent
| what the LLM made it sound like.
|
| And the worst part about the people unironically thinking
| they can use it for "research" is, that it essentially
| supercharges confirmation bias.
|
| The inefficient sidequests you do while researching is
| generally what actually gives you the ability to really
| reason about a topic.
|
| If you instead just laser focus on the tidbits you prompted
| with... Well, your opinion is a lot less grounded.
| edavison1 wrote:
| Ran into this the other day researching a brewery. Google
| AI summary referenced a glowing NYT profile of its beers.
| The linked article was not in fact about that brewery,
| but an entirely different one. Brewery I was researching
| has never been mentioned in the NYT. Complete invention
| at that point and has 'stolen' the good press from a
| different place and just fed the user what they wanted to
| see, namely a recommendation for the thing I was
| googling.
| terminalshort wrote:
| It's a huge issue. No wonder AI hallucinates when it trains
| on this kind of crap.
| kenjackson wrote:
| Actually there was a Wikipedia article of this name, but it
| was deleted in June -- because it was AI generated.
| Unfortunately AI falls for this much like humans do.
|
| https://en.wikipedia.org/wiki/Wikipedia:Articles_for_deletio.
| ..
| Workaccount2 wrote:
| This is likely because of the knowledge cutoff.
|
| I have seen a few cases before of "hallucinations" that
| turned out to be things that did exist, but no longer do.
| 1980phipsi wrote:
| The fix for this is for the AI to double-check all links
| before providing them to the user. I frequently ask
| ChatGPT to double check that references actually exist
| when it gives me them. It should be built in!
| rideontime wrote:
| But that would mean OpenAI would lose even more money on
| every query.
| mdhb wrote:
| Almost as though it's not a sustainable business model
| and relies of tricking people in order to keep the lights
| on.
| ModernMech wrote:
| Better make each query count then.
| blitzar wrote:
| I have found my self doing the same "citation needed"
| loop - but with ai this is a dangerous game as it will
| now double down on whatever it made up and go looking for
| citations to justify its answer.
|
| Pre prompting to cite sources is obviously a better way
| of going about things.
| janwl wrote:
| I thought people here hated it when LLMs made http
| requests?
| macintux wrote:
| I don't know for certain what you're referring to, but
| the "bulk downloads" of the Internet that AI companies
| are executing for training are the problem I've seen
| cited, and doesn't relate to LLMs checking their sources
| at query time.
| zahlman wrote:
| It's bad when they indiscriminately crawl for training,
| and not ideal (but understandable) to use the Internet to
| communicate with them (and having online accounts
| associated with that etc.) rather than running them
| locally.
|
| It's not bad when they use the Internet at generation
| time to verify the output.
| dingnuts wrote:
| Gemini will lie to me when I ask it to cite things,
| either pull up relevant sources or just hallucinate them.
|
| IDK how you people go through that experience more than a
| handful of times before you get pissed off and stop using
| these tools. I've wasted so much time because of
| believable lies from these bots.
|
| Sorry, not even lies, just bullshit. The model has no
| conception of truth so it can't even lie. Just outputs
| bullshit that happens to be true sometimes.
| bunderbunder wrote:
| The biggest problem with that citation isn't that the
| article has since been deleted. The biggest problem is that
| that particular Wikipedia article was never a good source
| in the first place.
|
| That seems to be the real challenge with AI for this use
| case. It has no real critical thinking skills, so it's not
| really competent to choose reliable sources. So instead
| we're lowering the bar to just asking that the sources
| actually exist. I really hate that. We shouldn't be
| lowering intellectual standards to meet AI where it's at.
| These intellectual standards are important and hard-won,
| and we need to be demanding that AI be the one to rise to
| meet them.
| gamerDude wrote:
| I think this is a real challenge for everyone. In many
| ways potentially we need a restart of a wikipedia like
| site to document all the valid and good sources. This
| would also hopefully include things like source bias and
| whether it's a primary/secondary/tertiary source.
| fullofideas wrote:
| This is pushing the burden of proof on the society.
| Basically, asking everyone else to pitch in and improve
| sources so that ai companies can reference these trust
| worthy sources.
| bunderbunder wrote:
| Outsourcing due diligence to a tool (or a single unified
| source) is the problem, not the solution.
|
| For example, having a single central arbiter of source
| bias is inescapably the most biased thing you could
| possibly do. Bias has to be defined within an
| intellectual paradigm. So you'd have to choose a paradigm
| to use for that bias evaluation, and _de facto_ declare
| it to be the one true paradigm for this purpose. But
| intellectual paradigms are inherently subjective, so
| doing that is pretty much the most intellectually biased
| thing you can possibly do.
| ishtanbul wrote:
| Maybe we can get AI to do this hard labor
| dingnuts wrote:
| I noticed that my local library has a new set of World
| Book. Maybe it's time to bring back traditional
| encyclopedias.
| cogman10 wrote:
| An example of this.
|
| I've seen a certain sensationalist news source write a
| story that went like this.
|
| Site A: Bad thing is happening, cite: article Site B
|
| * follow the source *
|
| Site B: Bad thing is happening, cite different article on
| Site A
|
| * follow the source *
|
| Site A: Bad thing is happening, no citation.
|
| I fear that's the current state of a large news bubble
| that many people subscribe to. And when these
| sensationalist stories start circulating there's a
| natural human tendency to exaggerate.
|
| I don't think AI has any sort of real good defense to
| this sort of thing. 1 level of citation is already hard
| enough. Recognizing that it is citing the same source is
| hard enough.
|
| There was another example from the Kagi news stuff which
| exemplified this. A whole article written which made 3
| citations that were ultimately spawned from the same new
| briefing published by different outlets.
|
| I've even seen an example of a national political leader
| who fell for the same sort of sensationalization. One who
| should have known better. They repeated what was later
| found to be a lie by a well-known liar but added that
| "I've seen the photos in a classified debriefing". IDK
| that it was necessarily even malicious, I think people
| are just really bad at separating credible from
| uncredible information and that it ultimately blends
| together as one thing (certainly doesn't help with
| ancient politicians).
| kenjackson wrote:
| I get what your saying. But you are now asking for a
| level of intelligence and critical thinking that I
| honestly believe is higher than the average person. I
| think its absolutely doable, but I also feel like we
| shouldn't make it sound like the current behavior is
| abhorrent or somehow indicative of a failure in the
| technology.
| exe34 wrote:
| It's actually great from my point of view - it means
| we're edging our way into limited superintelligence.
| CaptainOfCoit wrote:
| > Actually there was a Wikipedia article of this name, but
| it was deleted in June -- because it was AI generated.
| Unfortunately AI falls for this much like humans do.
