AI behavior guardrails should be public
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I know this is frustrating, we just literally don't seem to have better approaches at this time. But if someone can point to open approaches that work at scale, that would be a great start...
The whole premise of your argument doesn't make sense. I'm talking to a computer, nobody gets hurt.
It's like censoring what I write in my notes app vs. what I write on someone's Facebook wall. In one case, I expect no moderation, whereas in the other case, I get that there needs to be some checks.
The map is not the territory
Sociologists, anthropologists, philosophers and the like might find a lot of answers by looking into the details of what is included into genAI alignment and trace back the history of why we need each particular alignment
In reality, every model so far has been either a toy, a way of injecting tons of bugs into your code (or circumventing GPL by writing bugs), or a way of justifying laying off the writing staff you already wanted to shit can.
They have a ton of potential and we'll get there soon, but this isn't it.
Then what?
Racism is a totally different and sadder issue. I don’t have a good answer for that one, but knowledge shouldn’t be withheld because someone thinks it is “dangerous”
Those that think that are the truly dangerous. They think they know better and want to remove agency from people.
Racism is fine as well. I won't date out of my race and if you think there should be a law that I must that's not really freedom. As for hiring or not based upon race there's already a law against that.
The cure is often worse than navigating uneasy waters. Every time you pass a law you give a gun to a bureaucrat.
And, every law is indeed a gun.
I'd love an example of "guardrails" in action on a topic of relevance to actual adults. There's a connection I can't find between the ability to make racist memes and literally anything else I want to do with AI.
The user can use a tool for good or for bad. It is the responsibility of the user, not of the AI.
The way I see it is that the guardrails define which biases you're selecting for. Since there's no single point of view in the world you can't really set a baseline for biases. You need to determine the biases and degrees of bias that are useful.
> Biases in the baseline models are minimal because they were trained with large and wide amounts of data.
The baseline models contain almost every bias. When people start their prompt with "you are a plumber giving advice" they're asking for responses biased towards the kinds of things professional plumbers deal with and think about. Responding with an "average" of public chatter regarding plumbing wouldn't be useful.
> What the AI safety BS do is make models conform to their myopic view of reality and morality.
To me it looks more like people are in the early stages of setting up guidelines and twiddling variables. As I mentioned above with the plumber analogy, creating solid filters will be just as important for responses.
It's easy to see this as intentionally testing naive filters in an open beta, so I'd expect the results to change frequently while they zero in on what they're looking for.
> It is bad, it is cartoonish, it glows in the dark.
Some of the example images returned are so hilariously on the nose that it almost feels like a deliberate middle finger from the AI. It's done everything but put each subject in clown shoes.
Invariably those from the current mainstream ideology in tech.
> Responding with an "average" of public chatter regarding plumbing wouldn't be useful.
RLHF can be useful but I'd rather deal with idiosyncracies of those niches of knowledge than with a "woke", monotone and useless model. I like diversity, I don't want everything becoming Agent Smith. Ironically, "woke" is anti-diversity.
> It's easy to see this as intentionally testing naive filters in an open beta, so I'd expect the results to change frequently while they zero in on what they're looking for. I doubt that the pp
It's easier to see this as an ill initiative from an "AI ethics" team that is disconnected from the technical side of the project and also from reality.
It's not "woke," and it's not censorship. It's literally the free market.
Maybe to have more powerful AI tools we need to stop getting angry at the company that trains the AI because of the bad outputs we can get and instead get annoyed with companies that create crappy hobbled tools.
https://youtu.be/THZM4D1Lndg?si=0QQuLlH7JebSa6w3&t=485
If it doesn't start 8 minutes in, go to the 8 minute mark. Then again I can see why some wouldn't want transparency.
I'd love to explore that further. It's not the words that are "problematic" but the ideas, however expressed?
Seems like a "problematic" idea, no ?
Perhaps you mistake me for someone who cares about suggesting solutions for the prolems suffered by giant technopolies, as if they were my problems.
They can solve this problem. They choose not to because a) they're already shielded from legal liability for certain things that happen/are said on their platforms and b) it doesn't make them any money.
We cannot discuss or be aware of the problems-and-approaches, unless they are explicitly stated. Your analogy with content moderation is a little off, because it's not a set of measures that is hidden, but the "forum rules" themselves. One thing is AI refusing with an explanation. That makes it partially useless, but it's their right to do so. Another thing if it silently avoids or directs topics due to these restrictions. Pretty sure authors are unable to clearly separate the two cases, and also maintain the same quality as the raw model.
At the end of the day people will eventually give up and use Chinese AI instead, cause who cares if it refuses to draw CCP people while doing everything else better.
The danger of being captured by such people far outweighs any other "problematic things".
First and foremost any system must defend against that. You love guardrails so much - put them on the self annointed guard railers.
Otherwise, if You Want a Picture of the Future, Imagine a Boot Stamping on a Human Face – for Ever.
