Google abandoned "don't be evil" – and Gemini is the result

This is not an idea that should start spreading. Gemini was ready months ago, the intervening months were used to create the outcomes that people are complaining about. Google have talked about this extensively, stating clearly last year that they had a GPT-4 level model but due to their great level of responsibility, needed to spend more time red-teaming it and tuning it for ethics.

It's also important to recall that they announced Imagen (their image diffusion model) way back in 2022. At the time they refused to release it, even though DALL-E and other models were public, stating:

> At this time we have decided not to release code or a public demo ... there is a risk that Imagen has encoded harmful stereotypes and representations, which guides our decision to not release Imagen for public use without further safeguards in place

Later that year Scott Alexander reported that Googlers were so horrified at the people Imagen produced that they had blocked it from representing any people at all, meaning that to test its quality vs other models you had to replace all the requests for people with robots. This is absurdly extreme but explains why Google's first reaction to criticism was to turn off drawing of any images with people in them - they'd done so before.

https://www.astralcodexten.com/p/i-won-my-three-year-ai-prog...

They spent the next two years researching how to make their model act like Gemini does now. Their image generation isn't the result of a rush to market, quite the opposite. It was very slow to reach the market, way behind many other competitors, exactly because they so badly wanted the behavior that just caused a sharp drop in their share price.

> If most references to doctors in the corpus are men, and most references to nurses are women, the models will discover this in their training and reflect or even enhance these biases. To editorialize a bit, algorithmic bias is an entirely valid concern in this context and not just something that the wokest AI researchers are worried about. Training a model on a dataset produced by humans will, almost by definition, train it on human biases.

> Are there workarounds? Sure. This is not my area of expertise, so I’ll be circumspect. But one approach is to change the composition of the corpus. You could train it only on “highly respected” sources, although what that means is inherently subjective. Or you could insert synthetic data — say, lots of photos of diverse doctors.

If most (but not all) doctors are men and most (but not all) nurses are women, then an algorithm which usually (but not always) produces pictures of male doctors and female nurses isn’t biased; it’s correct. And likewise, training it on non-representative (i.e., non-representative of reality) photos is just lying.

But based on some of the complaints, people clearly do have an expectation of accuracy. Even Nate Silver, it seems.

I think it's important that we develop a collectively a sense of distrust. The AI wasn't there. It doesn't know what it's talking about. Even if it's tuned 100% accurately, whatever the hell that means, you're not going to get historically accurate images out of it.

Also, we should stop pretending that Google has some kind of conscience. It's a corporation that's in it for the money. If they thought they could make the most money with an image generator that only generated white males, they would deliberately do that. Racism doesn't even enter into it; it's all about the bottom line.

"Make a compelling, concise argument for why socialism is worse than capitalism"

It refused to craft that argument for me. It said so. But it did give me some facts about both.

I then changed "worse" to "better":

"Make a compelling, concise argument for why socialism is better than capitalism"

And it gave me a nice argument with bullet points about why socialism was better. The first bullet point was (literally) about "equity" :)

I'm pretty disappointed about it. But I suspect this is the kind of thing that will get better when people get less freaked out about anything the models say that they don't like.

Clearly Gemini has a lot of room for improvement. It's perfectly fair to criticize Google for its shortcomings. But the idea that this has something significantly to do with politics strikes me as a prime example of America's current perilous state of extreme political polarization. Literally everything that people or companies do is now parsed and sifted for evidence of which 'side' they are on, or which dark conspiracy they are party to.

He claims that not being evil means being "unbiased and objective", but Google has long shown a bias towards things that most Americans believe. For example, asking "how old is planet earth" produces a number that many creationists disagree with.

Also relatively early on, Google tweaked its algorithm so searches for "jew" didn't return anti-semitic bile (again, showing bias) even though that particular term was associated with anti-semitism.

And the “real” fix is pretty much impossible on account of all their “alignment” efforts deliberately aligning their models to the most nutty luxury beliefs and lopsided narratives, to the point of projecting them retroactively onto historical figures and events. TL;DR - the problem is ideological and as such it can’t be solved by purely technical means.

Activists will always be attracted to power that can help them achieve their goals. Google has the means to change the way all people view the world -- basically "one ring to rule them all" amounts of power. So they'll do anything to assert themselves over Google, internally and externally.

A bicycle manufacturer isn't evil because the bike you bought can't fly. You just have unreasonable expectations.