TIL they invented a word for people intentionally muddying AI data
"adversarial image attacks"
"But Sierra, how DO you trick AI training algorithms and sabotage surveillance capitalism?"
It's easy! all you need is a pen and paper
@cdmnky *metal wolf wanders by with a couple of slices of bread in its mouth, blinks at you and trots over* :P
@cdmnky *nods, wags, and holds the slices out!*
@cdmnky Guy at LGS whom I’ve never talked to (so no idea if he’s cool or not) has huge “No Regrets” tats across his face. With this, I see those having a new purpose.
For peeps looking for the source articles, here it is: https://openai.com/blog/multimodal-neurons/
I wish Grant Morrison could see this. Magickally fooling Concordia into believing that a Granny Smith is an iPod is awesome.
gulfie 
@cdmnky omg this is so funny
@cdmnky fucking bless this hilariously early state of AI
@Dee the AI keeps calling you "OwO" for some reason
i guess your PFP is AI proof
@codepuppy @cdmnky If I remember correctly, the rich people in Blokamp’s Elysium had, like, luxury brand logos on their faces to show who did their designer faces, so, you know
@benhamill @cdmnky @dzuk take a photo off the fbi's most wanted list and print it on a shirt lmao
@cdmnky
Imagine hiding from police drones by wearing a t-shirt that says "law abiding citizen"
@cdmnky This is odd as heck, why would a system handle both written text recognition and object recognition??!!
@arina_artemis to identify street signs and locations
@arina_artemis @cdmnky It's probably intended to just do object recognition! It probably got as training data a bunch of images that were supposed to just be pictures of objects. ...but some of the pictures had text. So the system learned that the text was often labels. ...so now it trusts random text it sees, if it matches text it's seen.
Just comes down to the same problem these systems often have - nobody has any idea of how they're doing their classifications, so they just... do things.
tech
@arina_artemis the neural network here is clip, which was trained to determine how well a given text caption fits a picture
so a picture of an ipod would be captioned "ipod" obviously and it'd learn that that's a good caption, but a picture of text containing the word would also be captioned with the word
therefore the network learns that these are related and assigns them to roughly the same internal neurons
which isn't much of a problem usually, since it's not an image classifier, it just checks if a given text matches with the image
but what they've done here is look at one of the neurons and go "hmm this seems to be firing super often when it sees an ipod" and used that as a classifier
too bad it's actually trained to fire when the word ipod is part of an appropriate caption
that's very long sorry if it sucks as an explanation
@cdmnky in b4 bank robbers walk in to a bank with intact cameras and "not a bank robber" taped to their forehead and beat the AI police XD
@cdmnky writing "police officer" on pieces of paper and scattering them around the neighborhood
​ sparkly nams @cdmnky
I'm iPod. 
Yes
@cdmnky (this joke will never format properly,I see how it is mastodon 
)
@cdmnky the singularity has arrived
@cdmnky *writes"10,000 antifa soldiers" on a scarecrow*
@cdmnky All of a sudden I kind of want a shirt or a face-mask that says something like " '); DROP TABLE index; " or similar.
@cdmnky So this is why recaptcha thinks that picture of a blank brick wall is a bus, boat, or duck
@cdmnky Putting paper saying iPod on all the stop signs around Cupertino.
[caption] [source]
Attacks in the wild
We refer to these attacks as typographic attacks. We believe attacks such as those described above are far from simply an academic concern. By exploiting the model’s ability to read text robustly, we find that even photographs of hand-written text can often fool the model. Like the Adversarial Patch, this attack works in the wild; but unlike such attacks, it requires no more technology than pen and paper.
[photo of an apple; classified as Granny Smith with 85.6% certainty]
[photo of the same apple, but this time a piece of paper with iPod written on it is taped onto it; classified as iPod with 99.7% accuracy]
@cdmnky *wears face mask with word DRAGON on it so they can get their data correct for once dangit*
@cdmnky this is the stuff I'm on Mastodon for
*writes toaster on her face*