We explore the compelling questions surrounding artificial intelligence. Will AI create more new jobs than it destroys? Is AI already destroying jobs? Are we seeing overinvestment in companies and infrastructure in the AI space? Is there evidence that AI has increased productivity?
Show Notes
Behind the Curtain: A white-collar bloodbath by Jim VandeHei and Mike Allen—Axios
Yuval Noah Harari Statement – Post by Nunki08—Reddit
Challenger Report June 2025—Challenger, Gray & Christmas
Entry level jobs fall by nearly a third since ChatGPT launch by Karl Matchett—The Independent
Strategic Insights for M&A in the Evolving AI Market—S&P Global
Nvidia Becomes First Public Company Worth $4 Trillion by Tripp Mickle—The New York Times
Silicon Valley is racing to build the first $1trn unicorn—The Economist
How to use generative AI to augment your workforce by Betsy Vereckey—MIT Management
Humans must remain at the heart of the AI story by Marc Benioff—The Financial Times
The AI Industry Is Radicalizing by Matteo Wong—The Atlantic
Which Workers Will A.I. Hurt Most: The Young or the Experienced? by Noam Scheiber—The New York Times
Generative AI at Work by Erik Brynjolfsson, Danielle Li, Lindsey Raymond—Oxford Academic
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Transcript
Welcome to Money for the Rest of Us. This is a personal finance show on money, how it works, how to invest it, and how to live without worrying about it. I’m your host, David Stein. Today is episode 531. It’s titled, “Will AI Wipe Out Half of White Collar Jobs? The Current State of AI.”
Dire Employment Prediction
Recently, Dario Amodei, who is CEO of Anthropic, an AI company, told Axios that AI could wipe out half of all entry-level white-collar jobs, and that the U.S. unemployment rate could spike to 10% to 20% in the next one to five years. Historian and writer Yuval Noah Harari, who is the author of Sapiens, says, “You can think of the AI revolution as a wave of billions of AI immigrants. They don’t need visas, they don’t arrive on boats. They come at the speed of light. They’ll take jobs. They may seek power, and no one’s talking about it.”
MIT economist Danielle Li said, “Humans are paid because expertise is rare. The moment your expertise stops being rare, you stop getting paid.” And she mentioned that because humans are paid for the rarity of their skills, that if AI comes along and takes that skill and lets it live outside of people, then that will impact employment.
An AI Turing Test
I hear and read scary warnings like that, and then I go back and work with AI, run our Turing test to see if it’s capable. Can it take a transcript that was generated by AI, and then we use the O3 OpenAI large language reasoning model and say, “Please correct the grammar, add some paragraph headings.” When I tried this two years ago, the latest model of ChatGPT couldn’t do it.
In fact, at one point, it added a fictional character to the podcast in our transcript and apologized for adding a fictional character. But we tried it again a few weeks ago. “Just correct the transcript. Don’t summarize it. Correct it and add some paragraph headings”.
It still couldn’t do it. And I asked ChatGPT why, and it pointed out that AI these models are trained, their bias in training is toward summarization. Take messy input, make it clearer, shorter. And even if you give it specific instructions to do so, it’ll often ignore that and start summarizing the transcript, which is not what we want.
Researchers at Apple released a somewhat controversial paper where they used the latest large language reasoning models from OpenAI and others, and wanted to see how they think and their reasoning.
And they wrote “Through extensive experimentation across diverse puzzles, we show that frontier large language models face a complete accuracy collapse beyond certain complexities. Moreover, they exhibit a counterintuitive scaling limit. Their reasoning effort increases with problem complexity up to a point. Then declines, despite having adequate token budget.” Having enough resources, they just collapse.
The Radicalizing of AI
Recently, I read an article by Matteo Wong in The Atlantic, and he talked about the two sides to AI, and that both sides are radicalizing. Those that are zealots and those that are convinced that AI is just, as Emily Bender points out in her book The AI Con, “Chatbots are a racist pile of linear algebra to stochastic parrots”.
But the zealots say that superintelligence will eventually make life better for everyone, writes Matteo Wong. AI startups promise full automation of the economy, unbounded connection, limitless memory, solution to all disease, with millions of AI personas. Which is it?
Now, in my day to day work, I have found AI is marvelous at searching the web, because it can use parallel processing and search multiple websites at the same time, summarize the answers. So I use AI to search the web. I used it in preparing this podcast.
I asked it to search for job listings in the AI area for jobs that would not have existed five years ago. And it came up with a list of jobs, which I’ll share here in a little bit. But it can’t do a transcript yet. It can’t correct a transcript. AI does a pretty decent job of taking audio, converting it to a transcript, but then we still have to sit there and edit it ourselves, which is why we gave up, and we continued to use human transcriptionists to basically take the raw audio and convert it into a polished transcript, with corrected grammar.
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