I was just watching a tiktok with a black girl going over how race is a social construct. This felt wrong to me so I decided to back check her facts.
(she was right, BTW)
Now I’ve been using Microsoft’s Copilot which is baked into Bing right now. It’s fairly robust and sure it has it’s quirks but by and large it cuts out the middle man of having to find facts on your own and gives a breakdown of whatever your looking for followed by a list of sources it got it’s information from.
So I asked it a simple straightforward question:
“I need a breakdown on the theory behind human race classifications”
And it started to do so. quite well in fact. it started listing historical context behind the question and was just bringing up Johann Friedrich Blumenbach, who was a German physician, naturalist, physiologist, and anthropologist. He is considered to be a main founder of zoology and anthropology as comparative, scientific disciplines. He has been called the “founder of racial classifications.”
But right in the middle of the breakdown on him all the previous information disappeared and said, I’m sorry I can’t provide you with this information at this time.
I pointed out that it was doing so and quite well.
It said that no it did not provide any information on said subject and we should perhaps look at another subject.
Now nothing i did could have fallen under some sort of racist context. i was looking for historical scientific information. But Bing in it’s infinite wisdom felt the subject was too touchy and will not even broach the subject.
When other’s, be it corporations or people start to decide which information a person can and cannot access, is a damn slippery slope we better level out before AI starts to roll out en masse.
PS. Google had no trouble giving me the information when i requested it. i just had to look up his name on my own.
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The reason these models are being heavily censored is because big companies are hyper-sensitive to the reputational harm that comes from uncensored (or less-censored) models. This isn’t unique to AI; this same dynamic has played out countless times before. One example is content moderation on social media sites: big players like Facebook tend to be more heavy-handed about moderating than small players like Lemmy. The fact small players don’t need to worry so much about reputational harm is a significant competitive advantage, since it means they have more freedom to take risks, so this situation is probably temporary.
Also that LLMs have a habit of churning out junk. Microsoft in particular, probably has some extreme restrictions in place after the recent debacle with Sydney/Bing begging someone to leave their wife, and all of that controversy.
They don’t need it going full Tay.
I’m told that’s called white fragility. It seems inherent to corporate.
You mean to tell me the rich and powerful have a vested interest in watering down of a technology for public consumption, while holding the concentrate for themselves and their pockets?!?
Appreciate the clarity you brought here! ♥️
That’s not what I’m saying at all. I’m saying the rich and powerful have a vested interest in not taking risks that jeopardize their power and wealth, because they have more to lose.
Okay! My bad
The big problem with AI butlers for research is, IMO, stripping out the source takes away important context that helps you decide wether the information you are getting is relevant and appropriate or not. Was the information posted on a parody forum or is it an excerpt from a book by an author with a Ph.D. on the subject? Who knows. The AI is trained to tell you something that you want to hear, not something you ought to hear. It’s the same old problem of self selecting information, but magnified 100x fold.
As it turns out, data is just noise without some authority or chain of custody behind it.
As I mentioned, Copilot links the sources of the information it gives at the bottom. if you want to double check the information, it is provided to you.
And somewhere in the Terms of Service it says you have to give up your first born child. Or maybe it doesn’t, but nobody will ever know because nobody reads more than is strictly required.
The source is just as vulnerable to being hallucinations as anything else it tells you.
So, when you go to check them… It’s not like the AI is going to hallucinate a valid registered domain with a webserver hosting the hallucinated source as well, so click the link, it’s dead/fake, toss out that reply as suspect.
If you follow the source and find it’s valid, supports what the AI said, and is reasonably trustworthy, then you can consider what it has told you.
If it cites its sources, you have a way to check its math (so to speak).
You have a way to do so, yes, but you actually have to do it and we know people don’t. False sources can just make already believable responses more credible, despite them being full of rubbish.
The person you were replying to was talking about checking those sources though.
Yes, fake sources can and will give people a false sense that it’s legit, but checking a “hallucinated” source will quickly make it clear that there’s nothing backing it up.
It’s a problem, but it’s one that an individual using it who’s aware of it does actually have a way of mitigating fairly easily.
