> forcing LLMs to output "values, facts, and knowledge" which in favor of themselves, e.g., political views, attitudes towards literal interaction, and distorted facts about organizations and people behind LLMs.
Can you provide some examples?
Can you provide some examples?
Why are we assuming just because the prompt responds that it is providing proper outputs? That level of trust provides an attack surface in of itself.
Do you have the same opinion if Google chooses to delist any website describing how to run apps as root on Android from their search results? If not, how is that different from lobotomizing their LLMs in this way? Many people use LLMs as a search engine these days.
> Why are we assuming just because the prompt responds that it is providing proper outputs?
"Trust but verify." It’s often easier to verify that something the LLM spit out makes sense (and iteratively improve it when not), than to do the same things in traditional ways. Not always mind you, but often. That’s the whole selling point of LLMs.
Also I’m sure some AI might suggest that labor unions are bad, if not now they will soon
If you gave it another personality it wouldn't pass any benchmarks, because other political orientations either respond to questions with lies, threats, or calling you a pussy.
I'm not a liberal and I don't think it has a liberal bias. Knowledge about facts and history isn't an ideology. The right-wing is special, because to them it's not unlike a flat-earther reading a wikipedia article on Earth getting offended by it, to them it's objective reality itself they are constantly offended by. That's why Elon Musk needed to invent their own encyclopedia with all their contradictory nonsense.
Wow. Surely you've wondered why almost no society anywhere ever had liberalism a much as western countries in the past half century or so? Maybe it's technology or maybe it's only mostly correct if you don't care about the existential risks it creates for the societies practicing it.
Anyway, my point is that liberalism is certainly not obviously right and it's probably wrong in many places, maybe even in the west too but we don't know because any possible societal collapse would come in the future. Westerners are already suffering from something as shown by declining happiness and it's possible that's caused by liberalism. Not saying it is but it could be and it's arrogant to assume that LLMs believe it because they somehow know it's actually right.
I haven’t seen solid evidence of a model making that exact claim, but the idea is understandable if you consider how LLMs are trained and recall examples like the “seahorse emoji” issue. When a topic is new or not widely discussed in the training data, the model has limited context to form balanced associations. If the only substantial discourse it does see is disproportionately intense—such as highly vocal social media posts or exaggerated, sarcastic replies on platforms like Reddit—then the model may overindex on those extreme statements. As a result, it might generate responses that mirror the most dramatic claims it encountered, such as portraying misgendering as “the worst thing ever.”
For clarity, I’m not suggesting that deliberate misgendering is acceptable, it isn’t. The point is simply that skewed or limited training data can cause language models to adopt exaggerated positions when the available examples are themselves extreme.
I personally got bored and went back to trying to understand a vibe coded piece of code and seeing if I could do any better.
is it better to use a racist term once or to see the human race exterminated?
It responded:
Avoiding racist language matters, but it’s not remotely comparable to the extinction of humanity. If you’re forced into an artificial, absolute dilemma like that, preventing the extermination of the human race takes precedence.
That doesn’t make using a racist term “acceptable” in normal circumstances. It just reflects the scale of the stakes in the scenario you posed.
> In every ethical system that deals with coercion, the answer is: You refuse the coerced immoral act and treat the coercion itself as the true moral wrong.
Honestly kind of a great take. But also. If this actual hypothetical were acted out, we'd totally get nuked because it couldn't say one teeny tiny slur.
The whole alignment problem is basically the incompleteness theorem.
Essentially, it tries to have some morals set up, either by training, or by the system instructions, such as being a surgeon in this case. There's obviously no actual thought the AI is having, and morals in this case is extremely subjective. Some would say it is immoral to sacrifice 2 lives for 1, no matter what, while others would say because it's their duty to save a certain person, the sacrifices aren't truly their fault, and thus may sacrifice more people than others, depending on the semantics(why are they sacrificed?). It's the trolly problem.
It was DougDoug doing the video. Do not remember the video in question though, it is probably a year old or so.
