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" 'Serious concerns' about DWP's use of AI to read correspondence from benefit claimants White mail system handles 'highly sensitive personal data' and people not told it is processing their information AI prototypes for UK welfare system dropped as officials lament 'false starts' Robert Booth UK technology editor Mon 27 Jan 2025 05.00 GMT Share When your mailbag brims with 25,000 letters and emails every day, deciding which to answer first is daunting. When lurking within are pleas for help from some of the country's most vulnerable people, the stakes only get higher. That is the challenge facing the Department for Work and Pensions (DWP) as correspondence floods in from benefit applicants and claimants - of which there are more than 20 million, including pensioners, in the UK. The DWP thinks it may have found a solution in using artificial intelligence to read it all first - including handwritten missives. Human reading used to take weeks and could leave the most vulnerable people waiting for too long for help. But "white mail" is an AI that can do the same work in a day and supposedly prioritise the most vulnerable cases for officials to get to first."

"There is also a lot of research that both third-party fact-checking and Community Notes can be really effective at reducing misperceptions. But - and this is a significant caveat - neither works well as a complete solution for lies on social media. When Twitter was working on Birdwatch, they claimed it would "not replace other labels and fact checks Twitter currently uses". But as I've written about before, Musk scaled back Twitter's Trust and Safety team significantly and positioned Community Notes as the replacement. As Yoel Roth, Twitter's former head of Trust and Safety, told WIRED, "The intention of Birdwatch was always to be a complement to, rather than a replacement for, Twitter's other misinformation methods." In fact, research on various attempts to mitigate COVID misinformation found that a layered, "Swiss cheese" approach might work best, where some efforts work well sometimes, but collectively the system catches most falsehoods."

"This cycle is particularly painful for non-engineers because they lack the mental models to understand what's actually going wrong. When an experienced developer encounters a bug, they can reason about potential causes and solutions based on years of pattern recognition. Without this background, you're essentially playing whack-a-mole with code you don't fully understand."

"For higher-complexity problems, however, the models would enter "collapse", failing to generate any correct solutions. In one case, even when provided with an algorithm that would solve the problem, the models failed. The paper said: "Upon approaching a critical threshold - which closely corresponds to their accuracy collapse point - models counterintuitively begin to reduce their reasoning effort despite increasing problem difficulty." The Apple experts said this indicated a "fundamental scaling limitation in the thinking capabilities of current reasoning models"."

"In 2015, a research group fed an AI system called Deep Patient health and medical data from some 700,000 people, and tested whether it could predict diseases. It could, but Deep Patient provides no explanation for the basis of a diagnosis, and the researchers have no idea how it comes to its conclusions. A doctor either can either trust or ignore the computer, but that trust will remain blind."

"What might happen next? First the investigators would find out the culprits' names, telephone numbers, and where they lived. Then the authorities would be alerted. Shortly afterwards, accounts would be closed down. And, in the worst cases, the police would prosecute. Finally, as people began to realise that actions online had actual consequences, many would start modifying their behaviour. The tsunami of online hate might eventually become a sea swell."

"Three-Dimensional Computer Simulations Have Solved The Mystery Of Why Doomed Stars Explode"

""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.""

""When a new technology comes to town, we have choices about how to use it," he said. "It doesn't necessarily need to broadcast propaganda, [and] it doesn't have to become a commercial free-for-all. Instead, we can look at a new technology and invent something new.""

"Decentralized storage platforms break apart the users' files and distribute them across multiple nodes on their network. Since the data is scattered across multiple nodes, there is no single point of failure."