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"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. "

""This is the first time such machine learning tools have been used in this context," says Fluri, "and we found that the deep artificial neural network enables us to extract more information from the data than previous approaches. We believe that this usage of machine learning in cosmology will have many future applications.""

"The greatest propaganda machine in history. Think about it. Facebook, YouTube and Google, Twitter and others - they reach billions of people. The algorithms these platforms depend on deliberately amplify the type of content that keeps users engaged - stories that appeal to our baser instincts and that trigger outrage and fear. It's why YouTube recommended videos by the conspiracist Alex Jones billions of times. It's why fake news outperforms real news, because studies show that lies spread faster than truth. And it's no surprise that the greatest propaganda machine in history has spread the oldest conspiracy theory in history - the lie that Jews are somehow dangerous. As one headline put it, "Just Think What Goebbels Could Have Done with Facebook.""

"acebook has come under fire this week after a hoax story about women being abducted in white vans went viral on its platform. The site's algorithms are thought to have perpetuated the circulation of the story."

"The robots, which are less than 1mm long, are designed by an "evolutionary algorithm" that runs on a supercomputer. "

"The results are unfortunately not surprising - countless studies have shown that facial recognition is susceptible to bias. A paper last fall by University of Colorado, Boulder researchers demonstrated that AI from Amazon, Clarifai, Microsoft, and others maintained accuracy rates above 95% for cisgender men and women but misidentified trans men as women 38% of the time."

"What Hamilton and his colleagues found surprising was that this approach could also be applied to helping find problems with existing deep networks, related to the surge of "deepfakes" that have recently cropped up. They applied this data structure to find areas where probabilistic models, such as the generative adversarial networks (GANs) that are often used to create deepfakes, break down. They coined these problematic areas "blind spots," and note that they give us insight into how GANs can be biased. Such blind spots further show that GANs struggle to represent particular areas of a dataset, even if most of their fakes can fool a human. "

"However, the recent study's seemingly high-tech attempt to pick out facial features associated with criminality borrows directly from the 'photographic composite method' developed by the Victorian jack-of-all-trades Francis Galton - which involved overlaying the faces of multiple people in a certain category to find the features indicative of qualities like health, disease, beauty and criminality."

""It marks an exciting moment for the field," said Demis Hassabis, DeepMind's founder and chief executive. "These algorithms are now becoming mature enough and powerful enough to be applicable to really challenging scientific problems." Advertisement Venki Ramakrishnan, the president of the Royal Society, called the work "a stunning advance" that had occurred "decades before many people in the field would have predicted"."

"After being set an overarching goal like maximizing profit, they develop their own strategies based on experience of the market, often with little human oversight. The most advanced also use forms of AI whose workings are opaque even if humans wanted to peer inside."

"Researchers at Columbia University sought to shed light on the problem by tasking 400 AI engineers with creating algorithms that made over 8.2 million predictions about 20,000 people. In a study accepted by the NeurIPS 2020 machine learning conference, the researchers conclude that biased predictions are mostly caused by imbalanced data but that the demographics of engineers also play a role."

"Because YouTube is the dominant player in the online video market, its choices dictate the norms of the whole industry. And unfortunately for independent creators, YouTube has proven to be more interested in appeasing large copyright holders than protecting free speech or promoting creativity. Through its automatic copyright filter, Content ID, YouTube has effectively replaced legal fair use of copyrighted material with its own rules."

"The Cyberspace Administration of China (CAC) unveiled a 30-point draft proposal for "algorithm recommendation management regulations" that would directly affect companies including ByteDance, Tencent Holdings and Kuaishou Technology. The rules would forbid practices that "encourage addiction or high consumption", as well as any activities that endanger national security or disrupt social and economic order."

"On Wednesday, California Gov. Gavin Newsom signed a bill into law that directly affects "mega-retailers" like Amazon, and how these companies use algorithms to manage warehouse workers. Mega-retailers are those that employ more than 1,000 warehouse workers, and they include one of Amazon's main competitors, Walmart."

"Twitter has admitted it amplifies more tweets from rightwing politicians and news outlets than content from leftwing sources. The social media platform examined tweets from elected officials in seven countries - the UK, US, Canada, France, Germany, Spain and Japan. It also studied whether political content from news organisations was amplified on Twitter, focusing primarily on US news sources such as Fox News, the New York Times and BuzzFeed."

"Growth, then, is the animating ideal behind the platforms these companies build, and 'persuasive technology' is the means of achieving this. The research this technology is built on draws on everything from dopamine studies to behavioural psychology and addiction analysis. Features galore have emerged to keep our attention, from the endless scroll to dark patterns, but one is more important than all others, according to Fisher: recommendation algorithms."

"A startup in Israel is tackling the problem, and saving lives, with a sophisticated algorithm that can analyze the almost infinite number of possible conflicts. Ask any doctor or pharmacist and they'll tell you about the minefield called "drug interaction". That's when a medicine designed to resolve one problem causes an adverse reaction with another medicine designed to resolve another problem. Or with anything else the patient puts in their body."

"This is partially why online anonymity is so important - it gives people the grace of exploration and inquiry. It allows people to make choices, change their minds, learn, and grow. TikTok doesn't make room for this kind of internet exploration; it makes it impossible to have curiosity without consequence. TikTok isn't alone in using engagement and recommender algorithms to curate personalised content feeds, but it does take it to the extreme. This is profitable both because it keeps people scrolling and because there's very little difference between being able to personalise content and personalise ads."

"Google should know better, given that it already had a "hallucination problem" with its featured snippets(Opens in a new tab) at the top of search results back in 2017. The snippets algorithm seemed to particularly enjoy telling lies about U.S. presidents. Again, what could go wrong?"

"These are the early days of the data revolution in personal decision-making. I am not claiming that we can completely outsource our lifestyle choices to algorithms, though we might get to that point in the future. I am claiming instead that we can all dramatically improve our decision-making by consulting evidence mined from thousands or millions of people who faced dilemmas similar to ours. And we can do that now."