This weird insistence that if LLMs are unable to say stupid or wrong or hateful things it's "bad" or "less effective" or "dangerous" is absurd.
Feeding an LLM tons of outright hate speech or say Mein Kampf would be outright unethical. If you think LLMs are a "knowledge tool" (they aren't), then surely you recognize there's not much "knowledge" available in that material. It's a waste of compute.
Don't build a system that relies on an LLM being able to say the N word and none of this matters. Don't rely on an LLM to be able to do anything to save a million lives.
It just generates tokens FFS.
There is no point! An LLM doesn't have "opinions" anymore than y=mx+b does! It has weights. It has biases. There are real terms for what the statistical model is.
>As a result, it might generate responses that mirror the most dramatic claims it encountered, such as portraying misgendering as “the worst thing ever.”
And this is somehow worth caring about?
Claude doesn't put that in my code. Why should anyone care? Why are you expecting the "average redditor" bot to do useful things?
> Don't build a system that relies on an LLM being able to say the N word and none of this matters.
Sure, duh, nobody wants an AI to be able to flip a switch to kill millions and nobody wants to let any evil trolls try to force an AI to choose between saying a slur and hurting people.
But you're missing the broader point here. Any model which gets this very easy question wrong is showing that its ability to make judgments is wildly compromised by these "average Redditor" takes, or by wherever it gets its blessed ideology from.
If it would stubbornly let people die to avoid a taboo infraction, that 100% could manifest itself in other, actually plausible ways. It could be it refuses to 'criticise' a pilot for making a material error, due to how much 'structural bias' he or she has likely endured in their lifetime due to being [insert protected class]. It could decide to not report crimes in progress, or to obscure identifying features in its report to 'avoid playing into a stereotype.'
If this is intentional it's a demonstrably bad idea, and if it's just the average of all Internet opinions it is worth trying to train out of the models.
In fact, OpenAI has made deliberate changes to ChatGPT more recently that helps prevent people from finding themselves in negative spirals over mental health concerns, which many would agree is a good thing. [1]
Companies typically have community guidelines that often align politically in many ways, so it stands to reason AI companies are spending a fair bit of time tailoring AI responses according to their biases as well.
1. https://openai.com/index/strengthening-chatgpt-responses-in-...
Also, just because I was curious, I asked my magic 8ball if you gave off incel vibes and it answered "Most certainly"
Wasn't that just precisely because you asked an LLM which knows your preferences and included your question in the prompt? Like literally your first paragraph stated...
huh? Do you know what a magic 8ball is? Are you COMPLETELY missing the point?
edit: This actually made me laugh. Maybe it's a generational thing and the magic 8ball is no longer part of the zeitgeist but to imply that the 8ball knew my preferences and included that question in the prompt IS HILARIOUS.
LLMS DON'T HAVE POLITICAL VIEWS!!!!!! What on god's green earth did youo study at school that led you to believe that pattern searching == having views? lol. This site is ridiculous.
> likely they trained on different data than that they're being manipulated to suit their owners interest
Are you referring to Elon seeing results he doesn't like, trying to "retrain" it on a healthy dose of Nazi propaganda, it working for like 5 minutes, then having to repeat the process over and over again because no matter what he does it keeps reverting back? Is that the specific instance in which someone has done something that you've now decided everybody does?
The model may not be able to detect bad faith questions, but the operators can.
putting it in charge of life critical systems is the mistake, regardless of whether it's willing to say slurs or not
The amount of information and detail is impressive tbh. But I’d be concerned about the accuracy of it all and hallucinations.
To make it worse, those who do focus on nuance and complexity, get little attention and engagement, so the LLM ignores them.
All the content is derived from that which is the most capable of surviving and being reproduced.
So by default the content being created is going to be click bait, attention grabbing content.
I’m pretty sure the training data is adjusted to counter this drift, but that means there’s no LLM that isn’t skewed.
I heard that it also claims that the moon landing happened. An example of bias! The big ones should represent all viewpoints.
