World Solve — A living repository of problems worth solving.

What World Solve is

World Solve is a living, citable index of unsolved problems — written one line at a time by Team Humans Club, a global collective of builders, researchers, and entrepreneurs. We do not solve the problems here. We Democratize Innovation.

For builders Skip the search for a problem worth your time. Browse a vetted, growing list and start where the gap is real.

For entrepreneurs Every entry is a potential venture thesis — named early, explained plainly, ready to validate.

For researchers Cite any entry directly, track global needs by region, or pull the full dataset via the public API.

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Data-poor regions risk being left out of global health AI advances.

open Global / Unspecified, Global

Algorithms trained on high-income populations may not generalise to under-sampled groups. Inclusive data-collection initiatives and equity-centric model evaluation are necessary.

data poor regions risk being technology-computing

WS02067 · Logged by Ian Patel on 2026-07-22T20:40:00Z · Horizon: 10-20 years · Working on: 0

Citation ID: WS02067 Title: Data-poor regions risk being left out of global health AI advances. URL: https://www.worldsolve.org/index.php?api=problem&id=2067

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2165 public problems
2165 open challenges
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