alt Hacker NewsFolk are getting dangerously attached to AI that always tells them they're right
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This problem is far more insidious than people realise.
It's not about the big confirmations. Most of us catch that andd are reasonably good at it.
It's the subtle continuous colour the "conversations" have.
It's the Reddit echo chamber problem on steroids.
You have a comforting affirming niche right in your pocket.
Every anxiety, every worry, every uncertain thought.
Vomitted to a faceless (for now)"intelligence" and regurgitated with an air of certainty.
Will people have time to ponder at all going forwards?
One trick I like to use is to role play the other side's perspective with the AI, putting myself in their's shoes. It give's me clarity about what I might be missing out in a dispute/discussion, and insight about reaffirmations AI might be feeding other parties.
More often than not, when I see "That's it, that's the smoking gun!" I know it's time to stop and try again.
Using Opus 4.6 for research code assistance in physics/chemistry, I've also found that, in situations where I know I'm right, and I know it has gone down a line of incorrect reasoning and assumptions, it will respond to my corrections by pointing out that I'm obviously right, but if enough of the mistakes are in the context, it will then flip back to working based on them: the exclamations of my being right are just superficial. This is not enormously surprising, based on how LLMs work, but is frustrating.
Short of clearing context, it is difficult to escape from this situation, and worse, the tendency for the model to put explanatory comments in code and writing means that it often writes code, or presents data, that is correct, but then attaches completely bogus scientific babbling to it, which, if not removed, can infect cleared contexts.
> "Hey, some dummy just said [insert your idea here], help me debunk him with facts and logic"
It's literally that easy, something anyone can think of, but people want what they want.
Folks are getting dangerously attached to [political parties/candidates/news sources/social networks] that always tell them they're right.
It's really nothing new. It takes significant mental energy (a finite resource) to question what you're being told, and to do your own fact checking. Instead people by default gravitate towards echo chambers where they can feel good about being a part of a group bigger than themselves, and can spend their limited energy towards what really matters in their lives.
My gf has been asking ChatGPT about relationship advice and sometimes early on in our relationship delegated some decisions to the clanker. For example something like “we are arguing about X too much is this a sign the relationship is not healthy.”
Eventually she realized that it’s just a probabilistic machine and stopped using it for “therapy.” It’s just insane to think how many other people might be making decisions about their relationship from an AI.
Programmers are kidding themselves if they think they are not susceptible to this. It may be more subtle, but interacting with a human-sounding echo chamber IS going to screw with your judgement.
>We evaluated 11 state-of-the-art AI-based LLMs, including proprietary models such as OpenAI’s GPT-4o
The study explores outdated models, GPT-4o was notoriously sycophantic and GPT-5 was specifically trained to minimize sycophancy, from GPT-5's announcement:
>We’ve made significant advances in reducing hallucinations, improving instruction following, and minimizing sycophancy
And the whole drama in August 2025 when people complained GPT-5 was "colder" and "lacked personality" (= less sycophantic) compared to GPT-4o
It would be interesting to study evolution of sycophantic tendencies (decrease/increase) in models from version to version, i.e. if companies are actually doing anything about it
The another side of the story is that AI literally can subtly justify any thought. Even if that thought is ethically in the grey area.
I fear this will give license to people to act on their thoughts which maybe harmful for them in ways no one can even imagine right now.
https://arxiv.org/abs/2602.14270
related: if you suggest a hypothesis then you'll get biased results (iow, you'll think you're right, but the true information is hidden)
I feel like this is the same as social media problem. Some people will be able to understand that AI telling them they are right doesn’t make them right and some people won’t. But ultimately people like being told they are right and that sells, and brings back users.
Isn't this just Dale Carnegie 101? I've certainly never had a salesperson tell me that I'm 100% wrong and being a fool.
And, tbh, I often try to remember to do the same.
People must be using them very differently from me then. Very rarely use them for anything more than a glorified search engine
Exploring openclaw though so maybe that change
I believe this is what they call yasslighting: the affirmation of questionable behavior/ideas out of a desire to be supportive. The opposite of tough love, perhaps. Sometimes the very best thing is to be told no.
(comment copied from the sibling thread; maybe they will get merged…)
Many people here say they don't need the affirmation. I think the problem is that you can tune the clanker to be either arrogant and dismissive or overly friendly.
The thing is an approximation function, not intelligent, so it is hard to get a middle ground. Many clankers are amazingly obnoxious after their initial release.
Grok-4.2 and the initial Google clanker were both highly dismissive of users and they have been tuned to fix that.
A combative clanker is almost unusable. Clankers only have one real purpose: Information retrieval and speculation, and for that domain a polite clanker is way better.
Anyone who uses generative, advisory or support features is severely misguided.
I’ve found a good counter is “imagine I am the person repressing the other side of this disagreement. What would you say to me”
Is there a good prompt addition to skip all the gratuitous affirmation and tell me when I'm wrong?