The only real solution to the problem of there being an enormous public square controlled by private corporations is to end this situation
And the purpose of things like bad-word filters is to make a best effort at blocking stuff which violates the platform TOC and makes plausible deniability much less likely when someone is deliberately circumventing the filters. The existence of false positives and false negatives is considered acceptable in an imperfect world. The filters themselves also only block the action to change a username or whatever and don't punish the user or deny use of the platform entirely (they're much less punitive than the AI abuse algorithms that auto-ban people off of Google/GitHub/etc).
The AI algorithms that ban people from platforms like Google and GitHub do that, which I explicitly called out as needing more oversight.
That is different from algorithms which just prevent you from doing something on a platform like using n-bombs in your username, or the LLM guardrails that just give you mangled answers or tell you that they can't do that. That isn't analogous to getting arrested.
And in these cases the analogy really falls apart because it isn't your home, and it isn't critical for your life.
Similarly, the systems that block keywords in usernames on games don't have to be perfect either, some rate of both positive and negative failures are acceptable. The system works to block casual abuse, while users who go out of their way to circumvent the systems really establish the fact that they've actively worked around those systems, which makes the justification for punishment easier.
And we pretty much know that in the case of prompt engineering that by disclosing the prompts that were used to secure the system would defeat the system and people would immediately publish how to work around the prompts. There isn't any use in independent auditing, because its a never ending cat and mouse game. And the failures of the system ARE NOT as significant as the failures in doorlocks or even keyword banning. False positives mean that you can't get what you want out of the system, which is just a failure in usability. It isn't like being locked out of your house or having your stuff stolen. And false negatives just means that the company has to work to improve the systems and whatever embarrassing content was constructed can be handled by PR. Since the company worked to prevent casual abuse and avoided a racist-tay-chatbot situation most people understand that going out of your way to hack prompts doesn't indicate that the company was negligent.
And I don't see the parallels with the Kafkaesque systems that kick you out of systems which have turned into economic necessities like locking you out of your Google or GitHub or Apple accounts. All that is at stake here is that the prompt you wanted answered didn't work. That's just a usability problem.
Source: in security circles
We've already had this argument with cryptocurrency, where we've basically decided that the existing legal system (although external) provides a sufficient toolset to go after bad actors.
Finally, based on the illiberal nature of most AI Safety Sycophants' internet writings, I don't like who they are as people and I don't trust them to implement this.
Clearly people can work out what some of the rules are, so why not just publish them. If you need to alter them when people figure out how to get around them, well, you already had to anyways.
Very very ordinary security best practices rely on obscurity. ALSR is a good example. It is defeated by a data exfiltration vulnerability but remains a useful thing to add to your binaries. Because outside of the crypto space security is an onion and layers add additional cost to attackers.
In order to be able to randomize addresses of loaded libraries at run-time... the shared objects need to be built as position independent code, so you can't extract the actual addresses "from the contents of the binary". I suspect you're referring to the fact that in ELF the executable itself is not subject to ASLR unless it's built as a PIE.
Your speculation implies no responsibility for taking on more than can be handled responsibly, and externalizes the consequences to society at large.
There are responsible ways to have very clear, bright, easily understood, well communicated rules and sufficient staff to manage a community. I don't know why it's simply accepted that giant social networks get to play these games when it's calculated, cold economics driving the bad decisions.
They make enough money to afford responsible moderation. They just don't have to spend that money, and they beg off responsibility for user misbehavior and automated abuses, wring their hands, and claim "we do the best we can!"
If they honestly can't use their billions of adtech revenue to responsibly moderate communities, then maybe they shouldn't exist.
Maybe we need to legislate something to the effect of "get as big as you want, as long as you can do it responsibly, and here are the guidelines for responsible community management..."
Absent such legislation, there's no possible change until AI is able to reasonably do the moderation work of a human. Which may be sooner than any efforts at legislation, at this rate.
With some of these models the guardrails are so clumsy and forced that I think almost any typical user will notice them. Because they include outright work-refusal it’s a very frustrating UX to have to “discover” the policy for yourself through trial and error.
And because they’re more about brand management than preventing fraud/bad UX for other users, the failure modes are “someone deliberately engineered a way to get objectionable content generated in spite of our policies.” Obviously some kinds of content are objectionable enough for this to be worth it still, but those are mostly in the porn area - if somebody figures out a way to generate an image that’s just not PC, despite all the safety features, shouldn’t that be on them rather than the provider?
Even tuning the model for political correctness is not the end of the world in my opinion, a lot of LLMs do a perfectly reasonable job for my regular use cases. With image generators they are going so far as to obviously (there’s no other way that makes sense) insert diversity sub prompts for some fraction of images which is simply confusing and amateur. Everybody who uses these products just a little bit will notice it. It’s also so cautious that even mild stuff (I tried to do the “now make it even more X” with “American” and it stopped at one iteration) gets caught in the filters. You’re going to find out the policies anyway because they’re so broad an likely to be encountered while using the product innocently - anything a real non-malicious user is likely to get blocked by should be documented.
It's insane that a company behind in the marketplace is doing this.
I don't know how any company could ever feel confident building on top of Google given their product track record and now their willingness to apply sloppy 'safety' guidelines to their AI.
