@Afinetheorem I believe there was a study done in NY comparing electricity use in blocks lined with trees versus those with no trees. AC related use down due to shade, also temps, IIRC
@GergelyOrosz the problem is that internal allocations are done via rationing, not the price system. The net is often a a significant missallocation of resources. I wrote about this here https://t.co/eA3VmPGoTy
One (of many) reasons why public infrastructure is so expensive in the USA is because local authorities lack engineering and procurement expertise. They rely on consultants who exploit the principal-agent problem to their advantage.
In Spain costs are low bc the public sector has experts in its staff.
I think there is a lesson here about optimal delegation to agents....
see https://t.co/KG8usI4qDb
@paulg The question is not whether it is possible so much as wether it is probable, no? I suspect rapid compound growth for years on end is quite rare...
@ojblanchard1@tylercowen I read the piece and to me it reads like an argument for mercantilism (the USA and China are being mercantilist, the EU should follow suit )
https://t.co/2EjV2R6TWb
@lugaricano The report paints a picture of a return to mercantilism. Where all important economic activity has to be done in the metropolis (USA).
My reading of economic history, and economics, is that this would be a very bad policy for the USA, sowing the seed of its own decline.
@lugaricano The report paints a picture of a return to mercantilism. Where all important economic activity has to be done in the metropolis (USA).
My reading of economic history, and economics, is that this would be a very bad policy for the USA, sowing the seed of its own decline.
Great piece highlighting the political roots of macro instability. What is the latest on the dynamics of how economic policy and political equilibria interact?
The Chilean Mirror: What Argentina Sees and Cannot Yet Reach https://t.co/H0ixkMNetK
The FT says that Amazon employees are doing random unnecessary task automations to consume tokens and to show their bosses that they're using AI more https://t.co/wZ204CKi32
@Afinetheorem To me it looks no different than copy paste. The video and voices are good bc they copy almost exactly the style of the training material, but with a different script. The AI has learned to mimic Disney. What are the general equilibrium implications of this?
People make similar arguments about gambling. I am not convinced. I suspect there are a lot of second order effects, social contagion, etc that interfere with the selection effect.
It's like saying a world of sin selects for the virtuous. Maybe. Or maybe the virtuous go down with the sinners. I suspect the model is underspecified...
Would like an RCT comparing these kinds of organizations to more traditional ones. What is impact on software reliability and performance, security, customer adoption and churn, employee retention and satisfaction, revenue and profit. Until then, this is all speculation.
@johnjhorton +1 for using tung oil. Are you using the raw stuff or the stuff mixed with solvents? If the former, how is it holding up to rain, uv etc.? Does it dry well? I'm trying to experiment with less toxic / biodegradable options....
This chart commits the classic base-rate error: it shows P(college | CEO) and pretends that answers P(CEO | college). "No college" can top the list among CEOs and still be a terrible path to becoming one, because the denominator is enormous.
I have a new piece out today on AI Adoption in @HarvardBiz with Antonio Cabrales, José Durán @toniroldanm, and colleagues from @BBVA on why most enterprise AI programs fail and what BBVA did differently.
Most large companies have a shadow AI economy. As of Summer 2025, only 40% of firms had bought official LLM subscriptions, but employees at 90%+ used consumer AI for work on the side. The standard corporate response is to restrict and monitor. The "core IT" department takes over and sees its task as reducing usage. This is the wrong reaction. Shadow AI is not a threat. It is a demand signal telling you that productivity gains exist.
BBVA deployed ChatGPT Enterprise company-wide in a secure cloud, compressing risk assessment, legal review, and GDPR compliance into two months. Their bet was that unmanaged hidden usage is more dangerous than rapid managed deployment.
The rollout leveraged "FOMO" (fear of missing out): only 3,000 initial licenses, allocated competitively with a "use it or lose it" policy. This turned enterprise AI from a mandate into a privilege. Then they built an Adoption Network: Champions, Co-Champions, and 200 Wizards (power users) who provided peer-to-peer support. The Community of Practice became the most active internal forum in BBVA's history.
Within a year, active users grew from 3,000 to 11,000. 83% use it weekly. Employees built 4,800+ custom GPTs. In audit, 99% of 600 auditors worldwide became active users, saving 3-4 hours per week. In Mexico, an insurance-advisory GPT cut query response time by 92% for 4,400 branch managers. These tools were built by frontline employees, not by IT. A human always owns the output. No direct writes to core systems.
If you want enterprise AI to work, stop building centralized plans. Trust the people who already figured out where AI helps. Give them a secure environment, clear rules, and a network to share what they learn.
https://t.co/99szYBlTwv