activescott's Notes

The year is 2026. The unemployment rate just printed 4.28%, AI capex is 2% of GDP (650bn), AI adjacent commodities are up 65% since Jan-23 and approximately 2,800 data centers are planned for construction in the US*. In spite of the current displacement narrative – job postings for software engineers are rising rapidly, up 11% YoY.

Indeed Job Postings: Software Engineers + Overall Postings, Daily and 21dma

The more important question insofar as it relates to the AI displacement narrative is: how intensely is AI being used for work? We can tease out the answer from a subset of the St Louis Fed data that buckets by frequency of AI use. We would posit that if AI represents imminent displacement risk, the real time population data would show an inflection upwards in the daily use of AI for work. The data seems unexpectedly stable and presents little evidence of any imminent displacement risk (solid lines at the bottom of the chart).

Displacing white collar work would require orders of magnitude more compute intensity than the current level utilization. If automation expands rapidly, demand for compute definitionally rises, pushing up its marginal cost. If the marginal cost of compute rises above the marginal cost of human labor for certain tasks, substitution will not occur, creating a natural economic boundary. This dynamic contrasts sharply with narratives assuming frictionless replication of intelligence. Even if algorithms improve recursively, economic deployment remains bounded by physical capital, energy availability, regulatory approvals, and organizational change.

For AI to generate a sustained macro contraction one must assume that labor income falls and no compensating rise occurs in investment, fiscal transfers, or external demand. The surge in new business formation is an interesting point of reference here.

In a part of the opinion joined by Justice Neil Gorsuch and Justice Amy Coney Barrett, Roberts said that Trump’s reliance on IEEPA to impose the tariffs violated the “major questions” doctrine – the idea that if Congress wants to delegate the power to make decisions of vast economic or political significance, it must do so clearly. In 2023, the court relied on the “major questions” doctrine to strike down the Biden administration’s student-loan forgiveness program. In that case and others like it, Roberts observed, it might have been possible to read the federal law at issue to give the executive branch the power it claimed. But “context” – such as the constitutional division of power among the three branches of government – and “common sense” “suggested Congress would not have delegated ‘highly consequential power’ through ambiguous language.”

In cases like this one, Roberts continued, in which the Trump administration contends that Congress has delegated to it “the core congressional power of the purse,” considerations like context and common sense “apply with particular force.” “[I]f Congress were to relinquish that weapon to another branch, a ‘reasonable interpreter’ would expect it to do so ‘clearly.’” And indeed, Roberts said, “[w]hen Congress has delegated its tariff powers, it has done so in explicit terms, and subject to strict limits,” a test that Trump’s tariffs failed here.

The bipartisan war powers resolution, sponsored by Reps. Ro Khanna (D-Calif.) and Thomas Massie (R-Ky.), aims to reassert Congress’s authority to wage war by requiring Trump to win congressional approval before launching any strikes against Iran.

But Massie, so far, is the only House Republican to say he’s supporting the resolution. And a small handful of Democrats — all of them close allies of Israel — are already lining up to oppose it. The combination sets the stage for the measure to fail in the Republican-controlled House, which would give Trump what amounts to a tacit authorization to conduct unilateral strikes as the president and other top officials signal that such an attack could be imminent.

Khanna, Massie and other supporters of the check on executive war powers maintain that they’re merely firming up the use-of-force authorities delineated by the Constitution, which explicitly grants Congress the power “to declare war.”

Last summer, after Trump launched strikes against Iranian nuclear facilities, Senate Republicans blocked a bipartisan resolution limiting Trump’s use of force in that country.

Over the last three months, the lower chamber has voted on three separate war powers resolutions — two related to military actions in Venezuela, and the third governing the Pentagon’s strikes on alleged drug traffickers in the Caribbean region. All resolutions were defeated by Trump’s GOP allies.

“We were told that the nuclear program in Iran had been completely and totally obliterated. Not my words, Donald Trump’s words. And so now we’re to believe that there’s an exigent circumstance where Donald Trump may need to strike militarily in order to prevent Iran presumably from achieving its nuclear ambitions,” Jeffries said Tuesday.

The danger here isn’t just about one contract; it’s about the precedent. If the Pentagon successfully bullies Anthropic into submission or replaces it with a more “flexible” competitor, we are effectively witnessing the birth of an intentionally unethical AI.

The Death of Human Agency When AI is integrated into weaponry for “all lawful purposes” without restrictions on autonomy, we invite the Responsibility Gap. If an AI-driven drone swarm misidentifies a target, who is at fault? By removing the “human-in-the-loop” requirement, the military is seeking a weapon that offers the ultimate prize of war: lethality without accountability. Surveillance as a Service Existing U.S. laws were written for wiretaps, not for generative AI that can ingest millions of data points to build predictive profiles. Under an “all lawful purposes” mandate, an LLM could be turned into a digital Panopticon. Anthropic has warned that current laws have not caught up to what AI can do in terms of analyzing open-source intelligence on citizens. The Moral Race to the Bottom If the Pentagon blacklists Anthropic, it sends a clear message to competitors: Safety is a liability. To win government billions, firms will be incentivized to strip away safety layers. Reports already suggest OpenAI, Google, and xAI have shown more “flexibility” regarding the Pentagon’s demands.

