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"Facebook has said it will start labelling misinformation about the climate crisis in a small trial limited to the UK. Labels will be attached to certain posts directing users to Facebook's Climate Science Information Center, a repository of fact-checked claims about the environment. The company has not yet said how it will decide which posts receive the label, but the process is similar to that used in the US election when it attempted to algorithmically discern posts that shared common myths or misconceptions, and appended a link taking users to a "voting information centre"."

"Some experts see platforms like Appen as a new form of data colonialism, says Saiph Savage, director of the Civic AI lab at Northeastern University. "Workers in Latin America are labeling images, and those labeled images are going to feed into AI that will be used in the Global North," she says. "While it might be creating new types of jobs, it's not completely clear how fulfilling these types of jobs are for the workers in the region." Due to the ever moving goal posts of AI, workers are in a constant race against the technology, says Schmidt. "One workforce is trained to three-dimensionally place bounding boxes around cars very precisely, and suddenly it's about figuring out if a large language model has given an appropriate answer," he says, regarding the industry's shift from self-driving cars to chatbots. Thus, niche labeling skills have a "very short half-life." "From the clients' perspective, the invisibility of the workers in microtasking is not a bug but a feature," says Schmidt. Economically, because the tasks are so small, it's more feasible to deal with contractors as a crowd instead of individuals. This creates an industry of irregular labor with no face-to-face resolution for disputes if, say, a client deems their answers inaccurate or wages are withheld. The workers WIRED spoke to say it's not low fees but the way platforms pay them that's the key issue. "I don't like the uncertainty of not knowing when an assignment will come out, as it forces us to be near the computer all day long," says Fuentes, who would like to see additional compensation for time spent waiting in front of her screen. Mutmain, 18, from Pakistan, who asked not to use his surname, echoes this. He says he joined Appen at 15, using a family member's ID, and works from 8 am to 6 pm, and another shift from 2 am to 6 am. "I need to stick to these platforms at all times, so that I don't lose work," he says, but he struggles to earn more than $50

"Twitter is expanding its use of warning labels on tweets that contain misleading details about coronavirus vaccines. The move, announced in a blogpost on Monday, is designed to strengthen the social network's existing Covid-19 guidance, which has led to the removal of more than 8,400 tweets and challenged 11.5m accounts worldwide."

"Some Facebook users who recently watched a Daily Mail video depicting Black men reported seeing a label from Facebook asking if they were interested in watching more videos about "primates." The label appeared in bold text under the video, stating "Keep seeing videos about Primates?" next to "Yes" and "Dismiss" buttons that users could click to answer the prompt. It's part of an AI-powered Facebook process that attempts to gather information on users' personal interests in order to deliver relevant content into their News Feed"

"Facebook and Instagram users will start seeing labels on AI-generated images that appear on their social media feeds, part of a broader tech industry initiative to sort between what's real and not. Meta said Tuesday it's working with industry partners on technical standards that will make it easier to identify images and eventually video and audio generated by artificial intelligence tools."

""We have evidence that applying these informs to posts decreases their reshares by ~8%," a Facebook data scientist told BuzzFeed. "However given that Trump has SO many shares on any given post, the decrease is not going to change shares by orders of magnitude.""

"Facebook failed to label 80% of articles on its platform promoting a fast-spreading conspiracy theory that the US is funding the use of bioweapons in Ukraine, according to a study released Friday by the Center for Countering Digital Hate (CCDH)."

"Imagine if it would have more of an impact for Palestine to be recognised as a sovereign country by Google than by the UN. It's a suggestion that's caught fire - a five-month-old online petition demanding Palestine be labeled and bordered in Google Maps has gained more than 250,000 signatures just over the past few days."

"The response on Twitter was predictably splenetic. Suárez's supporters claimed the images were manipulated, their argument promoted by a rather well-done diptych which did the rounds. The left-hand image - which had been photoshopped to remove the marks - purported to be the "real" unaltered version, while the right hand side - Gentile's original image - was labelled the fake."

"Facebook is considering incorporating most of its 1 billion-plus members' profile photos into its growing facial recognition database, expanding the scope of the social network's controversial technology. The possible move, which Facebook revealed in an update to its data use policy on Thursday, is intended to improve the performance of its "tag suggest" feature. The feature uses facial recognition technology to speed up the process of labelling or "tagging" friends and acquaintances who appear in photos posted on the network"

"His software is not labeled anything as grand as artificial intelligence. It's machine learning, facilitating and extending his own words, his own imagination. At one level, it merely helps him do what fledgling writers have always done - immerse themselves in the works of those they want to emulate. Hunter Thompson, for instance, strived to write in the style of F. Scott Fitzgerald, so he retyped "The Great Gatsby" several times as a shortcut to that objective."

"Affectiva is running a program that pays drivers to help train its emotion-recognition system. The company sends drivers a kit including cameras and other sensors to place within their vehicles. These record a person's facial expressions, gestures, and tone of voice on the road. That data is then labeled by trained specialists for a range of emotions, and fed into deep neural networks."

"At Imperial College London, Murray Shanahan and colleagues are working on a way around this problem using an old, unfashionable technique called symbolic AI. "Basically this meant an engineer labelled everything for the AI," says Shanahan. His idea is to combine this with modern machine learning. Symbolic AI never took off, because manually describing everything quickly proved overwhelming. Modern AI has overcome that problem by using neural networks, which learn their own representations of the world around them. "They decide what is salient," says Marta Garnelo, also at Imperial College."

"The new policy is a major shift in Twitter's efforts to balance its ideological commitment to free expression with user demands for improved enforcement of rules against harassment, hate speech and other toxic behavior."

"But even cleverest AI can be fooled with the simplest of hacks. If you write out the word "iPod" on a sticky label and paste it over the apple, Clip does something odd: it decides, with near certainty, that it is looking at a mid-00s piece of consumer electronics. In another test, pasting dollar signs over a picture of a dog caused it to be recognised as a piggy bank."

"Most people are aware of the cookies that track them across the web, and the privacy-invading practices of Google search, but did you know Google's email service, Gmail, collects large amounts of data too? This was recently put into stark focus for iPhone users when Gmail published its app "privacy label" - a self-declared breakdown of the data it collects and shares with advertisers as part of a new stipulation on the Apple App Store."

"Beginning in 2017, I did a project with artist Trevor Paglen to look at how people were being labelled. We found horrifying classificatory terms that were misogynist, racist, ableist, and judgmental in the extreme. Pictures of people were being matched to words like kleptomaniac, alcoholic, bad person, closet queen, call girl, slut, drug addict and far more I cannot say here. ImageNet has now removed many of the obviously problematic people categories - certainly an improvement - however, the problem persists because these training sets still circulate on torrent sites [where files are shared between peers]."

"Iran's missile attacks on two Iraqi airbases have been accompanied by a spread of online disinformation, falsely labelled images and claims of news sources being hacked, which have added to jitters in the region regarding the attacks."

"The pictures, analyzed by HuffPost, show a picture of Biden had been edited to make him look older, by darkening his skin and emphasizing imperfections. On Monday the campaign's Trump War Room Twitter account tweeted a manipulated video that appeared to show Biden saying, "You won't be safe in Joe Biden's America." The video was labelled "manipulated media" by Twitter."