If the purpose is to read someone's _writing_, then I'm going to read it, for the sheer joy of consuming the language. Nothing will take that from me.
If the purpose is to get some critical piece of information I need quickly, then no, I'd rather ask an AI questions about a long document than read the entire thing. Documentation, long email threads, etc. all lend themselves nicely to the size of a context window.
And what do you do if the LLM hallucinates? For me, skim-reading still comes out on top because my own mistakes are my own.
If something has actual substance I'll watch the whole thing, but that's maybe 10% of videos I find in experience.
Many years ago I make a little proof-of-concept for displaying the transcript (closed captions) of a YouTube video as text, and highlighting a word would navigate to that timestamp and vice-versa. Such a thing might be valuable as a browser extension, now that I think of it.
Citation: https://ea.rna.nl/2024/05/27/when-chatgpt-summarises-it-actu...
> I just realised the situation is even worse. If I have 35 sentences of circumstance leading up to a single sentence of conclusion, the LLM mechanism will — simply because of how the attention mechanism works with the volume of those 35 — find the ’35’ less relevant sentences more important than the single key one. So, in a case like that it will actively suppress the key sentence.
> I first tried to let ChatGPT one of my key posts (the one about the role convictions play in humans with an addendum about human ‘wetware’). ChatGPT made a total mess of it. What it said had little to do with the original post, and where it did, it said the opposite of what the post said.
> For fun, I asked Gemini as well. Gemini didn’t make a mistake and actually produced something that is a very short summary of the post, but it is extremely short so it leaves most out. So, I asked Gemini to expand a little, but as soon as I did that, it fabricated something that is not in the original article (quite the opposite), i.e.: “It discusses the importance of advisors having strong convictions and being able to communicate them clearly.” Nope. Not there.
Why, after reading something like this, should I think of this technology as useful for this task? It seems like the exact opposite. And this is what I see with most LLM reviews. The author will mention spending hours trying to get the LLM to do a thing, or "it made xyz, but it was so buggy that I found it difficult to edit it after, and contained lots of redundant parts", or "it incorrectly did xyz". And every time I read stuff like that I think — wow, if a junior dev did that the number of times the AI did, they'd be fired on the spot.
See also, something like https://boston.conman.org/2025/12/02.1 where (IIRC) the author comes away with a semi-positive conclusion, but if you look at the list near the end, most of these things are something that any person would get fired for, and are things that are not positive for industrial software engineering and design. LLMs appear to do a "lot", but still confabulates and repeats itself incessantly, making it worthless to depend on for practical purposes unless you want to spend hours chasing your own tail over something it hallucinated. I don't see why this isn't the case. I thought we were trying to reduce the error rate in professional software development, not increase it.
> AI False Information Rate Nearly Doubles in One Year
> NewsGuard’s audit of the 10 leading generative AI tools and their propensity to repeat false claims on topics in the news reveals the rate of publishing false information nearly doubled — now providing false claims to news prompts more than one third of the time.
1. I don't read "terrible articles". I can skim an article and figure if something I'm interested in.
2. I actually do read terrible articles and I have terrible taste
3. Any "summarization" I do that isn't from my direct reading is evaluated by the discussion around it. Though nowadays that's more and more spotty.
I mainly use a custom prompt using ChatGPT via the Raycast app and the Raycast browser extension.
That said, I don’t feel comfortable with the level of AI being shoved into browsers by their vendors.
If it does interest me then I can explore it. I guess I do this once a week or so, not a lot.
And even reading an article about those myself doesn't make me insusceptible to misinformation of course. Most of the misinformation about these wars is spread on purpose by the parties involved themselves. AI hallucination doesn't really cause that, it might exacerbate it a little bit. Information warfare is a huge thing and it has been before AI came on the scene.
Ok, as a more specific example, recently I was thinking of buying the new Xreal Air 2. I have the older one but I have 3 specific issues with it. I used AI to find references about these issues being solved. This was the case and AI confirmed that directly with references, but in further digging myself I did find that there was also a new issue introduced with that model involving blurry edges. So in the end I decided not to buy the thing. The AI didn't identify that issue (though to be fair I didn't ask it to look for any).
So yeah it's not an allknowing oracle and it makes mistakes, but it can help me shave some time off such investigations. Especially now that search engines like google are so full of clickbait crap and sifting through that shit is tedious.
In that case I used OpenWebUI with a local LLM model that speaks to my SearXNG server which in turn uses different search engines as a backend. It tends to work pretty well I have to say, though perplexity does it a little better. But I prefer self-hosting as much as I can (of course the search engine part is out of scope there).
I gave the example of wars, because it’s obvious, even for you, and you won’t relativize away the same way how you just did with AI misinformation, which affects you the exact same way.
Most recently, a new ISP contract: because it's both low stakes enough where I don't care much about inaccuracies (it's a bog standard contract from a run of the mill ISP), there's basically no information in there that the cloud vendor doesn't already have (if they have my billing details) but also where I'm curious about whether anything might jump out, all while not really wanting to read the 5 pages of the thing.
Just went back to that, it got both all of the main items (pricing, contract terms, my details) correctly, but also the annoying fine print (that I referenced, just in case). Also works pretty well across languages, though that depends on the model in question a bunch.
I feel like if browsers or whatever get the UX of this down, people will upload all sorts of data into those vendors that they normally shouldn't. I also think that with nuanced enough data, we'll eventually have the LLM equivalent of Excel messing up data due to some formatting BS.