AI is already prompting dramatic predictions about jobs and big policy proposals in response. But we still know remarkably little about what AI is actually doing to the economy. The reason isn’t that the data has been lost or hidden. It’s that much of the data we would need isn’t being collected.
Dr Erica Groshen, former Commissioner of the Bureau of Labor Statistics, joins me to explain why. She recently helped lead a group, under the auspices of the American Statistical Association, that produced 30 recommendations for modernizing the U.S. federal statistical system. The U.S. has no single national statistics agency. Instead it relies on 13 principal agencies spread across the government. These agencies depend on surveys at a time when survey response rates have been falling for decades. Legal barriers prevent them from sharing data even with one another.
That gap matters right now. Erica’s team counted 1,010 studies on AI and the labor market posted in 2026 alone, and their results vary widely. To measure AI’s real impact, you need to know which firms are adopting it and what happens to the workers inside those firms. Our current system can’t connect the two. Erica explains what would fix that: enhanced employer wage records, standardized data, and agencies that can share and adapt.
We also cover:
Why the CPI is a blended data product, and how “owner’s equivalent rent” actually works
How the BLS uses private price data, and what went wrong when a vendor raised its price fivefold
Whether the recent surge in new business formation shows up in the jobs numbers
Why productivity gains from AI are hard to capture
Whether the statistical agencies should be consolidated, and why the group held back
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See “The Nation’s Data at Risk: Meeting America’s Information Needs for the 21st Century” report here:
https://www.amstat.org/policy-and-adv...
0:00 Highlight & Introduction
0:56 Are we measuring what AI is doing to the economy?
1:54 Why falling survey response rates matter
4:20 13 agencies, no national statistics office
5:47 When two agencies measure the same thing differently
8:23 Privacy, misinformation, and public trust
9:44 What records can replace surveys
10:47 The legal barriers to sharing data
13:51 Interoperability and adaptability
17:27 The case for multi-year budgets
19:29 Why not restructure the whole system?
21:03 What most people misunderstand about the CPI
23:22 How the CPI measures housing: owner’s equivalent rent
26:58 Using private-sector price data
29:43 1,010 studies on AI and jobs, and conflicting results
31:52 The fix: enhanced employer wage records
34:27 The surge in new businesses and self-employment
36:55 Can we measure AI’s productivity gains?
38:15 The one thing to fix first
39:13 Tracking how tasks change on the job
42:23 Gig work and the limits of job classifications
43:44 Getting the recommendations adopted