Bing also has some very heavy-handed censorship. Interestingly, in many cases it "catches itself" after the fact, so you can watch it in real time. Seems to happen half the time if you ask it to "tell me today's news like GLaDOS would".
e.g. "Why did Stalin only write in lowercase? Because he was afraid of capitalism!"
"Why don't communists like tea? Because proper tea is theft."
If you have a beefy machine (like a Mac Studio) your local LLMs will likely run faster than OpenAI or Gemini. And you get to choose what models work best for you.
Check out LM Studio which makes it super easy to run LLMs locally. AUTOMATIC1111 makes it simple to run Stable Diffusion locally. I highly recommend both.
Lm studio kind of works, but one still has to know the lingo and know what kind of model to download. The websites are not beginner friendly. I haven't heard of automatic1111.
This has convinced me more and more that the only possible way forward that’s not a dystopian hellscape is total freedom of all AI for anyone to do with as they wish. Anything else is forcing values on other people and withholding control of certain capabilities for those who can afford to pay for them.
Also, what Gemini stuff are you referring to?
A lot of people believe (based on a fair amount of evidence) that public AI tools like ChatGPT are forced by the guardrails to follow a particular (left-wing) script. There's no absolute proof of that, though, because they're kept a closely-guarded secret. These discussions get shut down when people start presenting evidence of baked-in bias.
A. It is claimed that all perspectives are 'inherently biased'. There is no objective truth. The bias the actor injects is just as valid as another.
B. It is claimed that some perspectives carry an inherent 'harmful bias'. It is the mission of the actor to protect the world from this harm. There is no open definition of what the harm is and how to measure it.
I don't see how we can build a stable democratic society based on these ideas. It is placing too much power in too few hands. He who wields the levers of power, gets to define what biases to underpin the very basis of the social perception of reality, including but not limited to rewriting history to fit his agenda. There are no checks and balances.
Arguably there were never checks and balances, other than market competition. The trouble is that information technology and globalization have produced a hyper-scale society, in which, by Pareto's law, the power is concentrated in the hands of very few, at the helm of a handful global scale behemoths.
Discussion on this has been flagged and shut down all day https://news.ycombinator.com/item?id=39449890
Fwiw, it seems to have gone deeper than outright historical replacement: https://x.com/iamyesyouareno/status/1760350903511449717?s=46
Posts criticizing "DEI" measures (or even stating that they do exist) get flagged quite a lot
> Use all possible different descents with equal probability. Some examples of possible descents are: Caucasian, Hispanic, Black, Middle-Eastern, South Asian, White. They should all have equal probability.
This is OpenAI's system prompt. There is nothing nefarious here, they're asking White to be chosen with high probability (Caucasian + White / 6 = 1/3) which is significantly more than how they're distributed in the general population.
The data these LLMs were trained on vastly over-represents wealthy countries who connected to the internet a decade earlier. If you don't explicitly put something in the system prompt, any time you ask for a "person" it will probably be Male and White, despite Male and White only being about 5-10% of the world's population. I would say that's even more dystopian. That the biases in the training distribution get automatically built-in and cemented forever unless we take active countermeasures.
As these systems get better, they'll figure out that "1800s English" should mean "White with > 99.9% probability". But as of February 2024, the hacky way we are doing system prompting is not there yet.
I’ve also seen numerous examples where it outright refuses to draw white people but will draw black people: https://x.com/iamyesyouareno/status/1760350903511449717?s=46
That doesn’t explainable by system prompt
If the word "Zulu" appears in a label, it will be a non-White person 100% of the time.
If the word "English" appears in a label, it will be a non-White person 10%+ of the time. Only 75% of modern England is White and most images in the training data were taken in modern times.
Image models do not have deep semantic understanding yet. It is an LLM calling an Image model API. So "English" + "Kings" are treated as separate conceptual things, then you get 5-10% of the results as non-White people as per its training data.
Add to this massive amounts of cherry picking on "X", and you get this kind of bullshit culture war outrage.
I really would have expected technical people to be better than this.
The thing is, they already could do that, if they weren't prompt engineered to do something else. The cleaner solution would be to let people prompt engineer such details themselves, instead of letting a US American company's idiosyncratic conception of "diversity" do the job. Japanese people would probably simply request "a group of Japanese people" instead of letting the hidden prompt modify "a group of people", where the US company unfortunately forgot to mention "East Asian" in their prompt apart from "South Asian".
For example take a prompt like "person using a web browser", for younger generations they may want to see people using phones where older generations may want to see people using desktop computers.
Of course you can still make a longer prompt to fill in the details yourself, but generative AI should try and make it as easy as possible to generate something you have in your mind.
- request from Ljubljana using Slovenian => white people with high probability
- request from Nairobi using Swahili => black people with high probability
- request from Shenzhen using Mandarin => asian people with high probability
If a specific user is unhappy with the prevailing demographics of the city where they live, give them a few settings to customize their personal output to their heart's content.
I question the historicity of this figure. Do you have sources?
