$25,000
2020 • 1 month • Technology in the Public Interest
A project of YarnLabs, the Algorithmic Justice League is focused on conducting rigorous academic research on algorithmic bias that can lead to harmful discrimination; evidence-based advocacy focused on the AI industry and policymakers; and, producing art and creative science communication pieces to inform the general public on the risks and opportunities of artificial intelligence. The award supports Algorithmic Justice League team's participation in the 2020 Sundance Film Festival for the premiere of Coded Bias, a documentary that features the organization's work.
$500,000
2020 • 2 years • Technology in the Public Interest
A project of Yarn Labs, the Algorithmic Justice League is focused on conducting rigorous academic research on algorithmic bias that can lead to harmful discrimination; evidence-based advocacy focused on the artificial intelligence industry and government policymakers; and, producing art and creative science communication pieces to inform the general public on the risks and opportunities of artificial intelligence. Through this work, the Algorithmic Justice League seeks to advance transparency and accountability in the development, deployment and use of artificial intelligence related technologies and help ensure that marginalized communities most at risk to be harmed by these technologies are agents of change. The award provides flexible support to the organization.
$45,000
2019 • 6 months • Technology in the Public Interest
A project of YarnLabs, the Algorithmic Justice League is focused on conducting rigorous academic research on algorithmic bias that can lead to harmful discrimination; evidence-based advocacy focused on the AI industry and policymakers; and, producing art and creative science communication pieces to inform the general public on the risks and opportunities of artificial intelligence. The award supports a study and the publication of a white paper focused on sociotechnical considerations in the creation of human-centered computer vision datasets.