Personally, if I got a resurrection from it, I would accept the nudge and do the political activism in Dorchester.
I had to fight a similar battle with Google Maps, which most people believe to be a source of truth, and it took years until incorrect information was changed. I'm not even sure if it was because of all the feedback I provided.
I see Google as a firehose of information that they spit at me ("feed"), they are too big to be concerned about any inconsistencies, as these don't hurt their business model.
Now, frequently, the AI summaries are on top. The AI summary LLM is clearly a very fast, very dumb LLM that’s cheap enough to run on webpage text for every search result.
That was a product decision, and a very bad one. Currently a search for "Suicide Squad" yields
> The phrase "suide side squad" appears to be a misspelling of "Suicide Squad"
Surely there is a way to correct it: getting the issue on the front page of HN.
Well, in this case the inaccurate information is shown because the AI overview is combining information about two different people, rather than the sources being wrong. With traditional search, any webpages would be talking about one of the two people and contain only information about them. Thus, I'd say that this problem is specific to the AI overview.
That's deeply concerning, especially when these two companies control almost all the content we access through their search engines, browsers and LLMs.
This needs to be regulated. These companies should be held accountable for spreading false information or rumours, as it can have unexpected consequences.
Regulated how? Held accountable how? If we start fining LLM operators for pieces of incorrect information you might as well stop serving the LLM to that country.
> since it can have unexpected consequences
Generally you hold the person who takes action accountable. Claiming an LLM told you bad information isn’t any more of a defense than claiming you saw the bad information on a Tweet or Reddit comment. The person taking action and causing the consequences has ownership of their actions.
I recall the same hand-wringing over early search engines: There was a debate about search engines indexing bad information and calls for holding them accountable for indexing incorrect results. Same reasoning: There could be consequences. The outrage died out as people realize they were tools to be used with caution, not fact-checked and carefully curated encyclopedias.
> I'm worried about this. Companies like Wikipedia spent years trying to get things right,
Would you also endorse the same regulations against Wikipedia? Wikipedia gets fined every time incorrect information is found on the website?
EDIT: Parent comment was edited while I was replying to add the comment about outside of the US. I welcome some country to try regulating LLMs to hold them accountable for inaccurate results so we have some precedent for how bad of an idea that would be and how much the citizens would switch to using VPNs to access the LLM providers that are turned off for their country in response.
Other companies have been fined for misleading customers [0] after a product launch. So why make an exception for Big Tech outside the US?
And why is the EU the only bloc actively fining US Big Tech? We need China, Asia and South America to follow their lead.
[0] https://en.m.wikipedia.org/wiki/Volkswagen_emissions_scandal
But how do we know they're telling the truth? How do we know it wasn't intentional? And more importantly, who's held accountable?
While Google's AI made the mistake, Google deployed it, branded it, and controls it. If this kind of error causes harm (like defamation, reputational damage, or interference in public opinion), intent doesn't necessarily matter in terms of accountability.
So while it's not illegal to be wrong, the scale and influence of Big Tech means they can't hide behind "it was the AI, not us."
sounds good to me?
Fines, when backed by strong regulation, can lead to more control and better quality information, but only if companies are actually held to account.
The organization that runs the website, the Wikimedia Foundation, is also not a company. It's a nonprofit.
And the Wikimedia Foundation have not “spent years trying to get things right”, assuming you're referring to facts posted on Wikipedia. That was in fact a bunch of unpaid volunteer contributors, many of whom anonymous and almost all of whom unaffiliated with the Wikimedia Foundation.
A German 90s/2000s rapper (Textor, MC of Kinderzimmer Productions) produced a radio feature about facts and how hard it can be to prove them.
One personal example he added was about his Wikipedia Article that stated that his mother used to be a famous jazz singer in her birth country Sweden. Except she never was. The story had been added to an Album recension in a rap magazine years before the article was written. Textor explains that this is part of 'realness' in rap, which has little to do with facts and more with attitude.
When they approached Wikipedia Germany, it was very difficult to change this 'fact' about the biography of his mother. There was published information about her in a newspaper and she could not immediately prove who she was. Unfortunately, Textor didn't finish the story and moved on to the next topic in the radio feature.
That is such a classic problem with Google (from long before AI).
I am not optimistic about anything being changed from this, but hope springs eternal.
Also, I think the trilobite is cute. I have a [real fossilized] one on my desk. My friend stuck a pair of glasses on it, because I'm an old dinosaur, but he wanted to go back even further.
The site structure is also fairly prehistoric!
It's interesting that LLMs produce each output token as probabilities but it appears that in order to generate the next token (which is itself expressed as a probability), it has to pick a specific word as the last token. It can't just build more probabilities on top of previous probabilities. It has to collapse the previous token probabilities as it goes?
You can also see decision paralysis in action if you implement CoT - it's common to see the model "pondering" about a bunch of possible options before picking one.
Be ideal if it did disambiguate a la Wikipedia.
That's why this Dave Barry has a right. It's a subsection.
