Anthropic’s $5 Million Push to Measure AI’s Effect on Wellbeing #1876

In this episode, Ray Cochrane records from the Michigan studio on the one year anniversary of losing the show’s original host, Todd Cochrane. The featured story is Anthropic’s $5 million grant program, which pays outside researchers to measure whether AI is actually good for the people using it. Ray also covers Anthropic’s Enterprise Frontier Safeguards, Google’s Fairwind cyber defense program, Meta’s organizational second brain, sixteen green AI projects across Asia-Pacific, an Oklahoma Bitcoin mine condemned after leaking 3.8 million gallons of water, BepiColombo closing in on Mercury, and the 2026 Ig Nobel Prizes. – Want to start a podcast? Its easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens from the studio in Michigan, recording on the one year anniversary of the show losing its original host, Todd Cochrane, his father. The family has gathered for the occasion. He also plans to record several episodes throughout the week as a commemorative run, so listeners should expect a heavier release schedule than usual. He also shares where things stand. He and Delaney have gone back and forth on relocating to Michigan, but the family is pushing, and the plan is firming up for the coming month or so. Part of the draw is getting his dad’s studio cleaned up and running the way it used to. Finally, he passes along an update on the Zuvers, a story long-time listeners will recognize. The father of the three children is due out of jail soon, though he now faces retrial for the murder of the three boys. Cochrane notes that the original prison term related to their return rather than the murders themselves. The family’s expectation, he says, is that this time the sentence will be permanent. Anthropic Puts $5 Million Behind Measuring AI’s Effect on You The featured story asks a question the industry has mostly avoided. Not whether a model is smart, but whether you are better off after using it. Anthropic is funding independent research to find out, and the structure is the interesting part. The money creates what the field calls evaluations: standardized tests for AI models. Hundreds already exist for coding, math, and reasoning. However, almost none measure whether the tool is good for the human on the other end. Crucially, Anthropic is not building these tests in-house. Grantees receive funding, model access and technical support, then work fully independently. Everything they produce must be published open source, so any developer at any company can run it. As Cochrane puts it, Anthropic is paying to create a ruler other people will use to measure Anthropic. The example Anthropic leads with is deliberately uncomfortable. Claude might offer diet and workout advice to someone asking about weight loss. But if that user has a history of disordered eating, the same response becomes actively harmful. Cochrane connects this to sycophancy, a topic the show has returned to before, and notes that models carry no real memory of who you are unless you tell them. That is exactly why the problem has gone unmeasured. Code compiles or it doesn’t. Math checks out or it doesn’t. Wellbeing has no answer key, because the identical response can help one person and harm the next. The Five Things Anthropic Wants These Tests to Do Cochrane walks through all five criteria, since each targets a specific way this research usually fails. First, state plainly what you are measuring. It is easy to measure something adjacent, such as how often a model uses warm language, then publish numbers about a proxy while claiming insight into loneliness itself. Second, involve clinicians and subject-matter experts in designing and validating the tests. A capable engineer may simply not know what the warning signs of an eating disorder look like in text. Without those people in the room, the test measures what engineers imagine the harm looks like. Third, count overcompliance and overrefusal as harms. Overcompliance is the obvious failure. Overrefusal is the model becoming so cautious it turns useless, or shutting down someone who had nowhere else to ask. Cochrane adds that overrefusal is far harder to spot, because you often cannot tell it is degrading until it has degraded. Fourth, reflect real multi-turn usage. Most safety testing throws one nasty question at a model and checks for refusal. Meanwhile, actual harm builds across a long conversation where every individual message reads as fine. Fifth, validate the automated graders against real experts. Scoring thousands of conversations means an AI grades the AI. Consequently, a subtly wrong grader skews every downstream number in the same direction, and nothing in the process flags it. Cochrane expects this to be the hardest criterion to satisfy, since psychiatric and medical specialists do not come cheap by the hour. Applications close September 21st, and shortlisted applicants will be notified by October 5th. Notably, the announcement names no individual researcher or executive. Sponsor: GoDaddy Economy hosting $6.99/month, WordPress hosting $12.99/month, domains $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Anthropic’s