The Pentagon’s “supply chain threat” maneuver is a scorched-earth tactic designed to force Silicon Valley to choose between its values and its bottom line.

If Anthropic stands firm, it may lose $200 million in revenue and a seat at the defense table. But if they cave, they may well be providing the operating system for the very “Terminator” future they were founded to prevent. In the world of 2026, the most dangerous threat to the supply chain might just be an AI that has been ordered to stop caring about ethics.

date formatting in ICU - International Components for Unicode

It will significantly increase my opinion of @Anthropic if they do not back down, and honorably eat the consequences.

(For those who are not aware, so far they have been maintaining the two red lines of "no fully autonomous weapons" and "no mass surveillance of Americans". Actually a very conservative and limited posture, it's not even anti-military.

IMO fully autonomous weapons and mass privacy violation are two things we all want less of, so in my ideal world anyone working on those things gets access to the same open-weights LLMs as everyone else, and exactly nothing on top of that. Of course we won't get anywhere close to that world, but if we get even 10% closer to that world that's good, and if we get 10% further that's bad)

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After the call, the Semiconductor Industry Association hired McKinsey to take a look. They started with a basic question: What would happen if companies couldn’t get chips from the island?

A summary of the resulting report opened with a map of Taiwan detailing how integral the island is to the global economy. Taiwan enabled roughly $10 trillion of the world’s gross domestic product. It made chips for iPhones and more than half of so-called memory chips for cars, and it led in assembling A.I. chips.

The island’s semiconductor manufacturing is mainly in Hsinchu, an area where Taiwan’s government discouraged manufacturing after World War II because it is next to the sloping beaches that are the best place for an amphibious assault against the island.

If Taiwan’s factories were knocked offline, the impact would be immediate, the roughly 20-page report said. Economies would flounder. In China, the gross national product would fall by $2.8 trillion; in the United States, the drop would be $2.5 trillion.

Other reports, including one by Bloomberg Economics, a research service, estimate a conflict would cost the global economy more than $10 trillion.

The first part was easy. TSMC committed more than $50 billion to building a second and third plant in Arizona, two years after announcing its first facility during Mr. Trump’s first term. Intel promised to expand in Arizona and invest as much as $100 billion in an Ohio campus. Samsung pledged $45 billion for two factories in Taylor, Texas.

Customers were reluctant to buy chips that cost more than 25 percent more and were a generation behind those made in Taiwan, where the government has an unofficial rule requiring TSMC to put its most cutting-edge technology on the island first.

Intel and Samsung, despite their pledges to expand production, didn’t have any commitments. Their technology had fallen behind TSMC’s, and the industry doubted they could catch up.

Mr. Trump met with Mr. Tan days later and suggested that Intel give the United States 10 percent of Intel’s business. The chief executive agreed to the unorthodox request, even though some argued it was on shaky legal ground. Intel gave the government equity in exchange for the $8.9 billion it had been promised from the CHIPS Act.

The deal helped Intel secure its federal subsidies, without having to meet financial benchmarks to qualify for the money.

He told top chip executives, who had gathered for a Semiconductor Industry Association meeting, that the administration wanted them to buy 50 percent of their semiconductors from American plants, four people who attended said. Companies that didn’t would pay a 100 percent tariff.

Total effective tax rates (includes all taxes: federal+state income tax, sales tax, property tax, etc) for the richest Americans declined by 2018 to a level beneath that of the bottom 50% of earners,[18] contributing to wealth inequality. Analysis by economists Emmanuel Saez and Gabriel Zucman.

The Federal Insurance Contributions Act (FICA /ˈfaɪkə/) is a United States federal payroll (or employment) tax payable by both employees and employers to fund Social Security and Medicare[1]—federal programs that provide benefits for retirees, people with disabilities, and children of deceased workers.

Since 1990, the employee's share of the Social Security portion of the FICA tax has been 6.2% of gross compensation up to a limit that adjusts with inflation.[a][9] The taxation limit in 2020 was $137,700 of gross compensation, resulting in a maximum Social Security tax for 2020 of $8,537.40.[7] This limit, known as the Social Security Wage Base, goes up each year based on average national wages and, in general, at a faster rate than the Consumer Price Index (CPI-U). The employee's share of the Medicare portion of the tax is 1.45% of wages, with no limit on the amount of wages subject to the Medicare portion of the tax.

So personal income tax in the US is ~30% for most of us (ranging from ~10%-37%), compared to Social Security's ~6.2% Medicare is 1.45% (or 12.4% + 2.9% if you count the employer portion). AND only the first ~$137K is taxable so our maximum tax amount to Social Security and Medicare is capped, while normal income tax that politicians can direct to anything from foreign wars to immigration enforcement to redistribution to different states or interest on debt driven by tax breaks to the rich that caused deficits.

An average of 9,000 refugees were admitted monthly between January 2024 to January 2025. From February to December 2025, there were 1,226 total admissions, 1,059 of whom were from South Africa.

