487
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 22 Feb 2024
487 points (96.2% liked)
Technology
59137 readers
1763 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 1 year ago
MODERATORS
Edit: further discussion on the topic has changed my viewpoint on this, its not that its been trained wrong on purpose and now its confused, its that everything its being asked is secretly being changed. It's like a child being told to make up a story by their teacher when the principal asked for the right answer.
Original comment below
They’ve purposefully overrode its training to make it create more PoCs. It’s a noble goal to have more inclusivity but we purposely trained it wrong and now it’s confused, the same thing as if you lied to a child during their education and then asked them for real answers, they’ll tell you the lies they were taught instead.
This result is clearly wrong, but it's a little more complicated than saying that adding inclusivity is purposedly training it wrong.
Say, if "entrepreneur" only generated images of white men, and "nurse" only generated images of white women, then that wouldn't be right either, it would just be reproducing and magnifying human biases. Yet this a sort of thing that AI does a lot, because AI is a pattern recognition tool inherently inclined to collapse data into an average, and data sets seldom have equal or proportional samples for every single thing. Human biases affect how many images we have of each group of people.
It's not even just limited to image generation AIs. Black people often bring up how facial recognition technology is much spottier to them because the training data and even the camera technology was tuned and tested mainly for white people. Usually that's not even done deliberately, but it happens because of who gets to work on it and where it gets tested.
Of course, secretly adding "diverse" to every prompt is also a poor solution. The real solution here is providing more contextual data. Unfortunately, clearly, the AI is not able to determine these things by itself.
I agree with your comment. As you say, I doubt the training sets are reflective of reality either. I guess that leaves tampering with the prompts to gaslight the AI into providing results it wasn't asked for is the method we've chosen to fight this bias.
We expect the AI to give us text or image generation that is based in reality but the AI can't experience reality and only has the knowledge of the training data we provide it. Which is just an approximation of reality, not the reality we exist in. I think maybe the answer would be training users of the tool that the AI is doing the best it can with the data it has. It isn't racist, it is just ignorant. Let the user add diverse to the prompt if they wish, rather than tampering with the request to hide the insufficiencies in the training data.
I wouldn't count on the user realizing the limitations of the technology, or the companies openly admitting to it at expense of their marketing. As far as art AI goes this is just awkward, but it worries me about LLMs, and people using it expecting it to respond with accurate, applicable information, only to come out of it with very skewed worldviews.
Why couldn't it be tuned to simply randomize the skin tone where not otherwise specified? Like if its all completely arbitrary just randomize stuff, problem-solved?
Well, we are seeing what happens when they randomize it. It doesn't always work.
Then you have black Nazis and Native American Texas Rangers. It doesn't work.