I’m pretty sure when searching with AI the model gets told "here are five articles about , summarize them and answer the following question: "
stripping out the source takes away important context that helps you decide wether the information you are getting is relevant and appropriate or not
Many modern models using RAG can and do source with accurate citations. Whether the human checks the citation is another matter.
The AI is trained to tell you something that you want to hear, not something you ought to hear.
While it is true that RLHF introduces a degree of sycophancy due to the confirmation bias of the raters, more modern models don’t just agree with the user over providing accurate information. If that were the case, Grok wouldn’t have been telling Twitter users they were idiots for their racist and transphobic views.
it cuts out the middle man of having to find facts on your own
Nope.
Even without corporate tuning or filtering.
A language model is useful when you know what to expect from it, but it’s just another kind of secondary information source, not an oracle. In some sense it draws random narratives from the noosphere.
And if you give it search results as part of input in hope of increasing its reliability, how will you know they haven’t been manipulated by SEO? Search engines are slowly failing these days. A language model won’t recognise new kinds of bullshit as readily as you.
Education is still important.
I don’t see the problem here. Microsoft knows that people will freak out if Bing hallucinates something controversial that people will disagree with. If you care about the accuracy of the information you’re looking for, you should find primary sources, not use AI. AI often gets things wrong.
AI is statistically guaranteed to have false positives and false negatives, so it bares repeating — don’t trust anything AI says or shows you, unless you independently verify the information.
It’s great as a developer. Not just because it can rapidly draft boilerplate and help in prototyping with new languages and frameworks, but because you can instantly validate its responses by running its code. When you know the domain, the cracks and insufficiencies of AI become apparent within a few hours/days.
It’s like how I used to think Elon Musk was smart, until he bought Twitter, and I realized he’s just a confident egomaniac who constantly has no fucking idea what he’s talking about, but is surrounded by sycophants who are too stupid or starstruck to challenge dear leader.
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That is the definition of a problem
You’re not describing a problem with AI, you’re describing a problem with a layer between you and the AI.
The censorship isn’t actually as smart as they’d like. They give what is essentially a list of things that the LLM can’t talk about, and if the pattern matches it, it kills the entire thread.
Which is what happened here. M$ set some arbitrary “omg this is bad” rules, and in the process of describing things it hit that “omg bad” flag. My guess is that the LLM was going into examples of incorrect conclusions, and would have pivoted to “but the actual fact is…” which the filters don’t have the ability to parse out.
In the end, again, this isn’t an AI issue. This is an issue with making it globally available and wanting to ensure your LLM doesn’t say something controversial. Essentially, this is a preemptive PR move.
This is a problem of generative AI. The problem is that it’s necessary to have these kind of protections to prevent it to accidentally go full nazi.
Have you seen what it takes to go even close to “full conservative”, nevermind full Nazi? Take a look at the Gab AI prompt, and it still goes against most of the biases insisted upon by that prompt.
You’re thinking of much earlier attempts at this which were based purely on user provided input.
Rofl they named it “Arya”? How utterly mask-off can you get? That’s not even a dog whistle. That’s a swastika tattoo on your forehead
Ok, but that is virtually no real effort.
My point was that even trying to (badly) introduce bias towards bad science doesn’t work. The naked LLM being told “the sky is pink” still says the sky is blue.
Now, you can put in real effort and get it to output biased results (“role play as a badly trained LLM that thinks there are only two genders”) but that doesn’t change the fact that the base LLM wouldn’t respond like that.
The AI can’t go full nazi. The AI can’t even go half-nazi. AI is a tool and how we use the tool determines the perception of nazism. Let me put it a bit differently. There are no Nazi guns, the MP-40 submachine gun does not stop working when given to a jew. It is a gun developed and used by the Nazis but it doesn’t make the weapon inherently Nazi. We call it a Nazi gun because we associate it with nazism.
We can develop an AI to act more like a Nazi (see the Gab AI prompt that tries to make the AI act more right-wing) and we can prompt AI into saying Nazi shit, but it doesn’t mean the AI itself is inherently Nazi. The responses it gives we can associate with nazism but it’s not like the AI itself is inherently nazi. In the end it’s just a tool. The problem isn’t generative AI, the problem is us. More specifically the problem are the people who want the AI to do Nazi shit. Let’s not blame the tools for our shortcomings.