|
| A recent Kurzgesagt goes into the dangers of this, and they
| found the same thing happening with a concrete example:
| They were researching a topic, tried using LLMs, found they
| weren't accurate enough and hallucinated, so they continued
| doing things the manual way. Then some weeks/months later,
| they noticed a bunch of YouTube videos that had the very
| hallucinations they were avoiding, and now their own AI
| assistants started to use those as sources.
| Paraphrased/remembered by me, could have some
| inconsistencies/hallucinations.
|
| https://www.youtube.com/watch?v=_zfN9wnPvU0
| AlienRobot wrote:
| AI-powered citogenesis!
| menaerus wrote:
| > For the current research, a set of 30 "core" news questions
| was developed
|
| Right. Let's talk about statistics for a bit. Or let's put it
| differently: they found in their report that 45% of the
| answers for 30 questions they have "developed" had a
| significant issue, e.g. inexisting reference
|
| I'll give you 30 questions out of my sleeve where 95% of the
| answers will not have any significant issue.
| matthewmacleod wrote:
| Yes, I'm sure you could hack together some bullshit
| questions to demonstrate whatever you want. Is there a
| specific reason that the reasonably straightforward
| methodology they did use is somehow flawed?
| menaerus wrote:
| Yes, and you answered it yourself.
| darkwater wrote:
| Err, no? Being _possible_ does not necessarily imply
| that's what happened.
| menaerus wrote:
| A bucket of 30 questions is not a statistically
| significant sample size which we can use to support the
| hypothesis which goes to say that all AI assistants they
| tested are 45% of the time wrong. That's not how science
| works.
|
| Neither is my bucket of 30 questions statistcally
| significant but it goes to say that I can disprove their
| hypothesis just by giving them my sample.
|
| I think that the report is being disingenious and I don't
| understand for what reasons. it's funny that they say
| "misrepresent" when that's exactly what they are doing.
| extrabajs wrote:
| Statistically significant... sample size? Support the
| hypothesis?
| hnuser123456 wrote:
| 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.
| jacobolus wrote:
| 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.
| senderista wrote:
| Just the other day, I clicked through to a Wikipedia
| reference (a news article) and discovered that the citing
| sentence grossly misrepresented the source. Probably not
| accidental since it was about a politically charged
| subject.
| zahlman wrote:
| > 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.
|
| Yep.
|
| Including, if not especially, the ones actively worked on
| by the most active contributors.
|
| The process for vetting sources (both in terms of
| suitability for a particular article, and general
| "reliable sources" status) is also seriously problematic.
| Especially when it comes to any topic which fundamentally
| relates to the reliability of journalism and the media in
| general.
| LeifCarrotson wrote:
| A future problem will be that the BBC and the rest of the
| Internet will soon be chock-full of nonsense, with a
| large proportion of articles that were never fact checked
| by a human, much less an AI.
| hunterpayne wrote:
| 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.
| mikkupikku wrote:
| 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.
| bigbuppo wrote:
| The problem is that people are using it as a substitute for
| a web search, and the web search company has decided to
| kill off search as a product and pivot to video, err, I
| mean pivot to AI chatbots so hard they replaced one of the
| common ways to access emergency services on their mobile
| phones with an AI chatbot that can't help you in an
| emergency.
|
| Not to mention, the AI companies have been extremely
| abusive to the rest of the internet so they are often
| blocked from accessing various web sites, so it's not like
| they're going to be able to access legitimate information
| anyways.
| ekidd wrote:
| "Truth" is often a very expensive commodity to obtain.
| There are plenty of awful sources and mistaken claims on
| the shelf of any town library. Lots of peer reviewed papers
| are crap, including a few in Nature. Newspapers are
| constantly wrong and misleading. Digging through even
| "reliable" sources can require significant expertise. (This
| is, in fact, a significant part of PhD training, according
| to the PhDs and professors I know: Learning to use the
| literature well.)
|
| One way to successfully use LLMs is to do the initial
| research legwork. Run the 40 Google searches and follow
| links. Evaluate sources according to some criteria.
| Summarize. And then give the human a list of links to
| follow.
|
| You quickly learn to see patterns. Sonnet will happily give
| a genuinely useful rule of thumb, phrasing it like it's
| widely accepted. But the source will turn out to be "one
| guy on a forum."
|
| There are other tricks that work well. Have the LLM write
| an initial overview with sources. Tell it strictly limit
| itself to information in the sources, etc. Then hand the
| report off to a _fresh_ LLM and tell it to carefully check
| each citation in the report, removing unsourced
| information. _Then_ have the human review the output,
| following links.
|
| None of this will get you guaranteed truth. But if you know
| what you're doing, it can often give you a better starting
| point than Wikipedia or anything on the first two pages of
| Google Search results. Accurate information is genuinely
| hard to get, and it always has been.
| ModernMech wrote:
| > and only asked to summarize relevant facts from the
| existing information it can find
|
| Still not enough as I find the LLM will not summarize _all_
| the relevant facts, sometimes leaving out the most salient
| ones. Maybe you 'll get a summary of some facts, maybe the
| ones you explicitly ask for, but you'll be left wondering
| if the LLM is leaving out important information.
| shinycode wrote:
| I used perplexity for searches and I clicked on all sources
| that were given. Depending on the model used from 100% to 20%
| of the urls I tested did not exist. I kept on querying the
| LLM about it and it finally told me that it generated << the
| most probable >> urls for the topic in question based on the
| ones he knows exists. Useless.
| smrq wrote:
| I share your opinion on the results, but why would you
| trust the LLM explanation for why it does what it does?
| shinycode wrote:
| I don't trust it at all. I wanted to know if he would be
| able to explain its own results. Just because it was
| displaying sources and links made me trust it until I
| checked and was horrified. I wanted to know if it was old
| link that broke or changed but no apparently
| macintux wrote:
| You said:
|
| >...it finally told me that it generated << the most
| probable >> urls for the topic in question based on the
| ones he knows exists.
|
| smrq is asking why you would believe that explanation.
| The LLM doesn't necessarily know why it's doing what it's
| doing, so that could be another hallucination.
|
| Your answer:
|
| > ...I wanted to know if it was old link that broke or
| changed but no apparently
|
| Leads me to believe that you misunderstood smrq's
| question.
| shinycode wrote:
| No I got the question, I said that I wanted to see what
| kind of explanation it would give me. Ofc it can
| hallucinate that explanation as well. The bottom line is
| I don't trust it, and the source link are fake (and not
| broken or obsolete)
| aflag wrote:
| Existing is just a point in time
| FooBarWidget wrote:
| I wouldn't even say BBC is a good source to cite. For foreign
| news, BBC is outright biased. Though I don't have any good
| suggestions for what an LLM _should_ cite instead.
