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Call for field testers: shared human-AI work receipts #2

Description

@HarperZ9

Project Telos is looking for field testers for telos: a shared perceive-and-make surface where a person and model can inspect the same artifact and produce a re-checkable certificate.

The question this repo should help answer:

Can human-AI work produce a visible receipt trail that is useful in real domains, not only in demos?

Useful test lanes:

  • Doctor/admin: summarize and check public policy or guidance material. Do not use private patient data.
  • Artist/studio: track transforms, exports, gallery artifacts, and human-vs-automatic decisions.
  • Media/newsroom: separate supported claims, source links, assumptions, and unverifiable claims.
  • Token economy/routing: record which tool/service was chosen, why, what it cost, and what receipt came back.
  • Reasoning workflows: compare a model's explanation against shared witnessed state.

What I am looking for:

  • Verification and testing against real public workflows.
  • Clear examples where the receipt trail helps a human make a safer decision.
  • Cases where the UI/report hides too much, exposes too much, or labels uncertainty poorly.
  • Early traction from doctors/admins, artists, journalists, engineers, researchers, and builders who need checkable AI-assisted work.
  • Pointers to modest grassroots research funding or labs that would stress-test this properly.

Project links:

Stage label: public, solo, early, pre-revenue, not independently audited. Please test with public, synthetic, or non-sensitive material first.

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