Enterprise Frontier Safeguards Keep Your Logs in Your Vault Anthropic’s second announcement targets a completely different audience. Catching misuse across many sessions requires keeping logs. However, banks and hospitals cannot hand that data to an outside vendor, because regulators will not allow it. Safety monitoring and compliance were in direct conflict. The fix moves where the data lives. Activity logs go into the customer’s own cloud bucket at Amazon, Microsoft or Google, locked with keys the customer controls. Automated systems scan a rolling window for serious abuse such as credential theft, and alerts route straight to the customer’s own security team. No human at Anthropic reads it, and Anthropic does not charge for the feature. The backstory explains the urgency. Anthropic had begun retaining thirty days of data with its Fable 5 model, specifically to catch patterns that only appear across multiple sessions. Regulated customers had to walk away immediately. Over a hundred organizations helped shape the result, including a quarter of the Fortune 100 and every US globally systemically important bank. It works across Claude Code, Claude Enterprise, Amazon Bedrock, and Microsoft Foundry. Wells Fargo’s security team put it simply, saying their logs stay in a Wells-managed environment under Wells-managed keys. Cochrane adds a personal note on the same retention change. Because transcripts now persist thirty days after last touch, he can keep Claude Code threads open far longer and lean on clear without losing context. Google’s Fairwind Program Hands Patching to the Machines Google is running the same play from the defensive side. Normally, a human engineer must reproduce a security flaw, understand it, write a fix, then prove the fix broke nothing else. That can stretch to weeks, and attackers live in exactly that gap. Fairwind pairs two systems to close it. Gemini 3.8 Flash Cyber is a model tuned for security work. CodeMender hunts for flaws and writes the patches. Together, Google says they produce verified, deployment-ready patches in minutes, running inside the customer’s own environment. Access is deliberately restricted to three groups: national cyber authorities; critical infrastructure operators in healthcare, telecom, energy, and finance; and major technology platform providers. More than 650 partners are involved. Cochrane’s take centers on logging quality. Systems that emit specific, unique errors rather than generic ones let these tools find real issues almost immediately. Furthermore, he sees value in purpose-tuned models over general ones, since different training data and methodology surface gaps a single familiar model would miss. Meta Built an AI That Learns From Its Own Experts Every organization has two or three people who actually understand the hard systems. When they are busy, everyone waits. When they leave, the knowledge leaves too. Most AI assistants address this with retrieval, searching documents when you ask. Meta went the other way. A long-running offline process digests the source material ahead of time into more than 200 structured knowledge files, so the thinking happens before anyone asks. On top sit what Meta calls recipes, step-by-step procedures mirroring how a specialist actually works a problem. The reported numbers are concrete. Restructuring cut tokens consumed per turn by 80 percent. Assessments that took days now take minutes. The team built the whole system in six weeks across three sprints. Cochrane focuses on the feedback loop. Normally, an expert corrects an assistant in chat; the answer improves once, then the system forgets. Meta’s version compiles corrections into knowledge files and regression-tests them, so fixes stick without retraining the model. However, he raises two real caveats from his own attempts. Building those knowledge files is token-heavy, and codebases change. If the offline process does not rerun, the documentation drifts away from the code it describes. He also predicts this will become a service offered by AWS, GitHub, or GitLab rather than something each company builds alone. Sixteen Green AI Projects Across Asia-Pacific Google DeepMind named the first cohort of its Accelerator: AI for the Planet program. Sixteen organizations span New Zealand, Singapore, South Korea, Indonesia, Thailand, India, Australia and Japan, receiving three months of access to Google’s AI stack plus mentorship and a Singapore bootcamp. Several stand out. A New Zealand outfit called 800 Trust uses bioacoustics, monitoring an ecosystem by listening to it and running AI over continuous audio to track biodiversity. Wildlife.ai builds open-source AI camera traps. Australia’s X-Centric replaced the soil lab with a handheld X-ray reader that answers a farmer standing in the field. In India, Climitra Carbon verifies invasive species removal and converts the biomass into biochar. Access matters more than money, as Cochrane points out. A six-person conservation nonprofit cannot run frontier models, because the compute bill alone would consume its operating budget. The organizations closest to these problems have always been