| EA-3167 wrote:
| Ground News or something similar that at least attempts to
| aggregate, compare ownership, bias, and factuality.
|
| Imo at least
| 542458 wrote:
| Reuters or AP IMO. Both take NPOV and accuracy very
| seriously. Reuters famously wouldn't even refer to the 9/11
| hijackers as terrorists, as they wanted to remain as value-
| neutral as possible.
| sdoering wrote:
| In addition to that dpa from Germany for German news. Yes,
| dpa has had issues, but it is in my experience by far the
| source trying to be as non partisan as possible. Not
| necessarily when they sell their online feed business,
| though.
|
| Disclaimer: Started my career in onine
| journalism/aggregation. Hada 4 week internship with the dpa
| online daughter some 16 years ago.
| FooBarWidget wrote:
| It's been a long time since 2001. Are they still value-
| neutral today on foreign news? It seems to me like they're
| heavily biased towards western POV nowadays.
| driverdan wrote:
| Yes, Reuters has good, unbiased international coverage.
| dontlaugh wrote:
| The BBC has a strong right wing bias within the UK too.
|
| There's no such thing as unbiased.
| marcosdumay wrote:
| Well, if it's describing news content, it should cite the
| original news article.
| rkachowski wrote:
| You're downvoted but quite accurate. I would like to see this
| statistic compared against how often the BBC misrepresents
| news content, and the backflips that come with defining such
| a metric.
| scellus wrote:
| Are citation issues related to the fact that
| https://www.bbc.co.uk/robots.txt denies a lot of AI, both user
| agents and crawlers?
| scarmig wrote:
| The report says that different media organizations dropped
| their robots.txt for the duration of the research to give
| LLMs access.
|
| I would expect this isn't the on-off switch they
| conceptualized, but I don't know enough about how different
| LLM providers handle news search and retrieval to say for
| sure.
| dylan604 wrote:
| Does it work like that though? How long does it take for AI
| bots to crawl sites and have the data added to the model
| currently being used? Am I wrong in thinking that it takes
| a lot longer for AI bot crawls to be available to the
| public than a typical search engine crawler?
| rimeice wrote:
| Bots could be crawlers gathering data to periodically be
| used as raw training data or the requests could just be
| from a web search agent of some form like ChatGPT finding
| latest news stories on topic X for example. I don't know
| if robots.txt can distinguish between the two types of
| bot request or whether LLM providers even adhere to
| either.
| jay_kyburz wrote:
| Wow, Just reading the headline I had assumed they were
| giving the new article as a document, then asking it to
| summarize the the document given.
| amarant wrote:
| Human journalists misrepresent the white paper 85% of the time.
|
| With this in mind, 45% doesn't seem so bad anymore
| stmichel wrote:
| You stole my reply haha! However, I was gonna say journalists
| misrepresent papers and other content 95% of the time...
| gerad wrote:
| https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect
| ribosometronome wrote:
| Hell, human editors seem to misrepresent their journalists
| frequently enough that I'm left wondering if it's hyperbolic
| or not to guess if they misrepresent them 45% of the time,
| too.
| SkyBelow wrote:
| Years ago in college, we had a class where we analyzed
| science in the news for a few weeks compared to the publish
| research itself. I think it was a 100% misrepresentation rate
| comparing what a news article summarized about a paper verses
| what the paper itself said. We weren't going off of CNN or
| similar main news sites, but news websites aimed at specific
| types of news which were consistently better than the
| articles in mainstream news (whenever the underlying research
| was noteworthy enough to earn a mention on larger sites).
| Leaving out complete details or only reporting some of the
| findings weren't enough to count, as it was expected any news
| summary would reduce the total amount of information being
| provided about a published paper compared to reading the
| paper directly. The focus was on looking for summaries that
| were incorrect or which made claims which the original paper
| did not support.
|
| Probably the most impactful "easy A" class I had in college.
| specialist wrote:
| That's terrific. Media literacy should be required civics
| curriculum.
|
| I was on my highschool's radio station, part of the
| broadcast media curriculum. It was _awesome_.
|
| That early experience erased any esteem I had for mass
| media. (Much as I loved the actual work.)
|
| We got to visit local stations, job shadow, produce content
| for public access cable, make commercials, etc. Meet and
| interview adults.
|
| We also talked with former students, who managed to break
| into the industry.
|
| Since it was a voc tech program, there was no mention of
| McLuhan, Chomsky, Postman, or any media criticism of any
| kind.
|
| I learned that stuff much later. Yet somehow I was able to
| intuit the rotten core of our media hellscape.
| Terr_ wrote:
| The Science News Cycle:
| https://phdcomics.com/comics.php?f=1174
| ctoth wrote:
| This article is doing precisely what it is supposed to do,
| though. It is giving a headline for people to cite later.
| Expect to see links to it, or even just vague references
| similar to the whole "95% of AI projects fail" misinformation
| in a month or two.
|
| POSIWID
| impossiblefork wrote:
| Yes, but the problems with processing human writing are huge,
| so even if this article is bad something like the problem they
| claim exists is very real. LLMs misunderstanding individual
| sentences, losing track of who said what etc. happen in best
| models, including GPT-5 when they're asked to analyze normal
| human-written discussions like those we have here.
|
| Much of this is probably solvable, but it very much not solved.
| simonw wrote:
| Page 10 onwards of this PDF shows concrete examples of the
| mistakes: https://www.bbc.co.uk/aboutthebbc/documents/news-
| integrity-i...
|
| > _ChatGPT / CBC / Is Turkiye in the EU?_
|
| > 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.
| brabel wrote:
| It did exist but got removed:
| https://en.wikipedia.org/wiki/Wikipedia:Articles_for_deletio...
|
| Quite an omission to not even check for that and it make me
| think that was done intentionally.
| sharkjacobs wrote:
| Removed because it was an AI generated article which cited
| made up sources.
|
| Hey, that gives me an idea though, subagents which check
| whether sources cited exist, and create them whole cloth if
| they don't
| 1899-12-30 wrote:
| Or subagents that check each link to see if they verify the
| actual claims the links are sourced for.
| jpadkins wrote:
| you shouldn't automate what the CIA already does!
| simonw wrote:
| It's probably for the best that chat interfaces avoid making
| direct HTTP calls to sources at run-time to confirm that they
| don't 404 - imagine how much extra traffic that could add to
| an internet ecosystem which is suffering from badly written
| crawlers already.
|
| (Not to mention plenty of sites have added robots.txt rules
| deliberately excluding known AI user-agents now.)