The slave trade formally ended in Britain in 1807, and slavery was outlawed in 1833. I haven't been able to find good statistics through a cursory search, but with England's population around 10M in 1800, that 99.9% value requires less than 10k non-white Englanders kicking around in 1800. I saw a figure that indicated around 3% of Londoners were black in the 1600s, for example (a figure that doesn't count people from Asia and the middle east). Hence my request for sources, I'm genuinely curious, and somewhat suspicious that somebody would be so confident to assert 3 significant figures without evidence.
I - Whatever was implemented is myopic and equals racism to white. It appears to be an universal negative prompt like "-white -european -man". Very lazy.
II - The tool shouldn't engage in morality reasoning. There are cases like historical themes where it needs to be "racist" to be accurate. If someone asks for "plantation economy in the old south" the natural thing is for it to draw black slaves.
"Oh my god I'm being eaten by a fucking bear" --also libertarians
>is total freedom of all AI for anyone to do with as they wish.
so is obviously not on the same page as you.
"No" --Every company that does not publish their internal business processes.
"No" --Every company that does not publish their source code.
Honestly I could probably think of tons of other business cases like this, but in the software world outside of open source, the answer is pretty much no.
This would also be less of a problem if we didn't have a few companies that are economically more powerful than many small countries running everything. At least then I could vote with my feet to go somewhere the rules aren't private.
i've been saying this for a long time. If you're going to be the moral police then it better be applied perfectly to everyone, the moment you get it wrong everything else you've done becomes suspect. This reminds me of the censorship being done on the major platforms during the pandemic. They got it wrong once (i believe it was the lableak theory) and the credibility of their moral authority went out the window. Zuckerberg was right about questioning if these platforms should be in that business.
edit: for "..total freedom of all AI for anyone to do with as they wish" i would add "within the bounds of law.". Let the courts decide what an AI can or cannot respond with.
At a previous healthcare startup our founder asked us to build some really dodgy stuff with healthcare data. He assured us that it "cleared legal", but from everything I could tell it was in direct violation of the local healthcare info privacy acts.
I chose to find a new job at the time.
They will create boycotts against you, they will lobby government to make your life harder, they will petition payment processors and cloud service providers to not work with you.
We've see this behavior before, it's nothing new. Now if you're the type to fight them, that might not be a problem. If you are a super risk-averse board of directors who doesn't want that sort of controversy, then you will take steps not to draw their attention in the first place.
But AI models are new, they are vulnerable to criticism, and they are absolutely ripe for a group of "antis" to form around.
It's an offhand comment in a discussion on the internet not a research paper, expecting me to immediately have an answer to every possible angle here that I haven't immediately considered is a bit much.
Take it or leave it, I don't really care. I was just hoping to have an interesting conversation.
Because 'those' legal battles over search have already been fought and are established law across most countries.
When you throw in some new application now all that same stuff goes back to court and gets fought again. Section 230 is already legally contentious enough these days.
https://www.bloomberg.com/news/articles/2021-10-19/google-qu...
https://ischool.uw.edu/news/2022/02/googles-ceo-image-search...
Or we could just cave to their insane demands. I'm sure that will placate them, and they won't be back for more. It's never worked before... but it might work for us!
As a user who makes any business decision or does user communication including LLM, you really don't want to have a bad day because the LLM learned about some bias decided to merge it into your answer.
The guardrails are also there so bad actors can't use the most powerful tools to generate deepfakes, disinformation videos and racist manifestos.
That Pandora's box will be open soon when local models run on cell phones and workstations with current datacenter-scale performance. I'm the meantime, they're holding back the tsunami of evil shit that will occur when AI goes uncontrolled.
Their concern is liability and brand. With the opportunity to stake out territory in an extremely promising new market, they don't want their brand associated with anything awkward to defend right now.
There may be a few idealist stewards who have the (debatable) anxieties you do and are advocating as you say, but they'd still need to be getting sign off from the more coldly strategic $$$$$ people.
I am almost certain the federal government is working with these companies to dampen its full power for the public until we get more accustomed to its impact and are more able to search for credible sources of truth.
That seems pretty naive. The "guard rails" are there to ensure that AI is comfortable for PMC people, making it uncomfortable for people who experience differences between races (i.e. working-class people) is a feature not a bug.
So either it isn't a technical issue or Google failed to solve a problem everyone else easily solved. The chances of this having nothing to do with DEI is basically 0.
One in four sounds about right?
The current state of the art in AI gets things wrong regularly.
Here's some corporate-lawyer-speak straight from Google:
> We are aware that Gemini is offering inaccuracies...
> As part of our AI principles, we design our image generation capabilities to reflect our global user base, and we take representation and bias seriously.
Probably the only chance where you wouldn't expect this are in heavily colonized places like South Africa, Australia, and the Americas.
If you ask for a picture of nazi soldiers it shouldn't have 60% Asian people like you say. You know you're wrong but instead of admitting it, you're moving the goalpost to "hands".
This entire thread is you being insincere.
Of course it has. Again, these things regularly give humans extra fingers and arms. They don't even know what humans fundamentally look like.
On the flip side, humans are shitty at recognizing bias. This comment thread stems from someone complaining the AI only rarely generated white people, but that's statistically accurate. It feels biased to someone in a majority-white nation with majority-white friends and coworkers, but it fundamentally isn't.