furthest from the tooling. An Oklahoma Bitcoin Mine Condemned After Leaking 3.8 Million Gallons Cochrane corrects the figure up front. Many outlets report three million gallons, but El Reno city officials put it at 3.8 million. A Bitcoin mining operation on West Jensen Road leaked water and dropped pressure badly enough to close El Reno Public Schools, the Canadian County Courthouse, and other city and county offices. It happened during a month with 24 days above 100 degrees, in a region under severe to extreme drought. The leak is not the damning part. The city issued a stop-work order on the site back in 2023 for electrical, construction, and fire safety violations, then never followed up. The facility ran roughly three years under an order nobody enforced. Interim city manager Ken Brown did not dodge it, saying simply, “We failed.” The site is now posted as condemned with a ten-day removal notice, and a hearing with operator Athlon BT is set for September 14th. Reaching the company has proven difficult, with a website stuck on a maintenance notice and an unanswered California phone number. Cochrane draws one distinction that the coverage keeps blurring. This is a Bitcoin mining rig, not a hyperscale AI data center. The residents who lost pressure absorbed the cost, and nobody billed the operator for the aquifer. BepiColombo Closes In on Mercury After Eight Years Reaching the closest planet to the Sun took nearly eight years, which sounds backward until you understand the physics. Falling toward the Sun means gaining enormous speed, and a spacecraft arriving too fast simply sails past. So the mission spent those years shedding velocity across nine gravity-assist flybys: one at Earth, two at Venus, and six at Mercury itself. On September 3rd, the transfer module separated and was discarded more than 200 million kilometers from Earth. Mission control marked the moment with “Roll call completed, GO for separation.” Importantly, the spacecraft has not arrived yet. Orbit insertion is November 21st, the two science orbiters separate around December 9th and 10th, and science operations begin in April 2027. That November date is revised, having slipped from an earlier plan. Two orbiters fly because they do different jobs. Europe’s Mercury Planetary Orbiter studies the planet and what lies beneath its surface. Japan’s Mio studies the magnetosphere. Mercury having a magnetic field at all is genuinely odd, since a planet that small should have cooled and lost it long ago. The mission honors Giuseppe “Bepi” Colombo, the Italian mathematician who worked out how to slingshot a spacecraft to Mercury in the first place. NASA Builds a Rocket Engine Talk You Can Hear NASA hosts a webinar on Friday, October 2nd at 2 pm Eastern, titled “The RS-25 Engine and the Future of Artemis Missions.” It runs about two hours, is open to anyone, and RSVPs close September 25th. The RS-25 is not new hardware. It is the Space Shuttle main engine, the same design that flew 135 shuttle missions across three decades, now bolted four at a time into the SLS core stage. Together they produce roughly 2.2 million pounds of thrust at 111 percent of their original shuttle rating. Throwing them away is the strange part. These are precision engines built to fly repeatedly, yet Artemis expends four on every launch. NASA got a proven engine and skipped a decade of development, and that is the trade. The accessibility work is the real story. The event includes an audio-described video of an engine test firing, a live Q&A with an Artemis engineer, and a panel on accessibility in space and science. A test firing normally sells entirely on spectacle. Conveying that, and the engineering underneath it, without the visuals is a genuine design problem NASA built the whole event around solving. Buried Underwear Wins a 2026 Ig Nobel The 2026 Ig Nobel Prizes were awarded September 3rd in Zurich. Marc Abrahams launched them in 1991 at the satirical magazine Annals of Improbable Research, and what began as a roast is now something researchers actively want. The soil science prize went to a team that buried 1,000 pairs of underwear across more than 25 countries and dug them up two months later. Measuring how much cotton rotted turns out to be a cheap, surprisingly good proxy for how biologically alive the soil is. The biomechanics prize recognized a precise, cross-species definition of kissing that works for animals and excludes passing food. By that definition, polar bears kiss, some birds kiss, and so do ants. Nature reports the behavior traces back roughly 21.5 million years to the ancestor of all large apes, meaning ancient humans very likely kissed Neanderthals. Cochrane’s favorite was the physics prize, awarded for a splash-free urinal design that reportedly cuts spray to 1.4 percent of normal. Cochrane closes by pointing listeners to the GNC Insider program, the newsletter, and podcastapps.com for a modern podcast app. Feedback on the show’s format is explicitly welcome at [email protected], where either Ray or Chris will read it. The post Anthropic’s $5 Million Push to Measure AI’s Effect on Wellbeing #1876 appeared first on Geek News Central.