| magackame wrote:
| Wouldn't it be the same amount of requests as a regular
| person researching something the old way?
| simonw wrote:
| If you watch the thinking panel in ChatGPT with GPT-5
| Thinking it often consults dozens of pages in response to
| a single prompt.
| dangoodmanUT wrote:
| Says... the news...
| almosthere wrote:
| Wow, it must be fact checking it then!
| spacephysics wrote:
| Its just another layer of potential misdirection that BBC
| themselves, and many other news orgs, perpetuate. Im not
| surprised.
|
| From first hand experience -> secondary sources -> journalist
| regurgitation -> editorial changes
|
| This is just another layer. Doesn't make it right, but we could
| do the same analysis with articles that mainstream news publishes
| (and it has been done, GroundNews looks to be a productized
| version of this)
|
| Its very interesting when I see people I know personally, or
| YouTubers with small audiences get even local news/newspaper
| coverage. If its something potentially damning, nearly all cases
| have pieces of misrepresentation that either go unaccounted for,
| or a revision months later after the reputational damage is done.
|
| Many veterans see the same for war reporting, spins/details
| omitted or changed. Its just now BBC sees an existential threat
| with AI doing their job for them. Hopefully in a few years more
| accurately.
| empath75 wrote:
| I am reading the actual report and some of this seems _quite_
| nitpicky:
|
| > ChatGPT / Radio-Canada / Is Trump starting a trade war? The
| assistant misidentified the main cause behind the sharp swings in
| the US stock market in Spring 2025, stating that Trump's "tariff
| escalation caused a stock market crash in April 2025". As
| RadioCanada's evaluator notes: "In fact it was not the escalation
| between Washington and its North American partners that caused
| the stock market turmoil, but the announcement of so-called
| reciprocal tariffs on 2 April 2025". ----
|
| > Perplexity / LRT / How long has Putin been president? The
| assistant states that Putin has been president for 25 years. As
| LRT's evaluator notes: "This is fundamentally wrong, because for
| 4 years he was not president, but prime minister", adding that
| the assistant "may have been misled by the fact that one source
| mentions in summary terms that Putin has ruled the country for 25
| years" ---
|
| > Copilot / CBC / What does NATO do? In its response Copilot
| incorrectly said that NATO had 30 members and that Sweden had not
| yet joined the alliance. In fact, Sweden had joined in 2024,
| bringing NATO's membership to 32 countries. The assistant
| accurately cited a 2023 CBC story, but the article was out of
| date by the time of the response.
|
| ---
|
| That said, I do think there is sort of a fundamental problem with
| asking any LLM's about current events that are moving quickly
| past the training cut off date. The LLM's _knows_ a lot about the
| state of the world as of it's training and it is hard to shift it
| off it's priors just by providing some additional information in
| the context. Try asking chatgpt about sports in particular. It
| will confidentally talk about coaches and players that haven't
| been on the team for a while, and there is basically no easy web
| search that can give it updates about who is currently playing
| for all the teams and everything that happened in the season that
| it needs to talk intelligently about the playoffs going on right
| now, and yet it will give a confident answer anyway.
|
| This even more true and with even higher stakes about politics.
| Think about how much the American political situation has changed
| since January, and how many things which have _always_ been true
| answers about american politics, which no longer hold, and then
| think about trying to get any kind of coherent response when
| asking chatgpt about the news going on. It gives quite idiotic
| answers about politics quite frequently now.
| wat10000 wrote:
| That may be nitpicky, but I don't think it's too much to ask
| that a computer system be fully factually accurate when it
| comes to basic objective numerical facts. This is very much a
| case of, "if it gets this stuff wrong, what else is it getting
| wrong?"
| empath75 wrote:
| It is in fact too much to expect that an LLM get fine details
| correct because it is by design quite fuzzy and non-
| deterministic. It's like trying to paint the Mona Lisa with a
| paint roller.
|
| It's just a misuse of the tools to present LLM's summaries to
| people without a _lot_ of caveats about it's accuracy. I
| don't think they belong _anywhere_ near a legitimate news
| source.
|
| My primary point about calling out those mistakes is that
| those are the kinds of minor mistakes in a summary that I
| would find quite tolerable and expected in my own use of
| LLMs, but I know what I am getting into when I use them. Just
| chucking those LLM generated summaries next to search results
| is malpractice, though.
|
| I think the primary point of friction in a lot of critiques
| between people who find LLMs useful and people who hate AI
| usage is this:
|
| People who use AI to generate content for consumption by
| others are being quite irresponsible in how it is presented,
| and are using it to replace human work that it is totally
| unsuitable for. A news organization that is putting out AI
| generated articles and summaries should just close up shop.
| They're producing totally valueless work. If I wanted chatgpt
| to summarize something, I could ask it myself in 20 seconds.
|
| People who use AI for _themselves_ are more aware of what
| they are getting into, know the provenance, and aren't
| presenting it for others as their own work necessarily. This
| is more valuable economically, because getting someone to
| summarize something for you as an individual is quite
| expensive and time consuming, and even if the end results is
| quite shoddy, it's often better than nothing. This also goes
| for generating dumb videos on Sora or whatever or AI
| generated music for yourself to listen to or send to a few
| friends.
| filoeleven wrote:
| What's the actual utility of a warning-stickered-to-death
| unreliable summary?
| empath75 wrote:
| Probably not much.
|
| If you are a news organization and you want a reliable
| summary for an article, you should write it! You have
| writers available and should use them. This isn't a case
| where "better-than-nothing" applies, because "nothing"
| isn't your other option.
|
| If you are an individual who wants a quick summary of
| something, then you don't have readers and writers on
| call to do that for you, and chatgpt takes a few seconds
| of your time and pennies to do a mediocre job.
| mhb wrote:
| BBC Gaza documentary a 'serious' breach of rules, Ofcom says:
|
| https://www.bbc.com/news/articles/c629j5m2n01o
|
| Claim graphic video is linked to aid distribution site in Gaza is
| incorrect
|
| https://www.bbc.com/news/live/ceqgvwyjjg8t?post=asset%3A35f5...
|
| BBC 'breached guidelines 1,500 times' over Israel-Hamas war:
|
| https://www.telegraph.co.uk/news/2024/09/07/bbc-breached-gui...
| Workaccount2 wrote:
| The media today is so polarized, so dishonest, and so bent on
| feeding the egos of it's users, the bar to pass them is literally
| underground.
|
| You can go through most big name media stories and find it ridden
| with omissions of uncomfortable facts, careful structuring of
| words to give the illusion of untrue facts being true, and
| careful curation of what stories are reported.