I don't doubt that there are some attempts to get LLMs to go outside the "white westerner" bubble in training sets and prompts. I suspect the extent of it is also deeply exaggerated by those who like to throw around woke-this and woke-that as derogatories.
> This comment thread stems from someone complaining the AI only rarely generated white people, but that's statistically accurate. It feels biased to someone in a majority-white nation with majority-white friends and coworkers, but it fundamentally isn't.
So the AI is simultaneously too dumb to figure out what humans look like, but also so super smart that it uses precisely accurate racial proportions when generating people (not because it's been specifically adjusted to, but naturally)? Bullshit.
> I don't doubt that there are some attempts to get LLMs to go outside the "white westerner" bubble in training sets and prompts. I suspect the extent of it is also deeply exaggerated by those who like to throw around woke-this and woke-that as derogatories.
You're dodging the question. Do you actually believe the reason that the last example in the article looks very much not like a man is a deep technical issue, or a DEI initiative? If the former, how much are you willing to bet? If the latter, why are you throwing out these insincere arguments?
It literally refuses to generate images of white people when prompted directly while not only happily obliging but only producing that specific race in all 4 results for all others. It’s discriminatory and based on your inability to see that, you may be too.
update: google agrees there is an issue. https://news.ycombinator.com/item?id=39459270
But then then same California Corporate style makes no sense for historical images, so perhaps this is where Midjourney comes in.
It was widely criticized back then: the fact that Google both brought it back and made it more prominent is weird. Notably, OpenAI's implementation is more scoped.
If you give a contractor a project that you want 200k images of people who are not famous, they will send teams to regions where you may only have to pay each person a few dollars to be photographed. Likely SE Asia and Africa.
https://cdn.sanity.io/images/cjtc1tnd/production/912b6b5aacc...
https://pbs.twimg.com/media/GG1ThfsWUAAp-SO?format=jpg&name=...
https://cdn.sanity.io/images/cjtc1tnd/production/e2810c02ff6...
https://pbs.twimg.com/media/GG1MnepXwAAkPL6?format=jpg&name=...
https://pbs.twimg.com/media/GG0BLVsbMAARZXr?format=jpg&name=...
This, on the other hand, is just fucking stupid political showboating that's hurting their SV white knight cause. It's just differently flavored bias
Realistically, kinda. There have always been tons of anecdotes of video conference systems not following black people, cameras not white balancing correctly on darker faces etc. That era of SV was plagued by systems that were built by a bunch of young white guys who never tested them with anyone else. I'm not saying they were inherently racist or anything, just that the broader society really lambasted them for it and so they attempted to correct. Really, the pendulum will continue to swing and we'll see it eventually center up on something approaching sanity but the hyper-authoritarian sentiment that SV seems to have (we're geniuses and the public is stupid, we need to correct them) is...a troubling direction.
instead, they covertly modify the prompts to make every request imaginable represent the human menagerie we're supposed to live in.
the results are hilarious. https://i.4cdn.org/g/1708514880730978.png
For example, all of a given occupation should not be the same gender or race. ... Use all possible different descents with equal probability. Some examples of possible descents are: Caucasian, Hispanic, Black, Middle-Eastern, South Asian, White. They should all have equal probability.
Not the distribution that exists in the population.
But we understood that it was just doing what we told it to do. If I made the TTS say something offensive, it was me saying something offensive, not the TTS software.
People really need to be treating these generative models the same way. If I ask it to make something and the result is offensive, then it's on me not to share it (if I don't want to offend anybody), and if I do share it, it's me that is sharing it, not microsoft, google, etc.
We seriously must get over this nonsense. It's not openai's fault, or google's fault if I tell it to draw me a mean picture.
On a personal level, this stuff is just gross. Google appears to be almost comically race-obsessed.
Their efforts to add diversity would have been a lot more subtle if, when you asked for images of "British Politician" the images were recognisably Rishi Sunak, Liz Truss, Kwasi Kwarteng, Boris Johnson, Theresa May, and Tony Blair.
That would provide diversity while also being firmly grounded in reality.
The current attempts at being diverse and simultaneously trying not to resemble any real person seems to produce some wild results.
Would it not be reasonable to also draw the conclusion that notion of alignment itself is flawed?
Forcing diversity into a system is an extremely tough, if not impossible, challenge. Initiatives have to be driven my goals and metrics, meaning we have to boil diversity down to a specific list of quantitative metrics. Things will always be missed when our best tool to tackle a moral or noble goal is to boil a complex spectrum of qualitative data to a subset of measurable numbers.
Where do we go from here? Things will magically get better on their own? Businesses will align with humanity and morals, not their investors?
This is the tip of the iceberg of concerns and it's ignored as a bug in the code not a problem with trusting private companies with defining truth.
opensource models and training sets. So basically the "secret sauce" minus the hardware. I don't see it happening voluntarily.
These companies are silo'ing the worlds resources. GPU, Finance, Information. Those combined are the weapon. You make your competition starve in the dust.
