A grieving family in the US faced a $195,000 hospital bill.
Unable to make sense of it, they turned to an AI chatbot called Claude (built by Anthropic) for help. The AI highlighted duplicate charges, inconsistent medical codes, and services that shouldn’t have been billed together. With those findings, the family negotiated the bill down to $33,000.
It’s a remarkable story, but the real point isn’t that AI “saved the day”. It’s that the AI applied the rules it had been trained on, doing the repetitive and tedious work, and highlighted what was inconsistent or might otherwise go unnoticed. It didn’t feel empathy or understand fairness, it simply brought attention to what humans often miss in opaque systems.
This is very similar to how AI works in software development. AI tools don’t replace human judgment. They simply apply the rules they’ve been trained on, doing the repetitive and tedious work, surfacing patterns and inconsistencies that might otherwise be overlooked. For now, humans still (or should, anyway) guide, validate, and decide what goes into production.
Of course, this is one family’s account. We don’t know the hospital’s side or how much human verification was involved. But it illustrates a larger pattern: AI can help people question systems rather than just comply with them. It can empower ordinary users to navigate complexity more effectively.
Sometimes pairing with machines isn’t about creativity or productivity. Sometimes it’s about clarity and a quiet form of fairness.
And if this can help with hospital bills, maybe it’s time to get it to review all the privacy clauses I’m forced to sign, too.
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