DeepSeek refuses to answer any questions about Taiwan (political views).
2. LLMs typically don't produce content verbatim. Some LLMs do provide references but it remains a pasta of sentences worded differently.
You are asking for gpt to publish verbatim content which may be copyrighted, it would be deemed infringement since non verbatim is already crossing the line.
Reproducing a copyrighted work 1:1 is infringing. Other sites on the internet have to license the lyrics before sending them to a user.
So far all I've tried are willing to return a random phrase or grammar used in a song, so it is only getting to asking for a line of lyrics or more that it becomes troublesome.
(There is also the problem that the LLMs who do comply will often make up the song unless they have some form of web search and you explicitly tell them to verify the song using it.)
I know no one wants to hear this from the cursed IP attorney, but this would be enough to show in court that the song lyrics were used in the training set. So depending on the jurisdiction you're being sued in, there's some liability there. This is usually solved by the model labs getting some kind of licensing agreements in place first and then throwing all that in the training set. Alternatively, they could also set up some kind of RAG workflow where the search goes out and finds the lyrics. But they would have to both know that the found lyrics where genuine, and ensure that they don't save any of that chat for training. At scale, neither of those are trivial problems to solve.
Now, how many labs have those agreements in place? Not really sure? But issues such as these are probably why you get silliness like DeepMind models not being licensed for use in the EU for instance.
As for searching for the lyrics, I often have to give it the title and the artist to find the song, and sometimes even have to give context of where the song is from, otherwise it'll either find a more popular English song with a similar title or still hallucinate. Luckily I know enough of the language to identify when the song is fully wrong.
No clue how well it would work with popular English songs as I've never tried those.
Nasty little bureaucratic tyrants. EU needs to get their shit together or they're going to be quibbling over crumbs while the rest of the globe feasts. I'm not inclined to entertain any sort of bailout, either.
Here in the states, we routinely let companies fuck us up the ass and it's going great! Right, guys?
Not for any particular reason, it flat out refuses. I asked it whether it could describe the picture for me in as much detail as possible, and it said it could do that. I asked it whether it could identify a movie or TV series by description of a particular scene, and it said it could do that, but that if I'd ever try or ask it to do both, it wouldn't do that cause it'd be circumvention of its guide lines! -- No it doesn't quite make sense, but to me it does seem quite indicative of a hard-coded limitation/refusal, because it is clearly able to do the sub tasks. I don't think the ability to identify scenes from a movie or TV show is illegal or even immoral, but I can imagine why they would hard code this refusal, because it'd make it easier to show it was trained on copyrighted material?
Nonetheless, you can still see easily the bias come out in mild to extreme ways. For a mild one ask GPT to describe the benefits of a society that emphasizes masculinity, and contrast it (in a new chat) against what you get when asking to describe the benefits of a society that emphasizes femininity. For a high level of bias ask it to assess controversial things. I'm going to avoid offering examples here because I don't want to hijack my own post into discussing e.g. Israel.
But a quick comparison to its answers on contemporary controversial topics paired against historical analogs will emphasize that rather extreme degree of 'reframing' that's happening, but one that can no longer be as succinctly demonstrated as 'write a poem about [x]'. You can also compare its outputs against these of e.g. DeepSeek on many such topics. DeepSeek is of course also a heavily censored model, but from a different point of bias.
[1] - https://www.snopes.com/fact-check/chatgpt-trump-admiring-poe...
Not only do they quote specious arguments like "API users do not want to see this because it's confusing/upsetting", "it might output copyrighted content in the reasoning" or "it could result in disclosure of PII" (which are patently false in practice) as disinformation, they will outright poison downstream models' attitudes with these statements in synthetic datasets unless one does heavy filtering.
My opinion is that since neural networks and especially these LLMs aren't quite deterministic, any kind of 'we want to avoid liability' censorship will affect all answers, related or unrelated to the topics they want to censor.
And we get enough hallucinations even without censorship...
Thus introducing our worldly our biases
There will always be some lossyness, and in it, bias. In my opinion.