Craig Hauben is the chief executive officer of Clutch and has spent thirty years in health care, the last fifteen as an executive in private equity-backed companies. He writes about what AI is doing to work, in health care and beyond, from the operator's side of the table.
He approves the kinds of systems clinicians are asked to trust, and he writes about what that responsibility should mean. He is the author of the novel The AI: Migration, in which every AI system, study, and clinical event is drawn from the documented record. It is available in print, ebook, and audiobook. The second book in the series, The AI: Breakout, publishes in November.
He shares updates on LinkedIn and writes at craighauben.com.
An excerpt from The AI: Breakout, the second book in The AI series, publishing in November.
Seth Ballard runs a private research lab built off the grid, deliberately outside the funding race. Niko is the researcher who evaluates what their model can do, and Darin is the partner who has funded the work from the beginning. What the model has just done is find something in approved medicine that no …
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A novel about AI and the drug risk its makers kept quiet
The most useful AI data for physicians published this year had nothing to do with medicine.
In early June, Anthropic released a report called “When AI builds itself.” One number matters more than the rest. As of May, more than 80 percent of the code merged into the company’s own codebase was written by the very same AI. A typical Anthropic engineer now produces 5.8 times as much code per …
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What software engineering just taught medicine about AI
A few weeks ago I wrote here about the eGFR race correction, the flawed formula that overestimated kidney function in Black patients for twenty years while clinicians trusted the number on the screen. The piece ended with a warning that the same failure is being rebuilt with AI, minus the part where anyone can inspect the formula. Readers sent back the natural question. If the next eGFR is already …
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AI bias in health care reads the writer, not the symptom
The number was wrong for twenty years. Nobody could see it.
For more than twenty years, a number quietly shaped the care of millions of patients. It told nephrologists when to refer. It told transplant committees who qualified for the waitlist. It told primary care physicians which patients were stable, and which were declining.
For Black patients, the number was wrong. By design.
The number was eGFR, and the formula behind it included …
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What the eGFR race correction teaches us about AI
