281–290 of 1001 posts
It seems that basically anything Google does is not good enough for anyone these days. Damned if they do, damned if they don't.
There's an amusing irony here: real diversity would entail many competing ML companies from non-Western countries —each of which would bring their own cultural norms, alien and uncomfortable to Westerners. There's no cultural diversity in Silicon Valley being a global hegemon: exporting a narrow sliver of the world's viewpoints to the whole planet, imposing them with the paternalism drawn from our own sense of superi…
There's definitely human intervention in the model. Gemini is not true AI, it has too much human intervention in its results.
You're speaking as if LLMs are some naturally occurring phenomena that people are Google have tampered with. There's obviously always human intervention as AI systems are built by humans.
There's definitely human intervention in the model. Gemini is not true AI, it has too much human intervention in its results.
You're speaking as if LLMs are some naturally occurring phenomena that people are Google have tampered with. There's obviously always human intervention as AI systems are built by humans.
The model is built by machine from a massive set of data. Humans at Google may not like the output of a particular model due to their particular sensibilities, so they try to "tune it" and "filter both input/output" to limit of what others can do with the model to Google's sensibilities.
Google stated as much in their announcement recently. Their whole announcement was filled with words like "responsibility", "safety", etc., alluding to a lot of censorship going on.
That is certainly embarassing. But in the same time, I think it is a debate worth having. What corrections to the training dataset biases are acceptable. Is it acceptable to correct the answer to the query "Eminent scientist" from 95% men, 5% woment to 50%/50% or to the current ratio of men/women in science ? Should we correct the ratio of black to white people in answering a generic question to average across the gl…
That may also be a way to generate attention/visibility for Gemini considering that they are not seen as the leader in AI anymore? Attention is all you need.
We humans haven't even figured out how to discuss race, sex, or gender without it devolving into a tribal political fight. We shouldn't be surprised that algorithms we create and train on our own content will similarly be confused. Its the exact same reason we won't solve the alignment problem and have basically given up on it. We can't align humans with ourselves, we'll absolutely never define some magic ruleset tha…
We figured this out a long time ago. People are just bored and addicted to drama.
OK. Have a setting where you can choose either: 1. Attempt to correct inherent biases in training data and produce diverse output (May sometimes produce results that are geographically or historically unrepresentative) 2. Unfiltered (Warning. Will generate output that reflects biases and inequalities in the training data.) Default to (1) and surely everybody is happy? It's transparent and clear about what and why it'…
> Of course the politically sensitive people are waging war over it. Just like politically sensitive people waged war over Google identifying an obscured person as a Gorilla. Its just a silly mistake, how could anyone get upset over that?
No one is upset that an algorithm accidentally generated some images, they are upset that Google intentionally designed it to misrepresent reality in the name of Social Justice.
It’s really hard to get these things right: if you don’t attempt to influence the model at all, the nature of the imagery that these systems are being trained on skews towards stereotype, because a lot of our imagery is biased and stereotypical. It seems perfectly reasonable to say that generated imagery should attempt to not lean into stereotypes and show a diverse set of people.
In this case it fails because it is not using broader historical and social context and it is not nuanced enough to be flexible about how it obtains the diversity- if you asked it to generate some WW2 American soldiers, you could rightfully include other ethnicities and genders than just white men, but it would have to be specific about their roles, uniforms, etc.
(Note: I work at Google, but not on this, and just my opinions)
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