Rather than some deep philosophical question, I think output that doesn't make one immediately go "Erm? No, that's completely ridiculous." is probably a reasonable benchmark for Google to aim for, and for now they still seem a good deal away.

This is in fact why Google had not previously released generative AI consumer products despite years of research into them. No one, including Google, has figured out how to bolt a reliable “truth filter” in front of the generative engine.

Asking a generative AI for a picture of the U.S. founding fathers should not involve any generation at all. We have pictures of these people and a system dedicated to accuracy would just serve up those existing pictures.

It’s a different category of problem from adjusting generative output to mitigate bias in the training data.

It’s overlapping in a weird way here but the bottom line is that generative AI, as it exists today, is just the wrong tool to retrieve known facts like “what did the founding fathers look like.”

That is a problem, but not the problem here. The problem here is that the humans at Google are overriding the training data which would provide a reasonable result. Google is probably doing something similar to OpenAI. This is from the OpenAI leaked prompt:

Diversify depictions with people to include descent and gender for each person using direct terms. Adjust only human descriptions.

Your choices should be grounded in reality. For example, all of a given occupation should not be the same gender or race. Additionally, focus on creating diverse, inclusive, and exploratory scenes via the properties you choose during rewrites. Make choices that may be insightful or unique sometimes.

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.

To you and I, it is obviously stupid to apply that prompt to a request for an image of the U.S. founding fathers, because we already know what they looked like.

But generative AI systems only work one way. And they don’t know anything. They generate, which is not the same thing as knowing.

One could update the quoted prompt to include “except when requested to produce an image of the U.S. founding fathers.” But I hope you can appreciate the scaling problem with that approach to improvements.

To me, this feels much more like Google intentionally trying to bias what was probably an otherwise representative sample, and hilarity ensuing. But it's actually quite sad too. Because these companies are really butchering what could be amazing tools for visually exploring our history - "our" being literally any person alive today.

Instead, it just goes "I got this!" and starts fabricating names like a 4 year old.

https://en.wikipedia.org/wiki/Hiram_R._Revels

I think this is a strong argument for open models. There could be no one true way to build a base model that the whole world would agree with. In a way, safety concerns are a blessing because they will force a diversity of models rather than a giant monolith AI.

I would prefer if I can set my preferences so that I get an excellent experience. The model can default to the country or language group you're using it in, but my personal preferences and context should be catered to, if we want maximum utility.

The operator of the model should not wag their finger at me and say my preferences can cause harm to others and prevent me from exercising those preferences. If I want to see two black men kissing in an image, don't lecture me, you don't know me so judging me in that way is arrogant and paternalistic.

People are complaining about and laughing at poor defaults.

I’m not saying Gemini doesn’t suck (like most Google products do). I am saying that I know to be very explicit about what I want from any LLM.

I have two coworkers in a private Slack and we are always generating crazy memes with ChatGPT. If I specify a bald Black guy (me), a white woman and a Filipino guy, it gets it right.

I tried some of the same prompts that Gemini refused to render with ChatGPT or forced “diversity” on, ChatGPT did it correctly.

I’m a Black guy and I hate a lot of the DI&E initiatives that I first encountered at Amazon when I worked there.

I can say though that Amazon didn’t discriminate, corporate policy is equally toxic toward everyone.

https://onlinenursing.cn.edu/news/nursing-by-the-numbers

I think the downside of leaving people out is worse than having ratios be off, and a good mitigation tactic is making sure that results are presented as groups rather than trying to have every single image be perfectly aligned with some local demographic ratio. If a Mexican kid in California sees only white people in photos of professional jobs and people who look like their family only show up in pictures of domestic and construction workers, that reinforces negative stereotypes they’re unfortunately going to hear elsewhere throughout their life (example picked because I went to CA public schools and it was … noticeable … to see which of my classmates were steered towards 4H and auto shop). Having pictures of doctors include someone who looks like their aunt is going to benefit them, and it won’t hurt a white kid at all to have fractionally less reinforcement since they’re still going to see pictures of people like them everywhere, so if you type “nurse” into an image generator I’d want to see a bunch of images by default and have them more broadly ranged over age/race/gender/weight/attractiveness/etc. rather than trying to precisely match local demographics, especially since the UI for all of these things needs to allow for iterative tuning in any case.

In the US, right? Because if we take a world wide view of nurses it would be significantly different I image.

When we're talking about companies that operate on a global scale what do these ratios even mean?

> Every two years, NCSBN partners with The National Forum of State Nursing Workforce Centers to conduct the only national-level survey specifically focused on the U.S. nursing workforce. The National Nursing Workforce Survey generates information on the supply of nurses in the country, which is critical to workforce planning, and to ensure a safe and effective health care system.

Ask for a nurse? There's no reason every nurse generated should be white, or a woman. In fact, unless you take the requestors location into account there's every reason why the nurse should be white far less than a majority of the time. If you ask for a "nurse in [specific location]", sure, adjust accordingly.

I want more diversity, and I want them to take it into account and correct for biases, but not when 1) users are asking for something specific, or 2) where it distorts history, because neither of those two helps either the case for diversity, or opposition to systemic racism.

Maybe they should also include explanations of assumptions in the output. "Since you did not state X, an assumption of Y because of [insert stat] has been implied" would be useful for a lot more than character ethnicity.

I think you're giving these systems a lot more "reasoning" credit than they deserve. As far as I know they don't make assumptions they just apply a weighted series of probabilities and make output. They also can't explain why they chose the weights because they didn't, they were programmed with them.

If you asked for "future pope" then maybe, but misrepresenting the diversity that regressive organisations allow to exist today is little better than misrepresenting historical lack of diversity.

Yes, it's not obvious what the first result returned should be. Maybe a safe bet is to use the current ratio of sexes/races as the probability distribution just to counter bias in the training data. I don't think all but the most radical among us would get too mad about that.

What probability distribution? It can't be that hard to use the country/region of where the query is being made? Or the country/region about which the image is being asked for? All reasonable choices.

But, if the image generated isn't what you need (say the image of senators from the 1800's example). You should be able to direct it to what you need.

So just to be PC, it generates images of all kind of diverse people. Fine, but then you say, update it to be older white men. Then it should be able to do that. It's not racist to ask for that.

I would like for it to know the right answer right away, but I can imagine the political backlash for doing that, so I can see why they'd default to "diversity". But the refusal to correct images is what's over-the-top.

Yes. Because that fosters constructive debate about what society is like and where we want to take it, rather than pretend everything is sunshine and roses.

> Should we force the AI to return results in proportion to a particular race/ethnicity/gender's actual representation in the workplace?

It should default to reflect given anonymous knowledge about you (like which country you're from and what language you are browsing the website with) but allow you to set preferences to personalize.

On the other hand, it’s probably trivial at this point to generate a sample that endorses different well known biases as a default result, isn’t it? And stating it explicitly in the interface is probably not requiring that much complexity, doesn’t it?

I think the major benefit of current AI technologies is to showcase how horribly biased the source works are.