📢 New @FAO report: 1.7 billion people live in areas where land degradation limits crop yields. We can avoid, reduce and reverse land degradation with targeted policies and strengthened institutions. 🌱 👉 Interactive Story: fao.org/interactive/2025/tac… #SOFA2025 #LandDegradation

It's a thrill when someone reads or cites something you wrote 30 years ago. It's a conversation traversing time. 👇 Thought-provoking essay. In a world where the cost of writing goes to zero, human attention remains limited. How do we adjust to keep the conversation going?

Great read. A reflection on how current AI changes the meaning we attribute to human endeavors, such as math, and what it implies. Provides real insight on navigating the transition we are experiencing. For those of us who feel a bit lost by recent AI developments.

Cowculus.

Hormuz disruption is hitting fertilizer -- and agrifood systems next. Sri Lanka is cut off from suppliers. Egypt’s bread subsidy is under strain. Latin America faces over 7% cereal income losses. Stabilize markets, reroute trade, support farmers and import-dependent nations.

🌍✨ New Paper Out! Learn how to analyze properties of any City-Region in the world with a click of your mouse. openknowledge.fao.org/server… #Econtwitter #Geography #GIS #urban #rural

When AI first arrived on the scene, I worried it would make economists, or even critical thinkers more broadly, less valuable. In my travels in the past 6 months to work with non-profits, for profits, and government agencies, I have observed how people are actually using AI. I have watched them fumble around with insights they clearly did not create themselves. My fears are now assuaged. One observation is that AI can produce something that in some cases is very wrong and in others looks nearly right, but is not quite there. Even if in time AI improves to "nearly right" or "exactly right" every time, a second issue still arises: explaining the materials. Explaining why an answer is almost correct but subtly off requires exactly the critical thinking skills that created the knowledge in the first place. Even explaining "exactly right" material takes critical thinking. I've watched smart people confidently present AI-generated material they clearly don't fully understand. The words sound right. But when someone pushes back just a little bit, the sand castle crumbles. It is quite difficult to defend what you didn't build. This leads me to now make the optimistic case for human expertise. The value of deeply understanding something — of having built the knowledge yourself — hasn't diminished with AI. If anything, it's increased. The people who can tell the difference between "nearly right" and "right" are more valuable than ever. The people who can explain the subtle details about something that is exactly right are invaluable. Creating knowledge still matters. Maybe now more than ever.

Easy, high-return, low-startup-cost use for Claude code: request a replicability audit of all do-files/scripts for a project to note errors and inconsistencies in use of varying data input files, idiosyncratic file paths for inputs and outputs, failure to adhere to replicability best practices, and so much more. It is really, really useful No need to download skills or read anyone's long how-to (though that is useful too, not knocking it!) You can just do it right away

This paper is one of the first to test AI skills and the results seem to suggest that yes, they have high practical value. They use pretty mediocre skills (6.2/12 quality rating) harvested mostly from places like Github, and still get large boosts, especially outside software.

🎯Important to be aware of rapid change in AI capabilities. Affects research questions for some, and research tools for many.

Thrilled to share: OpenScholar - our work on scientific deep research agents for reliable literature synthesis -has been accepted to Nature! 🎉 Huge thanks to collaborators across institutions who made this possible!

Dario is a brilliant technologist, but Demis is the better economist. He must have read @joshgans & @avicgoldfarb o-ring paper on automation.