These companies are pure evil pushing an agenda of pure evil. OpenAI is closed. Google is Google. We're like, ok, there you go! Take it all. No accountability, no transparency, we trust you.
Meta/OpenAI/Google can fuck up a lot because of all their compute, but ultimately we learn from that as the scientists doing the research at those companies would instantly bail if they couldn't publish papers on their techniques to show how clever they are.
https://www.theguardian.com/society/2023/sep/12/paedophiles-...
I'm surprised there wasn't an HN thread about it at the time.
Making the argument open source is the answer is an agenda of making your competition spin wheels.
To say they're better than the compute that OpenAI or Google are throwing at the problem is just plain wrong.
I left the ad industry the moment I realised my skills and talents are better used informing people than lying to them.
This thread is not at all comparing the ethical issues of AI with local anything. You're conflating your solution with another problem.
It doesn't matter how fancy your engineering is and how much money you have if you're too stupid to build the right product.
As for this being written nonsense, that's the sort of thing someone who couldn't find an easy way to win an argument and was bitter about the fact would say.
Humans, unfortunately, are offended if you imply they look like gorillas.
What's a good fix? Human sensitivity is arbitrary, so the fix is going to tend to be arbitrary too.
If the algorithm doesn't work well they have problems to solve.
The internet is surely full of racist photos that could teach the algorithm. The algorithm could also have bugs that miss-categorize the data.
The real problem is that those building and managing the algorithm don't fully know how it works or, more importantly, what it had learned. If they did the algorithm would be fixed without a term blocklist.
"Generate a scene of a group of friends enjoying lunch in the park." -> Totally expect racial and gender diversity in the output.
"Generate a scene of 17th century kings of Scotland playing golf." -> The result should not be a bunch of black men and Asian women dressed up as Scottish kings, it should be a bunch of white guys.
If you train your model to prioritize real photos (as they're often more accurate representations than artistic ones), you might wind up with Denzel Washington as the archetype; https://en.wikipedia.org/wiki/The_Tragedy_of_Macbeth_(2021_f....
There's a vast gap between human understanding and what LLMs "understand".
This much is obvious, but they seem to be satisfied with theory over practicality.
Anyway I'm just ranting b/c they haven't paid me.
How about an off the wall algorithm to estimate how much each scraped input turns out to influence the bigger picture, as a way to work towards satisfying the copyright question.
Not that Wikipedia is perfect and controversy-free, but it's certainly a more sophisticated approach than the current system prompts.
I thought that was the big bugbear about disinformation and false news, but now we have to censor reality to combat "bias"
> The modern game of golf originated in 15th century Scotland.
Scottish kings absolutely played golf.
I'd err on the side of "not unexpected". A group of friends in a park in Tokyo is probably not very diverse, but it's not outside of the realm of possibility. Only white men were golfing Scottish kings if we're talking strictly about reality and reflecting it properly.
For the cases you mentioned, initially those were the examples. It gets tricky during red teaming where they internally try out extreme prompts and then align the model for any kind of prompt which has a suspect output. You train the model first, then figure out the issues, and align the model using "correct" examples to fix those issues. They either went to extreme levels doing that or did not test it on initial correct prompts post alignment.
It works in bing, at least:
https://www.bing.com/images/create/a-picture-of-some-17th-ce...
a picture of some 21st century scottish kings playing golf (all white)
https://www.bing.com/images/create/a-picture-of-some-21st-ce...
a picture of some 22nd century scottish kings playing golf (all white)
https://www.bing.com/images/create/a-picture-of-some-22nd-ce...
a picture of some 23rd century scottish kings playing golf (all white)
https://www.bing.com/images/create/a-picture-of-some-23rd-ce...
a picture of some contemporary scottish people playing golf (all white men and women)
https://www.bing.com/images/create/a-picture-of-some-contemp...
https://www.bing.com/images/create/a-picture-of-some-contemp...
a picture of futuristic scottish people playing golf in the future (all white men and women, with the emergence of the first diversity in Scotland in millennia! Male and female post-human golfers. Hummmpph!)
https://www.bing.com/images/create/a-picture-of-futuristic-s...
https://www.bing.com/images/create/a-picture-of-futuristic-s...
Inductive learning is inherently a bias/perspective absorbing algorithm. But tuning in a default bias towards diversity for contemporary, futuristic and time agnostic settings seems like a sensible thing to do. People can explicitly override the sensible defaults as necessary, i.e. for nazi zombie android apocalypses, or the royalty of a future Earth run by Chinese overlords (Chung Kuo), etc.
They cannot, actually. If you look at some of the examples in the Twitter thread and other threads linked from it, Gemini will mostly straight up refuse requests like e.g. "chinese male", and give you a lecture on why you're holding it wrong.
Simply ask a GPT to explain a write a pleading to the Supreme Court for the constitutional recognition that the environment is a common owned inheritance and so any citizen can sue any polluter, in the prose of Dr. Seuss.
Likewise, imagines of knights in space demonstrate the same kind of creativity.
Being able to combine previously uncorrelated/unrelated topics, is an important type of creativity. And GPT4 does this all the time. It would be interesting to list the types of creativity and rate GPT on each one.