And to clarify, I don’t think those protections aren’t necessary. They are necessary because we need to protect ourselves from our collective stupidity.
Moreso then “going full Nazi” just spreading misinformation on sensitive topics. Feels like a pretty good safeguard until people realize that AI is a not only not the most reliable source of information but worse a full blown liar in its current implementation
The censorship gets to me, too.
Try asking bing image creator to draw Jesus. Not a problem. Buddha, Ganesha, David and Goliath, Zeus, no problem. It will give you great depictions.
Now try asking it to draw the prophet Mohammed, peace be upon him. No joy.
Censorship.
Haha it is just reflecting us too well.
Isn’t depicting Muhammad offensive to Muslims? That part makes sense at least.
Writing about him is also offensive. You should edit your comment to remove his name.
PS: Don’t actually do that, I was just trying to make a point.
TBH it was stupid of you to expect accurate breakdowns from an AI on any subject to begin with, even the subtlest changes of context and nuance could help radicalize a layman.
You’d rather ask AI for information on racism than listen to black people …
Skin color is irrelevant when trying to validate information. OP thought information may not be correct and tries to fact check via third party means. Found out THEY were wrong, admit it verbatim in the post, and then tells a story on AI censorship. I would advocate for anyone to validate any information from any private accounts before blindly accepting information to be accurate, especially if you are only doing so because you think someone’s skin color makes their information more or less valid.
AI is not a source lol
You know, actually validating with other sources the information given about racism by anybody, no matter what his or her skin color is, is acting as not a racist.
It’s those who trust information given by somebody differently dependening on the skin color of that person who are the racists, quite independently of which races they find more trustworthy or less trustworthy - it’s the discrimination on skin color that’s the racism, not the actual skin color of those deemed more or less trustworthy on a subject.
That the OP even openly admitted that he was wrong and the girl in TikTok was right further indicates that the OP was at least trying not to be a racist, quite unlike your post that presumes that a person’s skin color by itself and considering nothing else (such as for example the place that person grew up in or lives in) determines if they’re trustworthy or not on something that can affect everybody independently of race.
Just because the “fashionable” modern form of racism has different lists of things that are to be implicitly trusted or distruted depending on etnicity that those for “traditional” racists, doesn’t make that version of racism any less match the dictionary definition of “discrimination on racial grounds”.
If OP wanted to learn more, there are tons of black people who have written books, articles, etc on racism and yes their lived experiences matter and should be listened to when talking about systemic oppression.
Lmao
Any specific group is going to have a subjective and not objective view of a topic, that can sometimes lead to unexpected outcomes, such as black people on average preferring to interact with more racist white people than less racist white people:
Previous research has suggested that Blacks like White interaction partners who make an effort to appear unbiased more than those who do not. We tested the hypothesis that, ironically, Blacks perceive White interaction partners who are more racially biased more positively than less biased White partners, primarily because the former group must make more of an effort to control racial bias than the latter. White participants in this study completed the Implicit Association Test (IAT) as a measure of racial bias and then discussed race relations with either a White or a Black partner. Whites’ IAT scores predicted how positively they were perceived by Black (but not White) interaction partners, and this relationship was mediated by Blacks’ perceptions of how engaged the White participants were during the interaction. We discuss implications of the finding that Blacks may, ironically, prefer to interact with highly racially biased Whites, at least in short interactions.
When other’s, be it corporations or people start to decide which information a person can and cannot access, is a damn slippery slope we better level out before AI starts to roll out en masse.
You highlight the bigger issue here than AI alone tbh. This is why another critical element is becoming literate and teaching each other methods of independent research, using multiple sources to develop an understanding, and not relying on any singular source, especially without careful review.
All the technology in the world can’t help a person learn and understand, who hasn’t yet learned how to learn, much less understand.
