Algorithmic Justice League (AJL)

What it does

Founded by Joy Buolamwini. Combines art, research and advocacy to expose AI bias and harm — the Gender Shades audits of facial recognition, the Coded Bias documentary, and campaigns against biometric surveillance. Operates a public harm-reporting platform and builds the voice of the most-impacted communities.

What they ask for — in their own terms

Stop AI harms and bias — especially from facial recognition and biometric systems — by centring the people most affected and giving them a way to report what happened to them.

What they do

Research, art and advocacy founded by Joy Buolamwini; runs report.ajl.org to collect public accounts of AI harm, campaigns such as #FreedomFlyers on TSA facial recognition, and equips advocates with empirical research.

Honest assessment

Small, mission-driven, and one of the few organisations that has built an actual intake for individual harm stories and has a track record of acting on them. High responsiveness for in-scope harms; out of scope for anything frontier or speculative.

What a newcomer can do

If an AI system has harmed you — a facial recognition misidentification, an airport scan, a rejected application — file it at report.ajl.org this week. Otherwise take an action from the Take Action page.

Worth knowing

Its remit is bias, biometrics and civil rights harm, not frontier model risk. Reporting a harm is not legal representation — AJL is not a law firm and cannot act on your case.

Concerns it covers

Near-term algorithmic harm to real people, especially racialised and gendered bias in facial recognition, biometrics and automated decision-making. Civil-rights framing throughout. Absolutely not an alignment organisation.

Government channel

Real — AJL research has directly driven municipal facial-recognition bans, FTC and congressional attention, and corporate product withdrawals (IBM, Amazon, Microsoft facial recognition).

Tips

yes — report.ajl.org is an explicit public harm-reporting channel

Where they work

United States primarily, international reach.

Size

Small organisation with very large cultural reach (Coded Bias, Buolamwini's research).

Spending

Donations via ActBlue and merchandise sales.