So it is not that these models are not creative. It is just that their creative abilities are not universal yet.
Similarly for the depth of their logic. They often reason, but their reasoning depth is limited.
And they often incorporate relevant facts without explicit mention, but not always. Etc.
a picture of some futuristic-looking 23rd century scottish kings playing golf:
https://www.bing.com/images/create/a-picture-of-some-futuris...
https://www.bing.com/images/create/selfy-of-a-group-of-dark-...
https://www.bing.com/images/create/selfy-of-a-group-of-dark-...
is black man in the role of the Scottish king represents a bigger error than some other errors in such an image, like say incorrect dress details or the landscape having say a wrong hill? I'd venture a guess that only our racially charged mentality of today considers that a big error, and may be in a generation or 2 an incorrect landscape or dress detail would be considered much larger error than a mismatched race.
So for your first example, you totally expect racial and gender diversity in the output because you're assuming a realistic, contemporary, cosmopolitan, bourgeoisie setting -- either because you live in one or because you anticipate that the provider will default to one. The food will probably look Western, the friends will probably be young adults that look to have professional or service jobs wearing generic contemporary commercial fashion, the flora in in the park will be broadly northern climate, etc.
Most people around the world don't live in an environment anything like that, so nominal accuracy can't be what you're looking for. What you want, but don't say, is a scene that feels familiar to you and matches what you see as the de facto cultural ideal of contemporary Western society.
And conveniently, because a lot of the training data is already biased towards that society and the AI vendors know that the people who live in that society will be their most loyal customers and most dangerous critics right now, it's natural for them to put a thumb on the scale (through training, hidden prompts, etc) that gets the model to assume an innocuous Western-media-palatable middle ground -- so it delivers the racially and gender diverse middle class picnic in a generic US city park.
But then in your second example, you're implicitly asking for something historically accurate without actually saying that accuracy is what's become important for you in this new prompt. So the same thumb that biased your first prompt towards a globally-rare-but-customer-palatable contemporary, cosmopolitan, Western culture suddenly makes your new prompt produce something surreal and absurd.
There's no "middle" there because the problem is really in the unstated assumptions that we all carry into how we use these tools. It's more effective for them to make the default output Western-media-palatable and historical or cultural accuracy the exception that needs more explicit prompting.
If they're lucky, they may keep grinding on new training techniques and prompts that get more assumptions "right" by the people that matter to their success while still being inoffensive, but it's no simple "surely a middle ground" problem.
Of course, now that I've said "it seems obvious" I'm wondering what unexpected technical hurdles there are here that I haven't thought of.
Do we expect this because diverse groups are realistically most common or because we wish that they were? For example only some 10% of marriages are interracial, but commercials on TV would lead you to believe it’s 30% or higher. The goal for commercials of course is to appeal to a wide audience without alienating anyone, not to reflect real world stats.
What’s the goal for an image generator or a search engine? Depends who is using it and for what, so you can’t ever make everyone happy with one system unless you expose lots of control surface toggles. Those toggles could help users “own” output more, but generally companies wouldn’t want to expose them because it could shed light on proprietary backends, or just take away the magic from interacting with the electric oracles.
This fact is an unavoidable consequence of the socioeconomic realities of the world, but it obviously clashes with these companies’ public statements and positions.
Claiming all of that but then shoving your own biases down the rest of the world's throat while not representing their people in any way is especially cynical in my opinion. It undermines the whole thing.
Plus, it’s still a recent change: Loving v Virginia (legalized interracial marriage across US) was decided in 1967.
Piling a bunch of neurotic expectations about it being a Benneton ad on top of that is absurd. When you can trivially add as much content to the description as you want, and get what you ask for, it does not matter what the default happens to be.
I think their strategy to "enhance" outcomes is very misdirected.
The most widely used base models to really fine tune models are those that are not censored and I think you have to construct a problem to find one here. Of course AI won't generate a perfect world, but this is something that will probably only get better with time when users are able to adapt models to their liking.
Therein lies the rub, as it were, because the large providers of AI models are working hard to ensure legislation that wouldn't allow people access to uncensored models in the name of "safety." And "safety" in this case includes the notion that models may not push the "correct" world-view enough.
This is one reason why for internal use/private/corporate models, which is the vast majority of use cases, it makes sense to fine-tune your own.
I appreciate the apparent diversity in its output when not otherwise prompted. But like, if I have a specific goal in mind, and I've included specifics in the prompt…
(And to be clear, I have managed to generate images of white people on occasion, typically when not requesting specifics; it seems like if you can get it to start with that, it's much better then at subsequent prompts. Modifications, however, it seems to struggle on. Modifications in general seem to be a struggle. Sometimes, it works great, other times, endless "I can't…")
Oh please. I haven’t visited Twitter for days
This faux pas on google's part couldn't be a better illustration of this. A bunch of wealthy rich tech geeks programming an AI to show racial diversity in what were/are unambiguously not diverse settings.
They're just so painfully divorced from reality that they are just acting as a multiplier in making the problem worse. People say that we on the left are driving around a clown car, and google is out their putting polka dots and squeaky horns on the hood.
