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"The campaign's most organized form involves a database set up by anonymous activists that lists targets in the military, their photos, their locations, and how they have offended. Offenders are ranked by "traitor level," from "elite" to "low." Individuals have also taken social punishment into their own hands by creating Facebook groups and viral posts that share the identities of military family members or supporters. For the anti-coup population living abroad, the main objective is to get generals' family members living outside the country deported and their assets frozen. Within Myanmar, the goal is social and economic pressure, with boycotts on businesses and brands, and hopes that social shaming will convince military affiliates to work against their families and support the Civil Disobedience Movement."

"EFF's Legal Director Corynne McSherry offers five lessons to keep in mind: 1. (Lots of) mistakes will be made: copyright takedowns result in the removal of tons of legitimate content. 2. Robots won't help: automated filtering tools like Content ID have been a disaster, and policing copyright with algorithms is a lot easier than policing "bad speech." 3. These systems need to be transparent and have due process. A system that allows for automated instant censorship and slow, manual review of censorship gives a huge advantage to people who want to abuse the system. 4. Punish abuse. The ability to censor other peoples' speech is no joke. If you're careless or malicious in your takedown requests, you should pay a consequence: maybe a fine, maybe being barred form using the takedown system. 5. Voluntary moderation quickly becomes mandatory. Every voluntary effort to stem copyright infringement has been followed by calls to make those efforts mandatory (and expand them)."

"Vast sums are being spent by governments across the industrialized and developing worlds on automating poverty and in the process, turning the needs of vulnerable citizens into numbers, replacing the judgment of human caseworkers with the cold, bloodless decision-making of machines. "

"Landsem's digital detective skills would help pivot the Norwegian approach to digital image-based abuse. In 2017, she discovered several nude images of Nora Mørk, a handball player on the national team. The case kickstarted a national debate and, in the summer of 2021, Norway made the spread of intimate images a crime punishable with up to one year of imprisonment - two if the abuse is "systematic" or "organised.""

"The public is often supportive of the use of such tech: 59% of U.K. adults told a survey they "somewhat" or "strongly" support police use of facial recognition technology in public spaces, and a Pew Research study found 46% of U.S. adults said they thought it was a good idea for society. In China, one study found that 51% of respondents approved of facial recognition tech in the public sphere, while in India, 69% of people said in a 2023 report that they supported its use by the police. But while authorities generally pitch facial recognition as a tool to capture terrorists or wanted murderers, the technology has also emerged as a critical instrument in a very particular context: punishing protesters. "

"There's a certain irony that, in fields outside of computer science, plagiarism is a sign that you didn't understand the question. Within computer science, the opposite is true. Not only have you found an acceptable solution, you've understood it enough to use it within the parameters of your own project."