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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Algorithmic Justice League | 2/2 | https://en.wikipedia.org/wiki/Algorithmic_Justice_League | reference | science, encyclopedia | 2026-05-05T06:58:00.489687+00:00 | kb-cron |
=== Olay Decode the Bias campaign === In September 2021, Olay collaborated with AJL and O'Neil Risk Consulting & Algorithmic Auditing (ORCAA) to conduct the Decode the Bias campaign, which included an audit that explored whether the Olay Skin Advisor (OSA) System included bias against women of color. The AJL chose to collaborate with Olay due to Olay's commitment to obtaining customer consent for their selfies and skin data to be used in this audit. The AJL and ORCAA audit revealed that the OSA system contained bias in its performance across participants' skin color and age. The OSA system demonstrated higher accuracy for participants with lighter skin tones, per the Fitzpatrick Skin Type and individual typology angle skin classification scales. The OSA system also demonstrated higher accuracy for participants aged 30–39. Olay has, since, taken steps to internally audit and mitigate against the bias of the OSA system. Olay has also funded 1,000 girls to attend the Black Girls Code camp, to encourage African-American girls to pursue STEM careers.
=== CRASH project === In July 2020, the Community Reporting of Algorithmic System Harms (CRASH) Project was launched by AJL. This project began in 2019 when Buolamwini and digital security researcher Camille François met at the Bellagio Center Residency Program, hosted by The Rockefeller Foundation. Since then, the project has also been co-led by MIT professor and AJL research director Sasha Costanza-Chock. The CRASH project focused on creating the framework for the development of bug-bounty programs (BBPs) that would incentivize individuals to uncover and report instances of algorithmic bias in AI technologies. After conducting interviews with BBP participants and a case study of Twitter's BBP program, AJL researchers developed and proposed a conceptual framework for designing BBP programs that compensate and encourage individuals to locate and disclose the existence of bias in AI systems. AJL intends for the CRASH framework to give individuals the ability to report algorithmic harms and stimulate change in AI technologies deployed by companies, especially individuals who have traditionally been excluded from the design of these AI technologies [20, DataSociety report].
=== Freedom Flyers Campaign === Beginning in 2023, the AJL launched the “Freedom Flyers” campaign, which raises awareness about the use of facial recognition by TSA at U.S. airports. As part of the campaign, the organization collects traveler experiences through a “TSA scorecard” to document how biometric systems are used at airport checkpoints . Its report ''Comply to Fly?'' found that many travelers perceive facial recognition screening as mandatory, despite official claims that it is voluntary. The campaign also highlights that passengers can opt out of facial recognition without penalty and hosts events such as the Freedom Flyers Summit to discuss the broader implications of these technologies. It frames airport screening as a key site in the expansion of biometric surveillance and raises concerns about privacy, consent, and potential bias, particularly for marginalized groups.
== Support and media appearances == AJL initiatives have been funded by the Ford Foundation, the MacArthur Foundation, the Alfred P. Sloan Foundation, the Rockefeller Foundation, the Mozilla Foundation and individual private donors. Fast Company recognized AJL as one of the 10 most innovative AI companies in 2021. Additionally, venues such as Time magazine, The New York Times, NPR, and CNN have featured Buolamwini's work with the AJL in several interviews and articles.
== See also ==
== References ==
== External links == Official Website