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"The noise got so loud it caught the ear of parliament: the digital, culture, media and sport select committee opened an inquiry into the fairness of the "streaming economy". "

""We believe the government should introduce legislation that ensures commercial images are labelled with a logo where any part of the body, including its proportions and skin tone, are digitally altered," its report says. Meanwhile, it says dermal fillers should be made prescription-only substances, in line with Botox, and there should be minimum training standards for providers."

"In the fall of 2020, gig workers in Venezuela posted a series of images to online forums where they gathered to talk shop. The photos were mundane, if sometimes intimate, household scenes captured from low angles-including some you really wouldn't want shared on the Internet. In one particularly revealing shot, a young woman in a lavender T-shirt sits on the toilet, her shorts pulled down to mid-thigh. The images were not taken by a person, but by development versions of iRobot's Roomba J7 series robot vacuum. They were then sent to Scale AI, a startup that contracts workers around the world to label audio, photo, and video data used to train artificial intelligence."

"The music industry is urging streaming platforms not to let artificial intelligence use copyrighted songs for training, in the latest of a run of arguments over intellectual property that threaten to derail the generative AI sector's explosive growth. In a letter to streamers including Spotify and Apple Music, the record label Universal Music Group expressed fears that AI labs would scrape millions of tracks to use as training data for their models and copycat versions of pop stars."

""An emotionally intelligent human does not usually claim they can accurately put a label on everything everyone says and tell you this person is currently feeling 80% angry, 18% fearful, and 2% sad," says Edward B Kang, an assistant professor at New York University writing about the intersection of AI and sound. "In fact, that sounds to me like the opposite of what an emotionally intelligent person would say." Adding to this is the notorious problem of AI bias. "Your algorithms are only as good as the training material," Barrett says. "And if your training material is biased in some way, then you are enshrining that bias in code.""

"Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study."

"The Ukrainian military has used AI-equipped drones mounted with explosives to fly into battlefields and strike at Russian oil refineries. American AI systems identified targets in Syria and Yemen for airstrikes earlier this year. The Israel Defense Forces, meanwhile, used another kind of AI-enabled targeting system to label as many as 37,000 Palestinians as suspected militants during the first weeks of its war in Gaza."

"The "March 2013 Watchlisting Guidance," a 166-page document issued last year by the National Counterterrorism Center, spells out the government's secret rules for putting individuals on its main terrorist database, as well as the no fly list and the selectee list, which triggers enhanced screening at airports and border crossings."

"This week, Atlassian's . This follows the trend of more and more high-profile hacks that are waking consumers up - like , , and the that rocked the country when 40 million debit and credit card numbers stolen during the holiday shopping time that year. (See of all the hacks from 2004 - present.)"

"Let's return to my favorite analogy for thinking about issues surrounding youth and social media: cars. Cars can be incredibly dangerous! There's a reason we don't let kids drive them until a certain age, and even then, put all sorts of safety measures in place. Now, let's imagine every time you got into a car, you got a warning saying "This car might crash and kill you." This would certainly raise your awareness that cars are dangerous. It would scare you. But would it change your behavior? Now, let's say you added an "action" to the end: "This car might crash and kill you…but putting on your seatbelt right now will reduce the risk of death by 500%."   It's long been known that fear-based public health messaging cannot simply describe a threat-it also needs to recommend an action to be effective. First you learn what could go wrong, then you learn what to do to avoid it.  So, will warning parents that social media use "is associated with significant mental health harms for adolescents" actually change their behavior? Will it lead to them more effectively limiting, monitoring, and/or managing their kids' social media use? "