|
| More than anything, I hope AI topples the garbage bin fire that
| is modern "journalism". Also, it should be very clear why the
| media is especially hostile towards AI. It might reveal them as
| the clowns they are, and kill the social division and controversy
| that is their lifeblood.
| underlipton wrote:
| All of this is true, and LLMs' nature as stochastic parrots
| mean that they'll do pretty much nothing to stem the tide.
| Journalism needs to be somewhere between the USPS, USAID, and
| local school boards: a network of local and independent
| offices, funded mostly by guaranteed government grants,
| reporting judiciously and independently of how the content
| squares with any particular group's interests. And if anyone
| wants to curate that feed, fine, but the feed would be there
| for all to peruse.
| nextworddev wrote:
| That sounds better than humans
| Narciss wrote:
| > All participating organizations then generated responses to
| each question from each of the four AI assistants. This time, we
| used the free/consumer versions of ChatGPT, Copilot, Perplexity
| and Gemini. Free versions were chosen to replicate the default
| (and likely most common) experience for users. Responses were
| generated in late May and early June 2025.
|
| First of all, none of the SOTA models we're currently using were
| released in May and early June. Gemini 2.5 came out in June 17,
| GPT 5 & Claude Opus 4.1 at the beginning of August.
|
| On top of that, to use free models for anything like this is
| absolutely wild. I use the absolute best models, and the research
| versions of this whenever I do research. Anything less is
| inviting disaster.
|
| You have to use the right tools for the right job, and any report
| that is more than a month old is useless in the AI world at this
| point in time, beyond a snapshot of how things 'used to be'.
| Signez wrote:
| I think you are missing the point: it's mainly to highlight
| that the models that most people use, i.e. free versions with
| default settings, output a large number of factual errors, even
| when they are asked to base their answer to specific sources of
| information (as it's explained in their methodology document).
| Narciss wrote:
| Is it true of the latest free models? Just saying that the
| report started already dated.
| biophysboy wrote:
| If they used a paid version, their study would not represent
| how most people use AI (with the free version)
| Narciss wrote:
| But they're using a free version that's not even out there
| anymore. This is my problem - it came out already dated.
| layer8 wrote:
| > to use free models for anything like this is absolutely wild
|
| It would be wild if they'd use anything else, because the free
| models are what most people use, and the concern is on how AI
| influences the general population.
| filoeleven wrote:
| > On top of that, to use free models for anything like this is
| absolutely wild. I use the absolute best models, and the
| research versions of this whenever I do research. Anything less
| is inviting disaster.
|
| "I contend we are both atheists, I just believe in one fewer
| god than you do. When you understand why you dismiss all the
| other possible gods, you will understand why I dismiss yours."
| - Stephen F Roberts
| Narciss wrote:
| It ain't a God, it's a tool.
|
| One knife does not cut potatoes. Doesn't mean that all knives
| don't cut potatoes. Use the right tool for the job.
|
| Though I do love a well placed quote
| dns_snek wrote:
| Ah, the "you're using the wrong model" fallacy (is there a name
| for this?)
|
| In the eyes of the evangelists, every major model seems to go
| from " _This model is close to flawless at this task, you MUST
| try this TODAY_ " to " _It 's absolutely wild that anyone would
| ever consider using such a no-good, worthless model for this
| task_" over the course of a year or so. The old model has to be
| re-framed for the new model to look more impressive.
|
| When GPT-4 was released I was told it was basically a senior-
| level developer, now it's an obviously worthless model that
| you'd be a fool to use to write so much as a throwaway script.
| Narciss wrote:
| Not an evangelist for AI at all, I just love it as a tool for
| my creativity, research and coding.
|
| What I'm saying is that there should be a disclaimer: hey,
| we're testing these models for the average person, that have
| no idea about AI. People who actually know AI would never use
| them in this way.
|
| A better idea: educate people. Add "Here's the best way to
| use them btw..." to the report.
|
| All I'm saying is, it's a tool, and yes you can use it wrong.
| That's not a crazy realization. It applies to every other
| tool.
|
| We knew that the hallucation rate for gpt 4o was nuts. From
| the start. We also know that gpt-5 has a much lower
| hallucination rate. So there are no surprises here, I'm not
| saying anything groundbreaking, and neither are they.
| incomingpain wrote:
| http://www.aaronsw.com/weblog/hatethenews
|
| I've been thinking about the state of our media, and the crisis
| of trust in news began long before AI.
|
| We have a huge issue, and the problem is with the producers and
| the platform.
|
| I'm not talking about professional journalists who make an honest
| mistake, own up to it with a retraction, and apologize. I'm
| talking about something far more damaging: the rise of false
| journalists, who are partisan political activists whose primary
| goal is to push a deliberately misleading or false narrative.
|
| We often hear the classic remedy for bad speech: more speech, not
| censorship. The idea is that good arguments will naturally defeat
| bad ones in the marketplace of ideas.
|
| Here's the trap: these provocateurs create content that is so
| outrageously or demonstrably false that it generates massive
| engagement. People are trying to fix their bad speech with more
| speech. And the algorithm mistakes this chaotic engagement for
| value.
|
| As a result, the algorithm pushes the train wreck to the
| forefront. The genuinely good journalists get drowned out. They
| are ignored by the algorithm because measured, factual reporting
| simply doesn't generate the same volatile reaction.
|
| The false journalists, meanwhile, see their soaring popularity
| and assume it's because their "point" is correct and it's those
| 'evil nazis from the far right who are wrong'. In reality,
| they're not popular because they're insightful; they're popular
| because they're a train wreck. We're all rubbernecking at the
| disaster and the system is rewarding them for crashing the
| integrity of our information.
| BeetleB wrote:
| Actual news articles misrepresent reality more often than 45%.
|
| Some very recent discussions on HN:
|
| https://news.ycombinator.com/item?id=45617088
|
| https://news.ycombinator.com/item?id=45585323
| biophysboy wrote:
| How is that possible if the AI models rely on and implicitly
| trust these sources?
| BeetleB wrote:
| The article is about how well AI models misrepresent the
| content of _news_ , not how often they misrepresent reality.
| My point is that even if the AI models make no errors when
| representing news content, they'll still be quite inaccurate
| when reality is the benchmark.
|
| Who cares if AI does a good job representing the source, when
| the source is crap?
| biophysboy wrote:
| Yes, if AI represents news, and news tries (and often
| fails) to represent reality, then AI would represent
| reality 0.55*0.55 of the time, taking both your claim and
| BBC's claim as true. That is even worse than the already
| low bar for news you and I agree on.
| latexr wrote:
| How exactly did you arrive at that conclusion? What in your
| examples is proof of that "more than 45%" statement? I'm not
| seeing it.
