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Ex-NSA Hacker Is Building an AI To Find Hate and Far-Right Symbols on Twitter and Facebook (vice.com)
Motherboard reporter Lorenzo Franceschi-Bicchierai has interviewed Emily Crose, a former NSA hacker, who has built NEMESIS, an AI-powered program that can help spot symbols that have been co-opted by hate groups to signal to each other in plain sight. Crose, who has also moderated Reddit in the past, thought of building NEMESIS after the Charlottesville, Virginia incident last year. From the report: Crose's motivation is to expose white nationalists who use more or less obscure, mundane, or abstract symbols -- or so-called dog whistles -- in their posts, such as the Black Sun and certain Pepe the frog memes. Crose's goal is not only to expose people who use these symbols online but hopefully also push the social media companies to clamp down on hateful rhetoric online. "The real goal is to educate people," Crose told me in a phone call. "And a secondary goal: I'd really like to get the social media platforms to start thinking how they can enforce some decency on their own platforms, a certain level of decorum." [...]
At a glance, the way NEMESIS works is relatively simple. There's an "inference graph," which is a mathematical representation of trained images, classified as Nazi or white supremacist symbols. This inference graph trains the system with machine learning to identify the symbols in the wild, whether they are in pictures or videos. In a way, NEMESIS is dumb, according to Crose, because there are still humans involved, at least at the beginning. NEMESIS needs a human to curate the pictures of the symbols in the inference graph and make sure they are being used in a white supremacist context. For Crose, that's the key to the whole project -- she absolutely does not want NEMESIS to flag users who post Hindu swastikas, for example -- so NEMESIS needs to understand the context. "It takes thousands and thousands of images to get it to work just right," she said.
At a glance, the way NEMESIS works is relatively simple. There's an "inference graph," which is a mathematical representation of trained images, classified as Nazi or white supremacist symbols. This inference graph trains the system with machine learning to identify the symbols in the wild, whether they are in pictures or videos. In a way, NEMESIS is dumb, according to Crose, because there are still humans involved, at least at the beginning. NEMESIS needs a human to curate the pictures of the symbols in the inference graph and make sure they are being used in a white supremacist context. For Crose, that's the key to the whole project -- she absolutely does not want NEMESIS to flag users who post Hindu swastikas, for example -- so NEMESIS needs to understand the context. "It takes thousands and thousands of images to get it to work just right," she said.
He's a trans SJW who often writes about the trials of being a female in IT. To this person ANYONE who doesn't celebrate their flavor of crazy is "far-right" and full of "hate".
Slightly more blacks per capita are killed as compared to whites, but when you look at the racial breakdown of violent crimes they are disproportionately committed by blacks. When you scale for criminal activity, blacks are actually shot less than whites.
Browsing at +1 - no ACs, I ignore their posts. So refreshing!
"But now gay people want to force bakers to bake them cakes "
How about another way of seeing it? How about gay people don't want to be denied basic commercial services provided to everyone else? If a baker can tell a gay couple they won't make them a cake they can tell a black couple the same.
I ignore Anonymous Coward posts. If you want to discuss something, that's awesome. Log in.
I used to listen to Radio 4 in the UK (that's a pretty "middle of the road" station).. At the hours I was in the car listening to it, Women's hour was often on; it was interesting to hear what the subjects were that women were focusing on, and sometimes came up with things that were worth pondering a lot from the male perspective..
I gave it up when day in, day out, they were getting further and further into 3rd wave/intersectional feminism.. Now this is a "mainstream" station, not an extreme or "out there" kind of place. I gave it up and just listen to the music stations now.
I'm finding 3rd wave being more and more "normal feminism".. If you're first or second wave feminist, it's not called "feminist" by a huge section these days, just "normal".. After the war of sex in feminism that led to 3rd wave, there's no agreement on what it means to be feminist, so you say what it means, and anyone who disagrees is an oppressor. I've had loads of 'mainstream' women tell me it's perfectly valid to put me down and be as abusive as they like, as I have "male privilege", and it's their enshrined right to do this.
That's a great example of Cherry Picking.
A rather fuller examination of the data, and a proper conclusion can be found here.
A quick hint, Vox are basically using mis-framing of the population statistics to give a completely wrong picture.
As a professional statistician, let me explain one big problem in your attempt to analyze racial shooting statistics:
Populations.
You are attempting to count the number of people shot of a given race against the ENTIRE US population for that race. However, that's not the group your sample is being chosen from. Your group is being chosen from amongst those that are interacting with police - if you never see a cop, you are not at risk of being shot.
The correct population to use is the number of white/black/etc people that interact with police (stopped, ticketed, arrested, anything) and compare that with the sample proportion that is shot/otherwise killed. Anything else is wrong, either due to ignorance or to perpetuate a deliberate falsehood.