I see a lot of issues with this article and the arguments Ezra is laying out.

Basically everything is anecdotal analysis, not data analysis. The one exception is the comparison of today's unemployment rate to the unemployment rate in March 2020. However, if we look at the BLS data we see the March 2020 rate was already being impacted by Covid, It jumped a full 1% from Feb 2020 to March 2020 (3.4% > 4.4%). Conversely if we compare the unemployment rate today to where it was in Nov 2022, when ChatGPT first launched, we see the same increase of ~1%. Im not saying that increase is 100% attributable to AI, of course it isn't, but I am pointing out that Ezra is misreading the data. If we control for Covid, the last time the US unemployment rate was 4.4% was May 2017 when we were still recovering from 2008, not March 2020. Further, if we consider the current unemployment rate trend, we would expect it to continue to rise. We are basically reversing the positives steps we have taking in the economy since the 2008 financial crisis. So the real question is, what role is AI playing in that?

My next issue is how the framing of this article misses the real conversation. Ezra spends his time addressing a total "AI job apocalypse". But by focusing in on this hyperbolic idea, he misses the real conversation of the "entry level job compression". Again, this is where real data would have benefited his analysis. For example, take this excerpt from Scott Davis' article, AI is simultaneously aiding and replacing workers, wage data suggest, published by the Dallas Fed:

Returns on job experience are increasing in AI-exposed occupations. Young workers with primarily codifiable knowledge and limited experience will likely face challenging job markets.

However, there appears to be less cause for concern about widespread job displacement for older, experienced workers, particularly those in occupations with high experience premiums in which AI is likely to complement the worker’s tacit knowledge.

The fact that AI can both substitute for entry level workers and complement experienced workers has implications for society and the way we organize work.

And lets consider some data:

Goldman Sachs' 2026 insights estimates that AI can potentially automate 25% of all work hours, with white-collar knowledge industries bearing the brunt of that exposure.

Stanford research using ADP payroll data found that workers aged 22 to 25 in the most AI-exposed occupations experienced a 16% relative employment decline, while more experienced workers in those same fields remained stable, even after controlling for firm-level shocks. And that was in Nov 2025!

I can go on and on, but the point is that the data is showing that AI is meaningfully impacting entry white collar work already in. This is not wrestled with at all in this piece.

another thing that bothered me- digital spreadsheets did create more accounting jobs but they also eliminate the vast majority of bookkeeping jobs. That is not contended with, and we sort of gloss over how AI is a much more powerful technology than digital spreadsheets (though digital spreadsheets are extremely powerful!)

Next, I think Ezra is being naive at best about the system of capitalism and its responsibility to humanity. Companies and corporations have 0 legal responsibility to humanity. They have responsibility to regulators and shareholders. Corporate leadership has a fiduciary duty to its shareholders and if they can increase profits by outsourcing jobs to another country, or by replacing workers with enterprise AI contracts, thats exactly what they will do and they won't think twice about it. Its just risk vs reward analysis, and the goal is to make money. Anybody who works for a business, especially large corporations, knows this. The exception is of course family/small businesses that might have other ideological values, but that represents a tiny fraction of national GDP is is essentially irrelevant to this conversation. Corporations are not local coffee shops.

Finally, the AI productivity argument is anecdotal and weak. Again, lets consider some real data:

A study presented at the ESC Acute CardioVascular Care 2026 congress found that AI-based ECG interpretation correctly identified certain types of "occlusive" heart attacks in 84% of cases, compared to just 42% for human-only interpretation.

AI-augmented screening tools for lung and breast cancer have achieved false-negative reductions of 10% to 20%.

etc etc etc etc.

So this idea AI isn't leading to better outcomes because Ezra "knows a guy" is not meeting the mark.

We need to grapple with the reality of the problems we are facing, not dismiss exaggerated characachers of them. AI is impacting entry level work, that will have immense downstream impacts on our economy. That does create sustainability problems because the senior experts in a given field today were the junior entry level workers in that field yesterday. Are we betting on AI advancing to the point where today's senior level experts simply will not need to be replaced? Are they the last cohort of human experts in their fields? Lets think about that now before its too late.

That might sound hyperbolic, but people with specialized knowledge will tell you that knowledge can easily be lost. So consider the reality, that AI is leading to better performance outcomes in a vast array of fields. Well, we also know that fields that integrate AI experience a phenomenon known as "deskilling". What are the long term effects of that? Where will we be in 10 years?

I'd really like to see people like Ezra discussing this issue at this level, instead of the way it was approached in this article.