It's quite disappointing that these policies - especially the H1B tax, which brings the best and brightest in the world to the US - all target legal immigrants.

I love this report!

This data-driven, impartial report contains historic metrics — how you use them to advocate for the changes you want to see in the country is up to you.

Most spending was on Social Security, national defense, grants to state and local governments, Medicare, and interest on the debt. Spending and revenue were both higher than their pre-pandemic levels, and the federal government ran another deficit as spending outpaced revenue.

Why do we always lump Social Security in with other national spending? Social Security is collected separately from all other tax revenue and goes directly to the Social Security trust fund. That money cannot be put anywhere else. Politicians can't direct Social Security goes into a trust fund and politicians can't change how it's spent, unlike defense spending and other spending. In my view, Social Security should be separate. It's not the government's money to spend, it's money that is given back to the people directly. So comparing national defense, which the government can choose to change the spending levels, reallocate it to other spending priorities, Social Security cannot be because it's a trust fund.

Public schools took in and spent more funds than ever before. It also had mixed impacts on teachers and students. The number of public-school teachers has increased each year since 2020 while the number of students has decreased or stayed the same. Meanwhile, test scores have fallen.

Well we have to do something about that and be drastic about it. However, I don't see how cutting funding alone - the current Republican priority - will help.

UG Solutions told the FT it had made a “very broad” bid to provide anything from security for trucks to work sites and storage facilities for Trump’s contentious new Board of Peace, which is tasked with overseeing a new governance framework for Gaza.

The company deployed contractors to guard militarised aid sites run by the US and Israel-backed Gaza Humanitarian Foundation, which was shut down last year after five months of operations during the devastating war between Israel and Hamas. Hundreds of starving Palestinian aid seekers were killed by Israeli troops as they travelled through military zones to GHF sites, provoking fierce international condemnation at a time when severe Israeli restrictions on aid triggered a famine in Gaza.

Work on the idea is being led by Liran Tancman, an Israeli tech entrepreneur and former reservist who is now working as an unpaid adviser to Trump’s “Board of Peace”, the US-led body tasked with rebuilding Gaza, according to two people familiar with the matter.

Another person familiar with the talks over introducing a stablecoin — in which transactions are anonymous but traceable — said the idea behind the initiative was to “dry Gaza from cash so Hamas can’t generate any”.

However, other people familiar with the discussions expressed concerns that a stablecoin could potentially also be used to further detach the economies of Gaza and the West Bank, both of which Palestinians seek as part of a future state, particularly if a Gaza-only stablecoin were not under the control of the PMA. “It will be much more difficult [to maintain economic links between Gaza and the West Bank] if they have no means of easy payment between the two, so that Gaza would be almost like a self-contained economy,” said one. “That would be a concern.”

Another potential complication of relying on a stablecoin would be the fact that Gaza suffers from frequent power cuts and Israel has long limited Gazans to using slow 2G network technology. In his comments at the “Board of Peace” last week, Tancman said that Gaza’s 2G network “will be upgraded with free high-speed access to essential services” by July.

Another thing like glean that integrates and sucks in data and answers questions

Prominent economists, including from Morgan Stanley and JPMorgan Chase, calculate that the AI buildup was directly responsible not for 92 percent or 39 percent of gains to the U.S. economy in 2025, but as little as zero.

It’s clear that the huge spending on AI is adding to the U.S. economy, but the available economic data doesn’t neatly capture its effects. The debating economists and the slippery data suggest that if the technology does start to reshape the economy, it may be challenging to detect and clearly measure. That may leave political and corporate leaders to choose the numbers that fit their preferred narratives on how AI is changing American life and work.

That’s because the $31 trillion in yearly U.S. gross domestic product, the widest measure of the economy, tallies only the final value of products and services produced domestically. Spending on imports and foreign made components is subtracted because it boosts the economies of other countries, not that of the United States.

Roughly three-quarters of the cost of an AI data center is for the computer gear and parts such as computer chips that go inside of it, technology analysts estimate. America’s AI champions, including the computer chip pioneer Nvidia, manufacture many of their products in Asia — despite efforts by the Biden and Trump administrations to reduce U.S. dependence on essential chips made overseas.

And some forecasters say that the U.S. government’s economic data is a poor measure of the impact of AI and that alternative calculations show the current boom is an even bigger boost to economic growth.

“This is a big deal, but not the be-all and end-all,” said Joseph Politano, an economic analyst who writes the Apricitas Economics newsletter. He calculates that AI-related spending contributed about 0.2 percentage points to the 2.2 percent U.S. economic growth last year.

The AI buildup is putting real money into the pockets of some Americans and U.S. businesses. Stock market gains from AI enthusiasm are plumping up Americans’ investment portfolios.

“The two engines of today’s economy are the AI ecosystem and wealthy consumers,” Richmond Fed President Tom Barkin said in a January speech.

Prominent economists, including from Morgan Stanley and JPMorgan Chase, calculate that the AI buildup was directly responsible not for 92 percent or 39 percent of gains to the U.S. economy in 2025, but as little as zero.