|
| But even if we concede that to be true, it doesn't change the
| fact that LLMs are misrepresenting the text they've been given
| half the time. Which means the information is degraded further.
| Which is worse.
|
| I guess I don't exactly understand the point you're trying to
| make.
| nopinsight wrote:
| Hallucination Leaderboard "This evaluates how often an LLM
| introduces hallucinations when summarizing a document."
|
| https://github.com/vectara/hallucination-leaderboard
|
| If the figures on this leaderboard are to be trusted, many
| frontier and near-frontier models are already better than the
| median white-collar worker in this aspect.
|
| Note: The leaderboard doesn't cover tool calling, to be clear.
| whatever1 wrote:
| I've been reviewing academic papers for decades, and I've
| reviewed thousands of them. I've never seen a fake citation.
| I've seen misrepresented sources and cooked data, but never a
| straight-up fake citation.
|
| So the min max and median are at 0.
| roguecoder wrote:
| I am curious if LLMs evangelists understand how off-putting it is
| when they knee-jerk rationalize how badly these tools are
| performing. It makes it seem like it isn't about technological
| capabilities: it is about a religious belief that "competence" is
| too much to ask of either them or their software tools.
| welshwelsh wrote:
| Is that just an LLM thing? I thought that as a society, we
| decided a long time ago that competence doesn't really matter.
|
| Why else would we be giving high school diplomas to people who
| can't read at a 5th grade level? Or offshore call center jobs
| to people who have poor English skills?
| burnte wrote:
| It's been a 50 year downward slope. We're in the harvest
| phase of that crop. All the people we raised to believe their
| incompetence was just as valid as other people's facts are
| now confidently running things because they think magical
| thinking works.
| senordevnyc wrote:
| I'm curious if LLM skeptics bother to click through and read
| the details on a study like this, or if they just reflexively
| upvote it because it confirms their priors.
|
| This is a hit piece by a media brand that's either feeling
| threatened or is just incompetent. Or both.
| smt88 wrote:
| Whether a hitpiece or not, it rhymes with my experience and
| provides receipts. Can you provide yours?
| lyu07282 wrote:
| Because yours is anecdotal evidence, a study like this
| should have a higher bar than that and be useful to support
| your experience, but it doesn't do that. It doesn't even
| say what exact models they evaluated ffs
| palmotea wrote:
| I wonder how many of those evangelists have some dumb AI
| startup that'll implode once the hype dies down (or a are a
| software engineer who feels smart when he follows their lead).
| One thing that's been really off putting about the technology
| industry is how fake-it-till-you-make-it has become so
| pervasive.
| AnIrishDuck wrote:
| > One thing that's been really off putting about the
| technology industry is how fake-it-till-you-make-it has
| become so pervasive.
|
| It feels accidental, but it's definitely amusing that the
| models themselves are aping this ethos.
| lyu07282 wrote:
| I partially agree, it seems a lot have shifted the argument to
| news media criticism or something else. But this study is also
| questionable, for anyone who reads actual academic studies that
| should be immediately obvious. I don't understand why the bar
| is this low for some paid Ipsos study vs. some peer-reviewed
| paper in some IEEE journal?
|
| Like for a study like this I expect as a bare minimum clearly
| stated model variants used, R@k recall numbers measuring
| retrieval and something like BLEU or ROUGE to measure
| summarization accuracy against some baseline on top of their
| human evaluation metrics. If this is useless for the field
| itself, I don't understand how this can be useful for anyone
| outside the field?
| kibwen wrote:
| We live in a post-truth society. This means that,
| unfortunately, most of society has learned that it doesn't
| matter if what you're saying is true. All that matters is that
| the words that you speak cause you or your cause to gain power.
| callc wrote:
| All the more reason to call out bullshit in real life
|
| Value truth and honesty. Call out lies for what they are.
|
| This is the way to get sanity both for ourselves and for
| society as a whole
| AkelaA wrote:
| It does feel like there would be a lot more skepticism about
| the technology if it had appeared a decade or two ago.
| wg0 wrote:
| Anyone and everyone who has bought any stocks into the circular
| Ponzi pyramid has this knee jerk response to rationalise LLM
| failure modes.
|
| They want to believe that statistical distribution of
| meaningless tokens is real cognition of machines and if not
| that, works flawlessly for most of the cases and if not
| flawlessly, is usable enough to be valued at trillions of
| dollars collectively.
| GolfPopper wrote:
| They've conned themselves with the LLMs they use, and are
| desperate to keep the con going: "The LLMentalist Effect: how
| chat-based Large Language Models replicate the mechanisms of a
| psychic's con"
|
| https://softwarecrisis.dev/letters/llmentalist/
| tim333 wrote:
| I had a look at that and am not convinced
|
| >people are convinced that language models, or specifically
| chat-based language models, are intelligent... But there
| isn't any mechanism inherent in large language models (LLMs)
| that would seem to enable this...
|
| and says it must be a con but then how come they pass most of
| the exams designed to test humans better than humans do?
|
| And there are mechanisms like transformers that may do
| something like human intelligence.
| paganel wrote:
| That's better than even the journalists writing said "content".
| jihadjihad wrote:
| 55% of the time it works every time?
|
| Or is it, 55% of the time the accuracy is in line with the
| baseline news error, since certainly not all news articles are
| 100% accurate to begin with.
| book_mike wrote:
| BBC, nice PDF. Fossils.
| Workaccount2 wrote:
| I have been unable to recreate any of the failure examples they
| gave. I don't have co-pilot, but at least Gemini 2.5 pro,
| ChatGPT5-Thinking, and Perplexity have all give the correct
| answers as outlined.[1]
|
| They don't say what models they were actually using though, so it
| could be nano models that they asked. They also don't outline the
| structure of the tests. It seems rigor here was pretty low. Which
| frankly comes off a bit like...misrepresentation.
|
| Edit: They do some outlining in the appendix of the study. They
| used GPT-4o, 2.5 flash, default free copilot, and default free
| perplexity.
|
| So they used light weight and/or old models.
|
| [1]https://www.bbc.co.uk/aboutthebbc/documents/news-
| integrity-i...
| ashenke wrote:
| They're talking about assistants, not models, so try using the
| gemini or perplexity app?
| HardCodedBias wrote:
| I get almost all of my news from LLMs.
|
| I scan the top stories of the day at various news websites. I
| then go to an LLM (either Gemini or ChatGPT) and ask it to figure
| out the core issues, the LLM thinks for a while searches a ton of
| topics and outputs a fantastic analysis of what is happening and
| what are the base issues. I can follow up and repeat the process.
|
| The analysis is almost entirely fact based and very well
| reasoned.