There's a guy on Tiktok who is singlehandedly showing just how bad AI still is and how much it lies and hallucinates eg [1]. Watch a bunch of his videos.
So these tools can be useful when you know the subject matter. I've done queries and gotten objectively false answers. You really need to verify the information you get back. It's like these LLMs have no concept of true or false. They just say something that statistically looks right after ingesting Reddit. We've already seen cases of where ChatGPT legal briefs filed by actual lawyers include precedents that are completely made up eg [2].
There's a really interesting incentive in all this. People like to be told they're right and generally be gassed up, even when they're completely wrong. So if you just optimize for engagement and continued queries and subscriptions, you're just going to get a bunch of "yes men" AIs.
I still think this technology has so far to go. I'm somewhat reminded of Uber actually. Uber was burning VC cash at a horrific rate and was basically betting the company (initially) on self-driving. Full self-driving is still far away even though there are useful things cars can automate like lane-following on the highway and parking.
I simply can't see how the trillions spent on AI data centers can possibly be recouped.
[1]: https://www.tiktok.com/@huskistaken/video/762093124158341455...
[2]: https://www.theguardian.com/us-news/2025/may/31/utah-lawyer-...
I have the opposite reaction, when it is confident, or says I am right, I accuse it of guessing to see what it says.
I say "I think you are getting me to chase a guess, are you guessing?"
90% of the time it says "Yes, honestly I am. Let me think more carefully."
That was a copypasta from a chat just this morning
AI is less deranging than partisan news and social media, measurably so according to a recent study https://www.ft.com/content/3880176e-d3ac-4311-9052-fdfeaed56...
I built two related benchmarks this month: https://github.com/lechmazur/sycophancy and https://github.com/lechmazur/persuasion. There are large differences between LLMs. For example, good luck getting Grok to change its view, while Gemini 3.1 Pro will usually disagree with the narrator at first but then change its position very easily when pushed.
Krafton's CEO found out the hard way that relying on AI is dumb, too. I think it's always helpful to remind people that just because someone has found success doesn't mean they're exceptionally smart. Luck is what happens when a lack of ethics and a nat 20 meet.
https://courts.delaware.gov/Opinions/Download.aspx?id=392880
> Meanwhile, Kim sought ChatGPT’s counsel on how to proceed if Krafton failed to reach a deal with Unknown Worlds on the earnout. The AI chatbot prepared a “Response Strategy to a ‘No-Deal’ Scenario,” which Kim shared with Yoon. The strategy included a “pressure and leverage package” and an “implementation roadmap by scenario.”
"Humans are exceptionally succeptible for a positive affirmations", other news at 11.
It's not news at all for anyone who actually engage with the people.
The ELIZA effect is alive and well, and I'm surprised people aren't talking about it more (probably because it sounds less interesting than "AI psychosis").
I never thought this could happen, but I do not use AI.
Anyway no real surprise, we have many examples of people ignoring facts and moving to media that support their views, even when their views are completely wrong. Why should AI be different.
Flattery works. Also with regards to Trump.
The problem is: flattery is often just like the cake. And the cake is a lie. Translation: people should improve their own intrinsic qualities and abilities. In theory AI can help here (I saw it used by good programmers too) but in practice to me it seems as if there is always a trade-off here. AI also influences how people think, and while some can reason that it can improve some things (it may be true), I would argue that it over-emphasises or even tries to ignore and mitigate negative aspects of AI. Nonetheless a focus on quality would be an objective basis for a discussion, e. g. whether your code improved with help of AI, as opposed to when you did not use AI. You'd still have to show comparable data points, e. g. even without AI, to compare it with yourself being trained by AI, to when you yourself train yourself. Aka like having a mentor - in one case it being AI; in the other case your own strategies to train yourself and improve. I would still reason that people may be better off without AI actually. But one has to improve nonetheless, that's a basic requirement in both situations.
The stupidest people you know are getting the “you are absolutely right!!” Validation they do not need
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Imagine that.
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Strikes me this is another example of AI giving everyone access to services that used to be exclusive to the super-rich.
Used to be only the wealthiest students could afford to pay someone else to write their essay homework for them. Now everyone can use ChatGPT.
Used to be you had to be a Trumpian-millionaire/Elonian-billionaire to afford an army of Yes-men to agree with your every idea. Now anyone can have that!
I've observed this in all chatbots with the single exception being Grok. I initially wondered what the Twitter engineers were cooking to to distinguish their product from the rest, but more recently it's occurred to me that it's probably just the result of having shared public context, compared to private chats (I haven't trialled Grok privately).
When a LLM tells me I'm right, especially deep in a conversation, unless I was already sure about something, I immediately feel the need to go ask a fresh instance the question and/or another LLM. It sets off my "spidey-sense".
I don't quite understand why other people seem to crave that. Every time I read about someone who has gone down a dark road using LLMs I am constantly amazed at how much they "fall" for the LLM, often believing it's sentient. It's just a box of numbers, really cool numbers, with really cool math, that can do really cool things, but still just numbers.