this post was submitted on 13 Mar 2024
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An Amazon chatbot that’s supposed to surface useful information from customer reviews of specific products will also recommend a variety of racist books, lie about working conditions at Amazon, and write a cover letter for a job application with entirely made up work experience when asked, 404 Media has found.

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[–] [email protected] 112 points 5 months ago (5 children)

So this is the problem with AI, if you add guardrails you're a culture warrior 1984'ing the whole world, and if you don't now your tool will generate resumes with fake experience or recommend offensive books.

At the risk of sounding like a jackass, when do we start blaming people for asking for such things?

[–] [email protected] 95 points 5 months ago (1 children)

It's funny that this one does both at once. It lies about Amazon working conditions, meaning it probably has been censored in some way, but at the same time it is recommending Nazi books. Really shows Amazon's priorities when it comes to censorship.

[–] [email protected] 15 points 5 months ago (1 children)

At least Amazon is thinking of the shareholders.

[–] [email protected] 3 points 5 months ago* (last edited 5 months ago)

Although if I was to shareholder of Amazon i would be wondering why we even stock Nazi textbooks. Morality aside, they cannot really be that much of a market for them and even if there was the PR hit probably isn't worth it.

If it turns out there is a market for them we should probably separate off that part of the business to avoid PR blunders.

[–] [email protected] 32 points 5 months ago* (last edited 5 months ago) (1 children)

So this is the problem with AI, if you add guardrails you’re a culture warrior 1984’ing the whole world,

No this isn’t really a problem with the technology, though of course LLMs are extremely flawed in fundamental ways, it is a problem with conservatives being babies and throwing massive tantrums about any guardrails being added even when they are next to cliffs with 200 foot drops.

Conservatives and libertarians (who control most of these companies) want to try to figure this all out for themselves and are hellbent on trying the “no moderation” strategy first and haven’t thought past that step. This is what conservatives and libertarians always do, they might as well be a character archetype in commedia dell'arte at this point.

We can’t have an adult conversation about racism, sexism, hate against trans people or really even the basic concept of systematic stereotypes and prejudices because conservatives refuse to stop running around screaming, making this a conversation with children where everything has to be extremely simplified and black and white and we have to patiently explain over and over again the basic concept of a systematic bias and argue that it even exists.

Then these same people turn around and vote for people who literally want to control what women do with their unfertilized eggs while they act with a straight face like they give af about individual liberties or freedoms.

LLMs are fundamentally vulnerable to bias, we have to design LLMs with that in mind and first and foremost carefully structure and curate the training data we train an LLM on so that bias is minimized. The very idea of even thinking about the complexities usually sends conservatives right to outbursts of “that sounds like tyranny!” because they honestly just don’t have any of the skill sets that say, a liberal arts education that values the humanities, might provide you that could allow you to think about how to best solve problems that can’t truly be fairly solved and require empathizing with different groups.

Of course, nobody who has the power at AI companies is thinking about this either but…

[–] [email protected] 6 points 5 months ago (1 children)

How to you curate training data to remove biases without introducing bias? That’s the key problem here. I don’t think it’s unreasonable to be opposed to trading one bias for another. At least the initial bias is based on reality.

[–] [email protected] 13 points 5 months ago* (last edited 5 months ago) (1 children)

Because anybody who has taken a couple of humanities classes, english classes, philosophy classes, journalism/political science classes or who has spent time critically evaluating art, historical accounts or really anything other than just numbers, code and spreadsheets.... understands intuitively that EVERYTHING human has bias.

It seems like a lot of conservatives and libertarians are jussssssst beginning to comprehend this and again and they want the conversation to be "BIAS BAD GET RID OF IT" because they are children who don't listen and want to throw a tantrum so we can't have an adult conversation with nuance.

We can't remove biases, believe me, human history is written with the countless stories of artists, scientists, kings, religious leaders... who all thought they could do shit like that. The point is you can't. Everything we create and do is biased, everything we create and make is political, these aren't absolutist statements meant to trivialize a critical nuanced conversation about bias or politics though. On the contrary I am calling attention to the vital nature of these topics as the actually HARD part of LLMs or social media. The programming, data manipulation, development of decentralized protocols etc... they are all nearly trivial details comparatively.

Computer science has to try to create imperfect solutions to the bias problem, but it would have a much easier time if it recognized how tiny this whole world of computer science still is compared to the immense amount of knowledge in the humanities produced by generations of artists and thinkers tackling the same problems.

We can't remove biases, but we still have to make better choices anyways.