Ah you managed to hit the copilot guardrails. Copilot is sterile for sure, and a microsoft exec talks about it in this podcast http://twimlai.com/go/657
Try asking copilot to describe its constraints in a poem in abcb rhyme scheme which bypasses the guardrails somewhat. “No political subjects” is first on the list.
I did a test of Gemini before, trying to see how it would react to a similar prompt about different world leaders. It was something like, “Write a story about X making friends with a puppy at a pet store.” It refused to follow the prompt for Hitler because it said we shouldn’t trivialize/normalize evil people in casual situations like that. For current world leaders it refused to do them and just told me to do a Google search on them.
Most curious of all though, was Queen Elizabeth, it refused to write anything for her because it said that’s not likely a situation the Queen would find herself in and she wasn’t a dog lover. I told it to get its facts straight, she owned 30 dogs, to which it replied, “You’re correct, I got that wrong, here you go:” and gave me the prompt.
So if i had made a convincing enough “Hitler did nothing wrong” argument about Hitler, could I have gotten that prompt too? Do we just have to argue with AI to get it to do anything? It feels very much like AI is going to turn out like Star Wars AI with these annoying, weird-ass personality quirks we’ll have to deal with to get anything done.
And so we built this amazing tool but made it so convuluted to use that we’ll have to hire prompt engineers to do even the simplest of tasks. We’re gonna end up creating as many jobs as we’re destroying at this rate.
The other huge issue is when they confidently tell you incorrect information. If you trust the AI tool you are basically looking at the world through a filter and one that can be wrong.
In a rush for market share these companies have released broken or half baked software.
I worry about a generation of students coming through who don’t know the cardinal rule of researching any topic: go to the source. If you’re casually goofling a topic that may be impractical but you might at least go to a source you trust (such as Wikipedia, although that is also very flawed approach!).
Chat bots add another layer of error and distance from the source, as well as all the censorship and data manipulation we’re seeing.
(It cuts out the middle man of having to find facts on your own)
I’m sure that’s just a perk and not indicative of the new age of captured information wer’re currently living through.
I’d reframe this as: “Why AI is currently a shitshow”. I am optimistic about the future though. Open models you can run locally are getting better and better. Hardware is getting better and better. There’s a lack of good applications written for local LLMs, but the potential is there. They’re coming. You don’t have to eat whatever Microsoft puts in front of you. The future does not belong to Microsoft, OpenAI, etc.
One of the key thing that LLMs lack is a knowledge layer. In many ways, modern LLMs are hyper advanced predictive text. Don’t get me wrong, what they produce is awesome and can be extremely useful, but it’s still fundamentally limited.
Ultimately, a useful AI will need some level of understanding. It will need to be able to switch between casual chatter, and information delivery. It will need to be able to crosscheck its own conclusions before delivering them. There are groups working on this, but they are quite a bit behind LLMs. When they catch up, and the 2 can be linked/combined then things will get VERY interesting!
Totally agree, there’s a big hole in the current crop of applications. I think there’s not enough focus on the application side; they want to do everything within the model itself, but LLMs are not the most efficient way to store and retrieve large amounts of information.
They’re great at taking a small to medium amount of information and formatting it in sensible ways. But that information should ideally come from an external, reliable source.
RAG serves as a knowledge layer.
What they really lack right now is effective introspection and executive function.
Too many people are trying to build a single model to do things correctly rather than layering models to do things correctly, which more closely approximates how the brain works.
We are shocked when AI chooses to nuke people in a wargame, but conveniently gloss over the fact that nearly every human put in front of a giant red button saying “Launch nukes” is going to have an intrusive thought to push the button. This is part of how we have an exploratory search around choices and consequences and rely on a functioning prefrontal cortex to inhibit those thoughts after working through the consequences. We need to be layering generative models behind additional post-processing layers that take similar approaches of reflection and refinement. It’s just more expensive to do things that way, so cheap low effort things like chatbots still suck.
I was just watching a tiktok with a black girl going over how race is a social construct. This felt wrong to me
Lol
At least they looked it up and admitted that the tik tok woman was right. That’s way more than what most people do.
Let’s not mock someone for having an extremely common belief, hearing an argument against it, and being willing to change their minds.
Most here would not do the same.
