AI Markets

OpenAI CEO Sam Altman said on Tuesday the rapid development and adoption of AI would not lead to a global “jobs apocalypse” and the technology had not claimed as many white-collar jobs as he had feared. 

Speaking virtually at a Commonwealth Bank of Australia (CBA) conference in Sydney, Altman said he was initially concerned about the impact AI would have on global employment levels. 

A new working paper by Philip Moreira Tomei and Bouke Klein Teeselink, posted to arXiv in early May, makes claims that, if correct, should reorient the workforce policy conversation. In short, the authors argue that the AI exposure indices that have shaped most current thinking are looking at an incomplete subset of digital work. They identify which jobs and tasks current language models can already accelerate but they miss the jobs with features that make them amenable to automation later.

Tomei and Klein Teeselink build a new index that scores all 17,951 task statements in the federal O*NET database. The authors propose a measure what they call “reinforcement learning feasibility” which asks whether a task has the structural features (e.g., verifiable outcomes, use environments amenable to simulation, discrete decision/feedback loops) that allow AI systems to be trained on it through the post-training methods that are becoming the main drivers of AI capability. They then compare their index to the most-cited existing measure, from Eloundou and colleagues, which looks at whether tasks can be automated with current technology.

A new Redfin report found that since the launch of ChatGPT’s first model in Nov. 2022, luxury home prices in the region—classified as those selling between $3.1 and $7.6 million—have jumped 13.4%. At the same time, home values for lower-end properties in the Bay Area—those $535,000 to $615,000—have fallen by 3.8%.

“Some owners of lower-end properties have missed out on the AI boom, with home prices in the most affordable Bay Area zip codes declining over the past two years,” Yingqi Xu, Redfin senior economist, said in a statement. “It’s another sign of the K-shaped economy taking shape in the Bay Area, with AI lifting the fortunes of some households and neighborhoods much more than others.”

Many Americans today are grappling with the sobering reality of high mortgage rates, inflated home prices, and a housing stock shortage. Many are delaying homebuying by a near decade from just a few years ago, as the median age of the first-time homebuyer hit 40 in 2025, up from just 33 in 2021.

The market for Treasury debt is challenging to interpret even when the environment is calm, much less when multiple geopolitical and technological disruptions are present simultaneously. Two papers released in the past year offer differing perspectives on a consequential unknown in the current market, which is the expected effect artificial intelligence (AI) will have on future productivity growth.

The first of the two relevant papers, co-authored by Isaiah Andrews and Maryam Farboodi, examined market signals in 2023 and 2024 around the releases of updated AI models from five leading developers (OpenAI, Anthropic, Google Deepmind, xAI, and DeepSeek). A main finding was that the nominal interest rates for long-term Treasury and corporate debt fell after these models became public by a statistically significant 12 basis points.