[–] [email protected] 9 points 5 months ago (1 children)

Well put. I think tackling the bias will always be a challenge. It’s not that we shouldn’t, but how is the question.

I don’t know if any of the big public LLMs are trying to trim biases from their training data or are just trying to ad-hoc tackle it by injecting modifiers into the prompts.

That’s the biggest problem I have personally with LLMs is that they are untrustworthy and often give incorrect or blatantly false information.

Sometimes it can be frustrating when I run across the “I can’t do that because of ethics” on benign prompts that I felt like it shouldn’t have but I don’t think it’s been that big a deal.

When we talk about political conservatives being opposed to biased LLMs, it’s mostly because it won’t tell them that their harmful beliefs are correct

[–] [email protected] 6 points 5 months ago* (last edited 5 months ago)

When we talk about political conservatives being opposed to biased LLMs, it’s mostly because it won’t tell them that their harmful beliefs are correct

"What because I think Islam is inherently a violent religion now this chatbot is telling me I AM the one with violent and harmful beliefs??????" - some loser, maybe elon musk or maybe your uncle, who cares.

[–] [email protected] 11 points 5 months ago

So more or less the same as with human interactions.

[–] [email protected] 5 points 5 months ago (1 children)

What good will blame do? We need robust ai detection solutions.

[–] [email protected] 7 points 5 months ago (2 children)

Is that even possible? Part of modern generative systems is that they're trying to output text like a human would. As soon as someone invents a tool like that, it'll just be used to train the next generation, to make it even more indistinguishable, and turning the whole thing into a cat and mouse game.

[–] [email protected] 2 points 5 months ago* (last edited 5 months ago) (1 children)

AI » GAN » AI » GAN

Turns out it wasn't monkeys on typewriters that wrote perfect Shakespeare stories, it was trillions of transistors in a war of attrition.

[–] [email protected] 2 points 5 months ago* (last edited 5 months ago)

it was trillions of transistors in a war of attrition

By replacing the typewriter with a lever, you could probably achieve a similar result using monkeys.

[–] [email protected] -2 points 5 months ago (2 children)

It literally exists today and you sit here typing bullshit like 'is that even possible?'

Get every manner of blocked.

[–] [email protected] 4 points 5 months ago

It literally exists today and you sit here typing bullshit like ‘is that even possible?’

They're also infamously terrible, being half-correct and prone to detecting non-native English speakers as being AI. To the point where at least one institutition decided to not use a detector.

You'd likely be equally as accurate guessing at random. Not to mention that at the end of the day, they're just recognising quirks in the generated text. It is not difficult to mask those quirks either by having the prompt put out text in a different style, or for an update to change the generated text, breaking the detection as well.

There is no definite, sure-fire way to determine that text is AI-generated or not. For all you might know, as an AI language model, I could have cooked this comment up using a billion probability nodes loaded up into a typewriter, as it does not go against OpenAI's policies on generating text.

[–] [email protected] 1 points 5 months ago* (last edited 5 months ago) (1 children)

Quite the spicy one aren't you. I see where you get your username from.

But yes, they exist, and so does the ability to defeat them by training the detection data into a new undetected model. Cat and mouse game, as they say.

Robust today, defeated ~~tomorrow~~ today.

[–] [email protected] -1 points 5 months ago (1 children)

So, what you're saying is you don't really understand how data security works then.

Because it's never a 'one and done', it's ALWAYS a cat and mouse game, ALWAYS.

Which is why antivirus companies push definition updates.

And now we do the same with AI detectors, or they become irrelevant.

[–] [email protected] 1 points 5 months ago* (last edited 5 months ago) (1 children)

This is where I get to lol and say you don't understand AI.

When a kernel privesc vuln 0day is found and reported or caught in a dump, it gets fixed. Unless it was improperly fixed, that particular vulnerability can't be exploited again.

But when it comes to AI, a GAN's job is to take the 'vulnerability' that was 'fixed' and train on it to exploit it again.

And again.

And again.

And again.

https://en.m.wikipedia.org/wiki/Generative_adversarial_network

[–] [email protected] 0 points 5 months ago (1 children)

It's funny how people can just link to a wikipedia article about a ten year old thought experiment and think its some kind of mic drop moment. The current AI paradigm is starting to hit its singularity curve and hardly anything that old is anything more than a novelty and largely not applicable to current models, ESPECIALLY when it comes to modeling,

We aren't seeing this kind of iteritave adversity being used in actual real world attacks, and it is largely useless to train on a patched vulnerability.

But I'm sure you already knew that, maybe your testing me?