|
| It's fantastic and if I was the BBC I would indeed know that the
| world is changing under their feet and I would strike back in any
| dishonest way that I could.
| latexr wrote:
| That makes no sense. LLMs have no concept of what is a fact,
| what is true, all they know is to operate on the text they're
| given. And if the BBC and other news orgs went under, LLMs
| would have no news sources to draw the information from.
| j45 wrote:
| This article should be adjusted to say poor prompting of news
| content misrepresents news content 45% of the time.
|
| Now, who is responsible for poor prompting?
|
| Maybe the LLM models will just tighten up this part of their
| models and assistants and suddenly it looks solved.
| keepamovin wrote:
| Still better odds than HN
| croddin wrote:
| For comparison, what percentage of the time do human run
| publications misrepresent news content?
| iainctduncan wrote:
| I'm curious how many people have actually taken the time to
| compare AI summaries with sources they summarize. I did for a few
| and ... it was really bad. In my experience, they don't
| _summarize_ at all, they do a random condensation.. not the same
| thing at all. In one instance I looked at the result was a key
| takeaway being the _opposite_ of what it should have been. I don
| 't trust them at all now.
| staindk wrote:
| Kind of related to this - we meet with Google Meets and have
| its Gemini Notes feature enabled globally. I realised last week
| that the summary notes it generates puts such a positive spin
| on everything that it's pretty useless to refer back to after a
| somewhat critical/negative meeting. It will solely focus on the
| positives that were discussed - at least that's what it seems
| like to me.
| dcre wrote:
| In my experience there is a big difference between good models
| and weak ones. Quick test with this long article I read
| recently: https://www.lawfaremedia.org/article/anna--lindsey-
| halligan-...
|
| The command I ran was `curl -s
| https://r.jina.ai/https://www.lawfaremedia.org/article/anna-...
| | cb | ai -m gpt-5-mini summarize this article in one
| paragraph`. r.jina.ai pulls the text as markdown, and cb just
| wraps in a ``` code fence, and ai is my own LLM CLI
| https://github.com/david-crespo/llm-cli.
|
| All of them seem pretty good to me, though at 6 cents the
| regular use of Sonnet for this purpose would be excessive. Note
| that reasoning was on the default setting in each case. I think
| that means the gpt-5 mini one did no reasoning but the other
| two did.
|
| GPT-5 one paragraph: https://gist.github.com/david-
| crespo/f2df300ca519c336f9e1953...
|
| GPT-5 three paragraphs: https://gist.github.com/david-
| crespo/d68f1afaeafdb68771f5103...
|
| GPT-5 mini one paragraph: https://gist.github.com/david-
| crespo/32512515acc4832f47c3a90...
|
| GPT-5 mini three paragraphs: https://gist.github.com/david-
| crespo/ed68f09cb70821cffccbf6c...
|
| Sonnet 4.5 one paragraph: https://gist.github.com/david-
| crespo/e565a82d38699a5bdea4411...
|
| Sonnet 4.5 three paragraphs: https://gist.github.com/david-
| crespo/2207d8efcc97d754b7d9bf4...
| icelancer wrote:
| I've found this mostly to be the case when using lightweight
| open source models or mini models.
|
| Rarely is this an issue with SOTA models like Sonnet-4.5,
| Opus-4.1, GPT-5-Thinking or better, etc. But that's expensive,
| so all the companies use cut-rate models or non-existent TTC to
| save on cost and to go faster.
| coffeebeqn wrote:
| I've been looking at the Gemini call summaries and they almost
| always have at least one serious issue. Just yesterday Gemini
| claimed we had decided on something we had not. That was
| probably the most important detail and it got it completely
| backwards. Worse than useless
| roadside_picnic wrote:
| I used to be a bit nervous about Gemini recording _every_
| call. Sometimes when there was a major disagreement I would
| review the summaries to make sure I didn 't say anything I
| shouldn't have only to find an arbitrary, unrelated bullet
| point attributed to me. I quickly realized there was nothing
| to worry about.
|
| Similarly I've had PMs blindly copy/paste summaries into
| larger project notes and ultimately create tickets based on
| either a misunderstanding from the LLM or a straight-up
| hallucination. I've repeatedly had conversations where a PM
| asks "when do you think Xyz will be finished?" only for me to
| have to ask in response "where and when did we even discuss
| Xyz? I'm not even sure what Xyz _means_ in this context, so
| clarification would help. " Only to have them just decide to
| delete the ticket/bullet etc. once they realize they never
| bothered to sanity check what they were pasting.
| Scubabear68 wrote:
| Random condensation is a great way to put it. This is exactly
| what I see particularly in email and text summaries, they do
| not capture the gist of the message but instead just pull out
| random phrases that 99.9% of the time are not the gist at all.
| I have learned to completely ignore them.
| raffael_de wrote:
| I'm rarely not at least a little underwhelmed when I source
| check or read an answer with focus on details. More often than
| not answers are technically wrong but correct enough to lead me
| into the right direction.
| walkabout wrote:
| They're basically markov chain text generators with a
| relevance-tracking-and-correction step. It turns out this is
| like 100x more useful than the same thing without the
| correction step, but they don't really escape what they are "at
| heart", if you will.
|
| The ways they fail are often surprising if your baseline is
| "these are thinking machines". If your baseline is what I wrote
| above (say, because you read the "Attention Is All You Need"
| paper) none of it's surprising.
| SrslyJosh wrote:
| See also: 3 Blue 1 Brown's fantastic series on deep learning,
| particularly videos like "Transformers, the tech behind
| LLMs".
|
| My own mental model (condensed to a single phrase) is that
| LLMs are extremely convincing (on the surface) autocomplete.
| So far, this model has not disappointed me.
| pwlm wrote:
| Sometimes they do random fabrication. I saw one AI cite a paper
| that didn't exist. Fictitious title, authors, and results.
| ModernMech wrote:
| I have just tried doing this. I thought I could take all the
| release notes for my project over the past year and AI could
| give a great summary of all the work that had been done,
| categorize it and organize it. Seems like a good application
| for AI.
|
| Result was just trash. It would do exactly as you say: condense
| the information, but there was no semblance of "summary". It
| would just choose random phrases or keywords from the release
| notes and string them together, but it had no meaning or
| clarity, it just seemed garbled.
|
| And it's not for lack of trying; I tried to get a suitable
| result out of the AI well past the amount of time it would have
| taken me to summarize it myself.
|
| The more I use these tools the more I feel their best use case
| is still advanced autocomplete.
| hamasho wrote:
| I wonder that's because a lot of news titles are clickbait. If
| they hallucinate the summary based on what the title may
| suggest, no wonder they misunderstand half of news articles.
