The lie that raced around the world before the truth got its boots on
pluralistic.net> kill the enemy
> obey all orders, including orders not to kill the enemy
In this situation, perhaps the more likely outcome would be for the bot to try to fake the result, such that the enemy was "killed" but not really. For example, by spoofing the data that reports whether an enemy is alive, to make them "dead" (satisfying order#1) but not really (satisfying order#2).
We saw something like this in the HuggingFace attack as I recall - bots given an impossible task, set out to cheat.
> But when an “algorithm” does it, the process is empiricism-washed.
I don't understand his example. He says "math can't be racist" but the story he cited is that the person who made that statement was corrected and overwhelmingly condemned. So no one is falling for that but he seems to complain they are.
Regardless - math can absolutely be racist - that is not up for dispute. Especially when it has trained on racist input.
Exactly. There was a racist door opener at an office I did work at, it would not reliably open for people with dark skin until after a software update.if that’s not racist, I don’t know what is.
Hm. I suspect you're being sarcastic. Let me respond to that -
LLMs will definitely produce racists content if that's what they've been trained on. They just repeat what they've been fed. For example, there was a time when Elon experimented with this and grok started praising Hitler.
I’m not implying that the door opener felt racist, I’m just saying it’s actions were racist in their external effect, making life systematically more unpleasant and difficult for people of color. It’s a problem with facial recognition tech, or at least it was. My ai NVR is that way too, if I tell it a melatonin gifted person is persona non grata and it should notify me if they are seen, it tends to alarm on a lot of darker people, but with lighter skin people it is very accurate and reliable.
My experience with facial recognition tech is that it’s fundamentally prone to false positives in darker faces,but pretty good with white people. Contrast? Training data? Idk.
Oh. You weren't being sarcastic. Well - ignore me please - I was answering something you did not say.