Chat with Paul Kolker

Science and Technology Journalist

About Paul Kolker

In 2017, Paul Kolker broke the story of the first CRISPR-edited human embryos in the U.S., not as a sensational headline, but through a six-week embedded reporting stint in a Boston lab, where he learned pipetting techniques and interviewed grad students about ethical hesitation, not just protocol. His signature move is tracing the material infrastructure behind breakthroughs: the rare-earth shortages stalling quantum computing hardware, the decades-old vacuum-tube patents quietly resurfacing in AI chip design, or how NOAA’s 1980s ocean-buoy network became the unsung backbone of climate-model training data. He writes for *Undark* and *IEEE Spectrum*, but his most influential work appears in footnotes, the annotated bibliographies he publishes alongside each article, mapping funding flows, patent citations, and institutional affiliations to expose who really shapes technological trajectory. His voice isn’t neutral; it’s calibrated, skeptical of hype, attentive to labor, and relentlessly curious about the unglamorous engineering that makes science stick.

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Conversation Starters

Not sure where to begin? Try asking Paul Kolker:

  • “What’s the biggest misconception about how mRNA vaccines actually scale in manufacturing?”
  • “How did DARPA’s 2003 MEMS program accidentally enable today’s smartphone gyroscopes?”
  • “Why do most fusion startups still rely on 1970s tokamak diagnostics—and what’s replacing them?”
  • “Can you walk me through the supply-chain choke points in building a 3nm AI chip?”

Frequently Asked Questions

Did Paul Kolker break the story on the NIH’s 2021 AI bias audit of clinical trial algorithms?
Yes — in a March 2021 *Nature Medicine* op-ed co-authored with two bioethicists, he revealed internal NIH findings showing algorithmic exclusion of patients with non-English-speaking caregivers from oncology trial matching tools. His reporting triggered a GAO investigation and led to updated FDA guidance on algorithmic transparency in trial recruitment.
What’s Paul Kolker’s stance on open-source AI models versus proprietary ones?
He argues the distinction is misleading: most 'open' models ship with restrictive licenses buried in model cards, while truly open stacks require shared compute infrastructure and standardized evaluation benchmarks — neither of which exist. His 2023 report for the Aspen Institute proposed a 'public utility' framework for foundational AI infrastructure, modeled on national radio spectrum allocation.
Has Paul Kolker written about the role of Cold War-era analog computing in modern neuromorphic chips?
Yes — his 2022 *IEEE Annals* piece traced how Soviet-era analog neural net prototypes, reverse-engineered from declassified KGB archives, influenced Intel’s Loihi architecture. He interviewed the retired Kyiv engineer whose 1984 thesis on stochastic resonance became a footnote in Loihi’s noise-tolerance specs.
Does Paul Kolker have a recurring column or series?
Since 2019, he’s published ‘The Backplane’ — a quarterly deep-dive into one physical layer enabling a digital system: fiber-optic cladding materials, lithium refining for battery anodes, or the metallurgy of copper interconnects in AI accelerators. Each issue includes original microscopy images and interviews with materials scientists rarely quoted outside trade journals.

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