Indigenous rangers in the Warddeken Indigenous Protected Area in West Arnhem, Northern Territory, ran the AI animal-detection model MegaDetector over…
Our take This is AI as a sieve, not a judge: it threw out the empty frames so rangers could spend their time on work only they can do. The credit goes to the Warddeken rangers and elders who set the terms first. Any program bringing AI onto Indigenous land should copy the order: consent, then code.
University of Kent researchers David Roberts and Jason R.C.
Our take Credit where it's due: the chatbots did better than search. But a safeguard that guards tigers and waves through corals and orchids protects what people find appealing, not what is endangered, and that gap is the AI companies' to close.
Researchers at Inria, Sorbonne Université and the insurer AXA compared three AI weather models — GenCast, FourCastNet 3 and FGN — with ECMWF's operational…
Our take Better cyclone tracks mean earlier warnings for the people in a storm's path. The catch is in the same paper: a model that places a storm well can still misjudge its strength. Forecasters should take the first finding and keep checking the second.
The European Centre for Medium-Range Weather Forecasts (ECMWF) said on Oct 12 that it has extended its machine-learning forecasting system, AIFS, into a…
Our take Ships, ports and coastal towns gain most if one model can forecast wind, waves and sea ice together a day further out. This is a prototype, not a service, and ECMWF is candid about where it still drifts. That candor is the standard other AI forecasters should copy.
A machine learning method called probabilistic bias correction, which learns a forecast model's systematic errors from its own past forecasts and corrects…
Our take Two to six weeks out is when farmers plan planting and water managers set allocations, and it has been forecasting's blind spot. This gain is measured, not promised. Whether it reaches farmers depends on the forecasters testing it in Kenya, not the lab that built it.
A study published Oct. 14 in Nature ran a year-long, single-blind test of space-based methane detection: 481 metered methane releases in Arizona and 265…
Our take This is what honest evaluation looks like: blind, a year long, and willing to report where AI fails. Satellites can catch methane leaks that matter for the climate. An AI alarm that cries wolf costs regulators and operators trust, so AI methods should be held to this kind of test before anyone acts on their alerts.
University of Michigan-led researchers used the large language models Claude and ChatGPT to find and classify interactions between species described in…
Our take This is AI in a supporting role: reading what nature watchers already wrote down so ecologists can see how living communities are shifting. The credit belongs to the people who took the notes and the researchers who checked the machine's work, and it's the kind of AI use worth more of.
An audit posted to arXiv by Subigya Nepal, Ruth Heo, Emma M Parrish and Colin A Depp ran 2,550 scripted multi-turn conversations with AI chatbots in…
Our take Passing the first-reply test is not the same as staying with someone in crisis. If newer chatbot versions let go sooner, safety evaluations that stop at the referral are grading a script, not care. Labs should be tested on what happens after the user says no.
A study published Oct. 2 by AlgorithmWatch, the Umweltinstitut München and the Fraunhofer Institute for Systems and Innovation Research projects that…
Our take Efficiency rules are the cheapest power plant Germany has. Loosening them mid-boom trades a lighter compliance load for more gas burned and higher bills passed down the line. And per-site disclosure is the point: a sector can't be held to numbers it is allowed to hide.
The Center for Democracy & Technology published a report Oct. 15 on how Anthropic, Google, Meta, Midjourney, OpenAI, Stability AI and xAI address…
Our take A safeguard nobody tests is a promise, not a protection. The cost of that gap falls on people whose faces end up in someone else's prompt. A shared testing standard, as CDT urges, should come before the next model ships, not after the next victim.
When weighing climate policy trade-offs, large language models were on average 7.5 times more likely to recommend staying the course than doing something…
Our take Advice that defaults to what people already do is not neutral when what people already do runs on fossil fuel. A tool people ask what to buy, cook and fund could quietly slow the change the climate needs. Developers can fix a default; they have to decide it is worth fixing.
University of Texas at Austin researchers modeled the cost and energy trade-offs of desalinating saline water, from brackish groundwater to oil and gas…
Our take Freshwater is the resource communities can't replace. If data centers can cool on water nobody drinks, the question for regulators shifts from whether they can to why they don't. A model is not a mandate, but it does remove an excuse.