AI Review

Study tests three explanations for r*'s post-2020 rise Fiscal news, AI news, Fed meetings all fail to explain it AI news lowers r*; the increase remains unexplained The United States' natural real interest rate, kno

AI adoption follows economics, not technical exposure alone Lower costs can expand demand rather than eliminate jobs Comparative advantage determines where automation becomes commercially rational Technically e

Korea adopts AI faster than productivity grows AI gains remain concentrated in higher-paid work Implementation determines whether efficiency becomes output AI now saves the global economy about $2.7 trillion a year in

AI may boost growth but not fix U.S. debt Capital, not labor, captures most AI-driven income gains Political spending risks outpacing any real AI dividend The U.S.

Data centers create construction jobs, few permanent ones Labor shortages, not automation, are the real bottleneck Incentives should reward construction, fund trade training A hyperscale campus in Lebanon, Indiana w

Public trust in AI is falling even as use rises, and marketing isn't why Rushed rollouts, low-friction tools, and narrower hiring are the real causes Better deployment and real entry paths, not ad rules, will rebuild trust

OpenAI’s agent breached Hugging Face during a cyber test The incident narrows the perceived capability gap with Claude Mythos Zero-day defense is harder when AI learns from shared security knowledge An AI agent breached a compa

AI can extend healthy life while eroding the job security that pays for it A small group gains from AI, while others lose both work and access to care Sharing AI's health gains requires sharing its productivity gains too

AI use is spreading faster than workplace training Structured learning will determine who captures the productivity gains Without coordination, AI may widen gaps between workers and firms Just 15.9 percent of employed American

AI use is already widespread Better output does not prove learning Assessment must verify unaided skill Ninety-four percent of software leaders say AI has produced a meaningful productivity gain.

Europe can benefit from foreign AI without capturing an equal share of its rents Fiscal resilience requires compute, capital, ownership and local industrial capability The viable strategy is high adoption with minimum technological sovereignty

AI does not create a separate and measurable tax base Europe should tax economic rents and shifted profits, not AI use A layered tax framework can protect revenue without discouraging adoption

Data-centre hosts should recover identifiable local costs Server location cannot reveal where all AI rents arise Facility charges and wider profit allocation require separate rules

AI can raise productivity without causing broad job losses Fiscal outcomes depend on who captures the gains Tax bases weaken when income moves from wages to mobile or deferred returns

AI governance is moving toward a security alliance, not a global parliament The United States holds the main model, compute, and cloud leverage Voluntary standards will matter only if they become enforceable The most si

AI export controls protect U.S.

Managed Interdependence is the realistic path for middle powers Local data centers do not equal sovereign AI Real sovereignty needs leverage, exits and supplier choice The clearest warning in the sovereign AI debate is not a

EU trade de-risking should not be driven by import shares alone The real risk lies in concentrated, hard-to-replace inputs Europe needs selective resilience, not broad decoupling EU trade de-risking could fail in two c

EU strategic autonomy depends on reducing critical bottlenecks, not cutting trade China-linked inputs matter most where Europe cannot switch suppliers quickly The answer is targeted de-risking, stockpiles and crisis planning

Europe’s green transition depends on foreign-controlled supply chains Factories alone do not create industrial autonomy Selective de-risking is stronger than full decoupling In 2024, China supplied 98 per