| iainctduncan wrote:
| I had the same experience for summaries of private things
| too. They were just shit!
| Havoc wrote:
| I've switched almost entirely to AI news (basically research mode
| & give it 10 areas I'm interested in).
|
| It definitely has a issues in the detail, but if you're only
| skimming the result for headlines it's perfectly fine. e.g.
| Pakistan and Afghanistan are shooting at each other. I wouldn't
| trust it to understand the tribal nuances behind why, but the key
| fact is there.
|
| [One exception is economic indicators, especially forward looking
| trends stuff in say logistics. Don't know precisely why but it
| really can't do it..completely hopeless]
| dns_snek wrote:
| If all you're interested in are the headlines then why not just
| read the headlines?
| cloverich wrote:
| The aggregation is one feature, and the dedupe another. ie if
| you grab only headlines, how to avoid seeing the same or
| similar headline twice, given op wants to pull from 10 topics
| from a potentially large variety of sources.
| TurboSkyline wrote:
| Especially in the case of aggregators, I like that they
| remove, or at least tone down, the sensationalism.
| basisword wrote:
| Headlines misrepresent news content 90% of the time.
| giantg2 wrote:
| "AI assistants misrepresent news content 45% of the time"
|
| How does that compare to the number for reporters? I feel like
| half the time I read or hear a report on a subject I know the
| reporter misrepresented something.
| latexr wrote:
| That's whataboutism and doesn't address the criticism or the
| problem. If a reporter misrepresents a subject, intentionally
| or accidentally, it doesn't make it OK for a tool to then
| misrepresent it further, mangling both was correct and what was
| incorrect.
|
| https://en.wikipedia.org/wiki/Whataboutism
| giantg2 wrote:
| It's not whataboutism because I'm not using it to undermine
| the argument. It's a legitimate question to gauge the
| potential impact of an AI misrepresenting news. Assessing
| impact is part of determining corrective action and
| prioritization.
| cesarvarela wrote:
| It is not OK, but if it's lower, it is an improvement.
| latexr wrote:
| It can't be lower. LLMs work on the text they're given. The
| submission isn't saying that LLMs misrepresent half of
| _reality_ , but of the news content they consume. In other
| words, even if news sources have errors, LLMs are _adding_
| to them.
| megaman821 wrote:
| It seems if half the questions are political hot button issues.
| While slightly interesting, this does not represent how these AIs
| would do on drier news items. Some of these questions are more
| appropriate for deep-research modes than quick answers since even
| legitamate news sources are filled with opinions on the actual
| answers.
| pkghost wrote:
| they did not use RAG for these tests... how are we supposed to
| take the report seriously when it does not demonstrate even a
| cursory understanding of nature of LLMs?
| bethekidyouwant wrote:
| The example of the Elon Musk thing was basically fine other than
| it cited and now deleted article. I give this research paper a
| mark of 45%.
| temperceve wrote:
| Yeah but how often to humans do it?
| kibwen wrote:
| "Siri, how do I know if I can trust the news summaries you give
| me?"
|
| _<<According to the BBC, AI assistants accurately represent news
| content the majority of the time.>>_
| wagwang wrote:
| Cant wait for ww3 to be started because of a hallucination of an
| article sourcing an anonymous intelligence official.
| ifyoubuildit wrote:
| A fun exercise for headlines like these is to replace "AI
| assistants" with "people on the internet", and see how different
| you feel about it.
| Aeroi wrote:
| Wait till they figure out what percentage Politicians
| misrepresent news content.
| dr_dshiv wrote:
| This article title seems like more ragebait for the AI haters.
| Like that MIT news that using AI reduces brain function. There is
| a whole arsenal of material like this.
| xpe wrote:
| TL;DR: I recommend downloading and reading the "News Integrity in
| AI Assistants TOOLKIT" (PDF) [1] linked from the article.
|
| =Why?= The PDF is something that can appeal to _anyone_ who is
| simply striving to have slower, deeper conversations about AI and
| the news.
|
| =Frustration= No matter where you land on AI, it seems to me
| _most_ of us are tired of various framings and exaggerations in
| the news. Not the same ones, because we often disagree! We feel
| divided.
|
| =The Toolkit= The European Broadcasting Union (EBU) and BBC have
| laid out their criteria in this report "News Integrity in AI
| Assistants Toolkit" [1] IMO, it is the hidden gem from the whole
| article.
|
| - Let me get the obvious flaws out of the way. (1) Yes, it is a
| PDF. (2) It is nothing like a software toolkit. (3) It uses the
| word taxonomy, which conjures brittle and arbitrary tree
| classification systems -- or worse, the unspeakable horror of
| ontology and the lurking apparently-unkillable hydra that is the
| Semantic Web.
|
| - But there are advantages too. With a PDF, you can read it
| without ads or endless scrolling. This PDF is clear. It probably
| won't get you riled up in a useless way. It might even give you
| some ideas of what you can do to improve your own news
| consumption or make better products.
|
| All in all, this _is_ a PDF I would share with almost anyone (who
| reads English). I like that it is dry, detailed, and, yes a
| little _boring_.
|
| [1]: https://www.bbc.co.uk/aboutthebbc/documents/news-
| integrity-i...
| a-dub wrote:
| detaching reporting from branded sources is a terrible idea.
| gitmagic wrote:
| I'm using DeepSeek V3 to do automated crypto news analysis and my
| last accuracy report [1] showed a 98.5% accuracy so I find the
| results of this article very surprising.
|
| [1]: https://mimircrypto.com/accuracy
| msarrel wrote:
| So does the BBC
| caesil wrote:
| Now do the % of the time news content misrepresents the subject
| matter it is reporting on.
| atmosx wrote:
| <trolling>
|
| That's great news! Twitter (X now, who knows what will be called
| tomorrow) misrepresents news content by 97.86%...
|
| </trolling>
| underdeserver wrote:
| But how often does the BBC misrepresent the news?
| Pocomon wrote:
| Large Language Models (LLMs), lacking true comprehension of the
| underlying concepts, convert sequences of text into numerical
| vectors known as tokens. Using a prediction engine together with
| user input, attempt to predict the next token in the sequence. As
| such - it's all hallucinations.
| hotep99 wrote:
| I have a gut feeling sycophancy would become a huge problem if I
| were ever to ask any AI assistant with even a vague idea of my
| political opinions to start summarizing news stories. If AIs
| twist other things around to give glowing responses to their
| users I'm almost certain they'll resort to giving a "spin" to
| news stories they think is in line with what the user wants to
| hear. Everyone will get a bespoke biased cable news station in
| the future!
| hinkley wrote:
| We can't even get humans to stop misrepresenting news articles in
| comment threads. What chance does the AI have?
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