A widely-deployed healthcare algorithm once underestimated the severity of symptoms in women of color by more than 25%. It wasn't malice. No one wrote a line of code that said care less about these patients. The system simply learned from data that had never fully seen them — and then made millions of decisions anyway.
That discovery, made by a research team at Northwestern University. Not as a complaint, but as a coalition. Engineers, policy advocates, community leaders, and the very patients the system failed sat down together and built something better: a methodology for auditing AI that is now used by federal agencies and hospital networks across the country.
We're still building. And we're looking for the people who want to build with us.
The problem isn't going away on its own
AI now helps decide who gets hired, promoted, paid, approved, treated, and trusted. When women are missing from the data, the design teams, and the boardrooms, the system is broken before it ships. The harm isn't theoretical — it shows up in healthcare, hiring, finance, and search, in the lives of real people.
Most organizations talk about this problem. We work on it. Our model is four steps, and every one of them needs people:
- Identify — We run open audits on AI products across healthcare, hiring, finance, and public services. No NDAs, no hidden methodology.
- Convene — Researchers, builders, and impacted communities meet in our Innovation Labs to define what fair actually looks like.
- Build — Our hackathons and labs ship working, open-source prototypes with documented methodology.
- Hold to account — We publish, partner, and push for governance changes that make fairness the default, not the exception.
We have application for 501(c)(3) nonprofit, and our work is open by default — every audit, every dataset, every prototype is public, forkable, and documented.
Who actually thrives here
The people who do their best work with us share a few things. They'd rather ship an open-source prototype than win an argument. They believe you build with impacted communities, not for them. They're comfortable naming a broken system and then doing the unglamorous work of fixing it.
You don't need a PhD or a famous employer. We've had weekend volunteers turn into lab leads, students turn into published researchers, and senior engineers find the most meaningful work of their careers. What you need is the conviction that the systems shaping our lives should be built by all of us — and the willingness to put hours behind that conviction.
This is your invitation
If you've read this far, you're probably not looking for another newsletter to skim. You're looking for somewhere your skills actually matter. That's exactly what we're offering.
Fix the algorithm. Transform the future. Build the AI we all deserve — and build it with us.