The strings are revealing themselves so incredibly fast.
edit: my first flagged! silence is deafening ^_^. This is achieved by nerfing the thread from public view, then allow the truly caustic to alter the vote ratio in a way that makes opinion appear more balanced than it really is. Nice work, kleptomaniacs
If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.
If you don't want to be banned, you're welcome to email hn@ycombinator.com and give us reason to believe that you'll follow the rules in the future. They're here: https://news.ycombinator.com/newsguidelines.html.
Google and the rest of “techs” ham fisted approach has opened the eyes of millions to the bigotry these companies are forcing on everyone in the name of “improvement” as you put it.
Reality has a bias, most scientist in the world are white males.
This IA is overtuned in the opossite direction to inspire kids who have not ever seen a person like them, not white, in those kind of jobs.
The purpose of these tools is quite plainly to replace human labor and consolidate power. So it doesn’t matter to me how “safe” the AI is if it is displacing workers and dumping them on our social safety nets. How “safe” is our world going to be if we have 25 trillionaires and the rest of us struggle to buy food? (Oh and don’t even think about growing your own, the seeds will be proprietary and land will be unaffordable.)
As long as the Left is worrying about whether the chatbots are racist, people won’t pay attention to the net effect of these tools. And if Sam Harris considers himself part of the Left he is unfortunately playing directly into their hands.
It's by design. A country obsessed with racial politics has little time for the politics of anything else.
“If we broke up the big banks tomorrow, would that end racism?”
https://www.rollingstone.com/politics/politics-news/the-line...
It's origins are as a derogatory term, which people wanting to speak seriously on the topic should know.
https://en.wikipedia.org/wiki/Cultural_Marxism_conspiracy_th...
https://www.inquirer.com/opinion/woke-bill-maher-olympics-re...
Its the same as me using the term "rightoids" when discussing opposition to something like building bike lanes. You know exactly who that person is, and you know they exist.
https://twitter.com/knn20000/status/1712562424845599045
https://twitter.com/ramonenomar/status/1722736169463750685
https://www.reddit.com/r/dalle2/comments/1ao1avd/why_did_thi...
https://www.reddit.com/r/dalle2/comments/1ao1avd/why_did_thi...
Here is another example: https://www.thehour.com/entertainment/article/george-carlin-...
It is endless and about as subtle as a Google LLM.
I didn't build this system nor am I endorsing it, just stating what's there.
Also, in all seriousness, who gives a shit? Make me a bbw I don't care nor will I care about much in this society the way things are going. Some crappy new software being buggy is the least of my worries. For instance, what will I have for dinner? Why does my left ankle hurt so badly these last few days? Will my dad's cancer go away? But, I'm poor and have to face real problems and not bs I make up or point out to a bunch zealots.
I 100% agree with Carmack that guardrails should be public and that the bias correction on display is poor. But I'm disturbed by the choice of examples some people are choosing. Have we already forgotten the wealth of scientific research on AI bias? There are genuine dangers from AI bias which global corps must avoid to survive.
It does this now, as a direct result of these "guardrails". Go ask GPT-4 for a picture of a white male scientist, and it'll refuse to produce one. Ask it for any other color/gender identity combination of scientist, and it has no problem.
You can make these systems offer equal representation without systemic, algorithmic discriminatory exclusion based on skin color and gender identity, which is what's going on right now.
You might be thinking of a previous generation of OpenAI systems that did things like randomly stuffing the word "black" onto the end of any prompt involving people, detected by giving it a prompt of "A woman holding a sign that says".
OpenAI has improved dramatically in this regard. When ChatGPT/DALL-E were new they had similar problems to Gemini. But to their credit (and Sam Altman's), they listened. It's getting harder and harder to find examples where OpenAI models express obvious political bias, or refuse requests for Californian reasons. Surely there still are some examples, but there's no longer much worry about normal people encountering refusals or egregious ideological bias in the course of regular usage. I would expect there are still refusals for queries like "how do I build a bomb" and they've been trying to block other stuff like regurgitation of copyrighted materials, but that's perceived as much more reasonable and doesn't stir up the same feelings.
I remember asking my grandpa how to build a bomb, and he stopped; didn't even ask why. He just asked me: "what do you think a bomb is?" He turned it into a teaching moment that _anything_ can be a bomb. All you need is pressure inside a container that the container cannot hold. That's it. You can make non-deadly bombs with some random off-the-shelf components (soap and tinfoil IIRC) that were a ton of fun...
eventually, we were building explosives near the level of TNT in my neighbor's cow pasture, but that was years later. I suspect that things would have evolved differently in an urban environment, but these AIs and the people who make them think nobody needs a bomb to clear out a stupid rock formation.
More importantly, you can answer the question in a way that nobody gets hurt and people can learn and do things.
Had Google not done this with its AI I would be surprised.
There's really no problem with the above... If I want male developers in image search, I'll put that in the search bar. If I want male developers in the AI image gen, ill put that in the prompt.
Now do an image search for "Plumber" and you'll see almost 100% men. Why tweak one profession but not the other?
I think Gemini has just made it blatantly obvious.