It'd be like opening Dave Barry (comedian) on Wikipedia and halfway through the article in a subsection it starts detailing the death of a different Dave Barry.
The versions with "Dave Barry, the humorist and Pulitzer Price winner, passed away last November 20…" and "Dave Barry, a Bostonian … died on November 20th…" are also rather unambiguous regarding who this might be about. The point being, even if the meaning of the particular identity of the subject is moved outside to an embedding context, it is still crucial for the meaning of these utterances.
Vibrant watering hole with drinks & po' boys, as well as a jukebox, pool & electronic darts.
It doesn't serve po' boys, have a jukebox (though the playlists are impeccable), have pool, or have electronic darts. (It also doesn't really have drinks in the way this implies. It's got beer and a few canned options. No cocktails or mixed drinks.)
They got a catty one-star review a month ago for having a misleading description by someone who really wanted to play pool or darts.
I'm sure the owner reported it. I reported it. I imagine other visitors have as well. At least a month on, it's still there.
Too much to ask, surely.
I know it's the HN darling and is probably talked about too much already but it doesn't have this problem. The only AI stuff is if you specifically ask for it which in your case would be never. And unlike Google where you are at the whims of the algorithm you can punish (or just block) AI garbage sites that SEO their way into the organic results. And a global toggle to block AI images.
I can see a bright future in blaming things on AI that have nothing to do with AI, at least on here.
I don’t know if this is a fundamental problem with the llm architecture or a problem with proper prompts.
I also hope that the AI and Google duders understand that this is most people's experience with their products these days. They don't work, and they twist reality in ways that older methods didn't (couldn't, because of the procedural guardrails and direct human input and such). And no amount of spin is going to change this perception - of the stochastic parrots being fundamentally flawed - until they're... you know... not. The sentiment management campaigns aren't that strong just yet.
rf15•7h ago
randcraw•6h ago
Or elect them President.
BobbyTables2•6h ago
locallost•6h ago
trod1234•6h ago
The whole point of regulation is for when the profit motive forces companies towards destructive ends for the majority of society. The companies are legally obligated to seek profit above all else, absent regulation.
Aurornis•5h ago
What regulation? What enforcement?
These terms are useless without details. Are we going to fine LLM providers every time their output is wrong? That’s the kind of proposition that sounds good as a passing angry comment but obviously has zero chance of becoming a real regulation.
Any country who instituted a regulation like that would see all of the LLM advancements and research instantly leave and move to other countries. People who use LLMs would sign up for VPNs and carry on with their lives.
trod1234•4h ago
Enforcement ensures accountability.
Fines don't do much in a fiat money-printing environment.
Enforcement is accountability, the kind that stakeholders pay attention to.
Something appropriate would be where if AI was used in a safety-critical or life-sustaining environment and harm or loss was caused; those who chose to use it are guilty until they prove they are innocent I think would be sufficient, not just civil but also criminal; where that person and decision must be documented ahead of time.
> Any country who instituted a regulation like that would see all of the LLM advances and research instantly leave and move to other countries.
This is fallacy. Its a spectrum, research would still occur, it would be tempered by the law and accountability, instead of the wild-west where its much more profitable to destroy everything through chaos. Chaos is quite profitable until it spread systemically and ends everything.
AI integration at a point where it can impact the operation of nuclear power plants through interference (perceptual or otherwise) is just asking for a short path to extinction.
Its quite reasonable that the needs for national security trump private business making profit in a destructive way.
Ukv•2h ago
Would this guilty-until-proven-innocent rule apply also to non-ML code and manual decisions? If not, I feel it's kind of arbitrarily deterring certain approaches potentially at the cost of safety ("sure this CNN blows traditional methods out of the water in terms of accuracy, but the legal risk isn't worth it").
In most cases I think it'd make more sense to have fines and incentives for above-average and below-average incident rates (and liability for negligence in the worse cases), then let methods win/fail on their own merit.
trod1234•43m ago
I would say yes because the person deciding must be the one making the entire decision but there are many examples where someone might be paid to just rubberstamp decisions already made. Letting the person who decided to implement the solution off scot-free.
The mere presence of AI (anything based on underlying work of perceptrons) being used accompanied by a loss should prompt a thorough review which corporations currently are incapable of performing for themselves due to lack of consequences/accountability. Lack of disclosure, and the limits of current standing, is another issue that really requires this approach.
The problem of fines is that they don't provide the needed incentives to large entities as a result of money-printing through debt-issuance, or indirectly through government contracts. Its also far easier to employ corruption to work around the fine later for these entities as market leaders. We've seen this a number of times in various markets/sectors like JPM and the 10+ year silver price fixing scandal.
Merit of subjective rates isn't something that can be enforced, because it is so easily manipulated. Gross negligence already exists and occurs frighteningly common but never makes it to court because proof often requires showing standing to get discovery which isn't generally granted absent a smoking gun or the whim of a judge.
Bad things happen certainly where no one is at fault, but most business structure today is given far too much lee-way and have promoted the 3Ds. Its all about: deny, defend, depose.
ViscountPenguin•1h ago