A new study from Columbia Journalism Review showed that AI search engines and chatbots, such as OpenAI’s ChatGPT Search, Perplexity, Deepseek Search, Microsoft Copilot, Grok and Google’s Gemini, are just wrong, way too often.
I miss the days when Google would just give a snippet of a Wikipedia article at the top and you just click the “read more” button. It may not have been exactly what you were looking for but at least it wasn’t blatantly wrong. Nowadays you have to almost scroll down to the bottom just to find something relevant.
i almost think this is getting worse as the internet grows, there’s so much more information out there now and it’s easier and easier to push content further. i’m not surprised it’s more and more difficult to filter through the bs
To add to this. While there is “more information” that information is increasingly locked down and unsearchable. Things that used to be easy to find are now hidden in the walled gardens of sites like Facebook, X (Formerly Twitter), etc. Google Search and similar engines basically only searche ads now as everything else is locked down. It’s an internet full of data… that we can’t easily access.
I’m confidently wrong a lot of the time too. But I mainly do that just to fuck with people.
In all seriousness; studies are the first step to general knowledge outside professional circles and by extension, legislation made on it.
LLMs hallucinate. In other words, water is wet
They are in the end BS generation machines that are trained so much they accidentally happen to be right often enough.
Always ask AI for sources and validate them. You can also request AI to use only certain sources of your liking. Never go blind to those answers.
They get you 80 to 90 percent close to generally solving most problems asked. Sure they need fact checked as any info does. They are of major use in all areas of study and life. Just not the god everyone wants it to be.
They are less useful than a Wikipedia search and a dictionary. They can functionally replace humans in 0 fields that were not already automatable by machines. They are useless in any situation that warrants any degree of caution about safety.
85-90% is way over-estimated, it gets significantly worse dealing with specific tasks. And even if it was 85-90%, that’s not good enough, even remotely, for just about anything. Humans make errors too, but inconsistently and inversely proportional to experience. This makes no difference to the LLM though, it will always make errors at that exact rate. The kinds of errors it can make are also not just missteps but often pure delusion and very far from what the input was requesting. They cannot reason. They have no rationale. They’re imitation in its most empty form. They cannot even so much as provide information reliably.
They also ruin every single industry they come into contact with, and even worse they have utterly destroyed the usability of the internet. LLMs are a net negative for humanity in so many different ways. They deserve as much attention and investment as chatbots did back in 2005.
Their best use case scenario is in churning out an endless amount of lifeless soleless jpg background noise and word salad articles. Their best use case is in tricking people into giving them money or ad revenue. Scamming is the only thing they are anywhere near functionally useful for.
The problem when you keep moving the bar like that is that you will find yourself supporting stupid gimmicks instead of practical technology.
The problem is that the sales pitch of these AI answering services in search engines is to save you time from having to open search results and read them yourself. The problem with 80-90% accuracy is that if the summaries are hallucinated even once, you can no longer trust them implicitly, so in all cases you now have to verify what it says by opening search results and reading them yourself. It’s a convenience feature that doesn’t offer you any actual convenience.
Sure it’s impressive that they are accurate 80-90% of their time, but AI used in this context is of no actual value.
It’s a real issue. A strong use case for LLM search engines is providing summaries which combine lots of facts that would take some time to compile through searching the old fashioned way. But if it’s only 90% accurate and 10% hallucinated bullshit, it becomes very difficult to pick out the bullshit from the truth.
The other day I asked Copilot to provide an overview of a particular industrial sector in my area. It produced something that was 90% concise, accurate, readable and informative briefing, and 10% complete nonsense. It hallucinated an industrial estate that didn’t exist, a whole government programme that doesn’t exist, it talked about a scheme that went defunct 20 years ago as if it were still current, etc. If it weren’t for the fact that I was already very familiar with the subject, I might not have caught it. Anyone actually relying on that for useful work is in serious danger of making a complete tit of themselves.
Copilot sucks and I totally understand the POV. I stick with GPT, Mixtral. I don’t think their going anywhere anytime soon but they need significant actual refinement.
Nah, it’s just the ghost in the machine.
Tip: always add “True” string to the algorithm/s
