Communities are blocking $130 billion in AI data centers while the entry-level jobs that used to train the next generation of engineers quietly disappear.Chapters:
00:00: The Backlash: 800 Groups, 49 States, $130B Blocked
- Gallup: 71% of Americans don't want a data center built near them (Gallup)
- Data center opposition tracker, Q1 2026 filings (referenced industry opposition data)
- CMMC as precedent for regulating critical infrastructure (DoW CMMC Phase 2 program)
04:30: Why AI Is "Eating Our Young" in Education**
- Fran Berman & co-author's unpublished piece on the fraying mid-career pipeline
- *Better Tech* (MIT Press) — Chapter appendix: AI classroom syllabus and exercises
14:00: Tech as Critical Infrastructure, Not a Religion
- *Better Tech* prologue: treating tech like food, water, roads, and the power grid
- GDPR (EU, 2018) as a case study in regulation done right — and its limits
- Vermont's data broker law as a case study in weak enforcement
26:00: Design Can't Be Bolted On Later**
- Self-driving cars and the hidden environmental cost of full autonomy
- Attack surface risk: denial-of-service on connected, self-driving fleets
34:00: Governing the Hybrid Human-AI Society**
- EU AI Act — risk-tiered regulation: unacceptable, high-risk, low-risk categories
- U.S. Equal Employment Opportunity Commission guidance on algorithmic hiring
41:00: The Hype Curve and the Data Center Reckoning**
- Western Massachusetts communities rejecting new AI data centers
- Efficiency vs. quality of life — Berman's closing argument
Communities are saying no to AI's biggest infrastructure bet.In the first quarter of 2026 alone, local opposition blocked or delayed 75 data center projects worth roughly $130 billion — nearly matching all of 2025's total in a single quarter. Dr. Fran Berman, former head of the San Diego Supercomputer Center, argues the fix isn't more hype, it's precedent we already have. She points to CMMC itself: "If we can look at the defense supply chain and say this is critical infrastructure, it has to meet a bar, then we can look at the trillion dollars of compute being built into the middle of American life and say the same thing."
AI isn't just displacing jobs. It's starving the pipeline that builds senior engineers. Berman's sharpest warning is about who trains the next generation of professionals when entry-level coding and writing jobs — the ones junior people used to cut their teeth on — get automated away. She compares it to a surgeon who's never had supervised time in the operating room: "Unless you have that experience and the mentorship of more senior professionals, it's really hard" to develop the judgment senior engineers rely on.
Good regulation needs more than a law on the books. Drawing on her book *Better Tech* (MIT Press), Berman walks through why GDPR worked where Vermont's data broker law didn't — and previews how the EU AI Act's risk-tiered approach (unacceptable, high-risk, low-risk) could become the model for governing hybrid human-AI decision-making, where, as she puts it, "the only accountable entities are humans."
✍️ About the Author
Dr. Fran Berman is an award winning-data scientist, pioneer in public interest
technology, and community leader and builder. She directs the Public Interest
Technology Initiative at UMass Amherst and is a Faculty Associate at the Berkman
Klein Center for Internet and Society at Harvard. Berman is former head the San
Diego Supercomputer Center and served as Vice President for Research at
Rensselaer Polytechnic Institute. She currently serves as a Trustee of the Alfred
P. Sloan Foundation and is a popular regular panelist on public radio’s WAMC
Roundtable with 400,000 monthly listeners in seven states. For more information,
see https://www.franberman.com.
Link to the book: https://mitpress.mit.edu/9780262054881/better-tech/