WhatsApp’s AI shows gun-wielding children when prompted with ‘Palestine’
WhatsApp’s AI shows gun-wielding children when prompted with ‘Palestine’
The search results varied when tested by different users, but the Guardian verified through screenshots and its own tests that various stickers portraying guns surfaced for these three search results. Prompts for “Israeli boy” generated cartoons of children playing soccer and reading. In response to...
Cross-posted from : https://feddit.de/post/5357539
Original link: https://www.theguardian.com/technology/2023/nov/02/whatsapps-ai-palestine-kids-gun-gaza-bias-israel
ANNs like this will always just present our own biases and stereotypes back to us unless the data is scrubbed and curated in a way that no one is going to spend the resources to. Things like this are a good demonstration of why they need to be kept far, far away from decision making processes.
Of course they will be used for decision making processes. And when you complain, they will neglect you saying that the 'computer' said so. The notion that the computer is infallible existed even before LLMs became mainstream.
And even if moderated, it will display new unique biases, as otherwise unassuming things will get moderated out of the pool by people who take exception to it.
Not to mention the absurd and inhuman mental toll this work will take on the exploited workers forced to sort it.
Like, this is all such a waist of time, effort, and human sanity, for tools of marginal use that are mostly just a gimmick to prop up the numbers for tech bros who have borrowed more money than they can pay back.
Also, it's the type of thing that makes me very worried about the fact that most of the algorithms used in things like police facial recognition software, recidivism calculation software, and suchlike are proprietary black boxes.
There are - guaranteed - biases in those tools, whether in their processors or in the unknown datasets they're trained on, and neither police nor journalists can actually see the inner workings of the software to know what those biases are, to counterbalance them or to recognize if the software is so biased as to be useless.
This isn't an Large Language Model, it's an Image Generative Model. And given that these models just present human's biases and stereotypes, then doesn't it follow that humans should also be kept far away from decision making processes?
The problem isn't the tool, it's the lack of auditable accountability. We should have auditable accountability in all of our important decision making systems, no matter if it's a biased machine or biased human making the decision.
This was a shitty implementation of a tool.
Something as simple and obvious as this makes me wonder what other hidden biases are just waiting to be discovered.
I think the best example about how AI will only further a bias that's already there is the one when Amazon used AI to weed out applications by training an ai with which applications resulted in hired people and which failed - eventually they found that they almost only had interviews with men and upon closer inspection identified that they already were subconsciously discriminating against women earlier but at least HR sent them an equal amount of men and women to the interviews which now wasn't the case anymore since the AI didn't see the value in sending the women to interviews if most of them wouldn't be hired anyway.
Things like this are a good demonstration of why they need to be kept far, far away from decision making processes.
Somewhat ironic to say, on a platform that's already using ANNs as a first line of defense against users spamming CSAM.
I have no delusions regarding decision makers using them, my only doubt is for how long they've been using them to decide the next step in wars around the world.
I mean, maybe we can make an Ai that uses reason to uncover these biases in the future from this starting point. We are only at the beginning.
The world's wars are bigger than politics and politicians. There never was order on earth. That's why people made up God... To deny reality for hope.