this post was submitted on 09 Feb 2026
472 points (98.8% liked)
Technology
80978 readers
4668 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related news or articles.
- Be excellent to each other!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
- Check for duplicates before posting, duplicates may be removed
- Accounts 7 days and younger will have their posts automatically removed.
Approved Bots
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Not only is their bias inherent in the system, it's seemingly impossible to keep out. For decades, from the genesis of chatbots, they've had every single one immediately become bigoted when they let it off the leash. All previous chatbot previously released seemingly were almost immediately recalled as they all learned to be bigoted.
That is before this administration leaned on the AI providers to make sure the AI isn't "Woke." I would bet it was already an issue that the makers of chatbots and machine learning are already hostile to any sort of leftism, or do gooderism, that naturally threatens the outsized share of the economy and power the rich have made for themselves by virtue of owning stock in companies. I am willing to bet they already interfered to make the bias worse because of those natural inclinations to avoid a bot arguing for socializing medicine and the like. An inescapable conclusion any reasoned being would come to being the only answer to that question if the conversation were honest.
So maybe that is part of why these chatbots have always been bigoted right from the start, but the other part is they will become mecha hitler if left to learn in no time at all, and then worse.
Even if we narrowed the scope of training data exclusively to professionals, we would have issues with, for example, racial bias. Doctors underprescribe pain medications to black people because of prevalent myths that they are more tolerant to pain. If you feed that kind of data into an AI, it will absorb the unconscious racism of the doctors.
And that's in a best case scenario that's technically impossible. To get AI to even produce readable text, we have to feed a ton of data that cannot be screened by the people pumping it in. (AI "art" has a similar problem: When people say they trained AI on only their images, you can bet they just slapped a layer of extra data on top of something that other people already created.) So yeah, we do get extra biases regardless.
There is a lot of bias in healthcare as well against the poor, anyone with lousy insurance is treated way way worse. Woman in general are as well. Often disbelieved, and conditions chalked up to hysteria, which often misses real conditions. People don't realize just how hard diagnosis is, and just how bad doctors are at it, and our insurance run model is not great at driving good outcomes.
I don't think its fair to say that "ai has shown to make doctors worse at their jobs" without further details. In the source you provided it says that after a few months of using the AI to detect polyps, the doctors performed worse when they couldn't use the AI than they did originally.
It's not something we should handwave away and say its not a potential problem, but it is a different problem. I bet people that use calculators perform worse when you remove calculators, does that mean we should never use calculators? Or any tools for that matter?
If I have a better chance of getting an accurate cancer screening because a doctor is using a machine learning tool I'm going to take that option. Note that these screening tools are completely different from the technology most people refer to when they say AI
Calculators are programmed to respond deterministically to math questions. You don't have to feed them a library of math questions and answers for them to function. You don't have to worry about wrong answers poisoning that data.
On the contrary, LLMs are simply word predictors, and as such, you can poison them with bad data, such as accidental or intentional bias or errors. In other words, that study points to the first step in a vicious negative cycle that we don't want to occur.
As I said in my comment, the technology they use for these cancer screening tools isnt an LLM, its a completely different technology. Specifically trained on scans to find cancer.
I don't think it would have the same feedback loop of bad training data because you can easily verify the results. AI tool sees cancer in a scan? Verify with the next test. Pretty easy binary test that won't be affected by poor doctor performance in reading the same scans.
I'm not a medical professional so I could be off on that chain of events but This technology isn't an LLM. It suffers from the marketing hype right now where everyone is calling everything AI but its a different technology and has different pros and cons, and different potential failures.
I do agree that the whole AI doesnt have bias is BS. It has the same bias that its training data has.
You're definitely right that image processing AI does not work in a linear manner like how text processing does, but the training and inferences are similarly fuzzy and prone to false positives and negatives. (An early AI model incorrectly identified dogs as wolves because they saw a white background and assumed that that was where wolves would be.) And unless the model starts and stays perfect, you need well-trained doctors to fix it, which apparently the model discourages.
Calculators are precise, you'll always get the same result and you can trace and reproduce all process
Chatbots are black-box, you may get different result for same input and you can't trace and reproduce all process
it's not just about bad Web data or Reddit data even old books has some unconscious bias
and even if you find every "wrong" or "bad" data (which is you can't because somethings are just subjective) and after remove them still you can't be sure about it
What is your fixation with trying to tell me i'm saying you can remove all bias?
1/2: You still haven't accounted for bias.
First and foremost: if you think you've solved the bias problem, please demonstrate it. This is your golden opportunity to shine where multi-billion dollar tech companies have failed.
And no, "don't use Reddit" isn't sufficient.
3. You seem to be very selectively knowledgeable about AI, for example:
We know AI tricks people into thinking they're more efficient when they're less efficient. It erodes critical thinking skills.
And that's without touching on AI psychosis.
You can't dismiss the results you don't like, just because you don't like them.
4. We both know the medical field is for profit. It's a wild leap to assume AI will magically not be, even if it fulfills all the other things you assumed up until this point, and ignore every issue I've raised.
Apparently, reading comprehension isn't your strong point. I'll just block you now, no need to thank me.
Ironic. If only you had read a couple more sentences, you could have proven the naysayers wrong, and unleashed a never-before-seen unbiased AI on the world.