Code for Science and Society

The Distributed AI Research Institute

A project of Code for Science & Society, The Distributed AI Research Institute (DAIR) is an interdisciplinary and globally distributed AI research institute rooted in the belief that AI is not inevitable, its harms are preventable, and when its production and deployment include diverse perspectives and deliberate processes it can be beneficial. The organization works across three interrelated areas: (1) Data for Change – using quantitative and qualitative methodologies to equip historically marginalized groups with data to advocate for change; (2) Frameworks for AI Research and Development – building frameworks for non-exploitative community rooted research practice; and (3) Alternative Tech Futures – Imagining technological futures reflective of everyone being able to see themselves centered in the design of new technology. The award provides flexible support to DAIR.

REAL ML

Code for Science and Society empowers communities to work together and build innovative technology for the public good. It envisions a future where research, data, and technology initiatives shift power to communities. The award provides flexible support to REAL ML (Research, Engagement, Advocacy, and Lived Experience in Machine Learning), a project of Code for Science and Society, whose mission is to connect a global interdisciplinary community of practitioners and researchers to translate algorithmic accountability research into real world interventions that benefit the public interest. It nurtures and mainstreams narratives and critiques rooted in equity and values of human rights, antiracism, anticolonialism, and feminism, with practices that center lived experience, participation, and social justice. REAL ML is primarily carried out through a variety of events and workshops that are meant to help the organization’s community members test ideas, develop research methods, and engage in shared learning to inform their work and that of the broader ecosystem.

Algorithmic Justice League

A project of Code for Science and Society, the mission of Algorithmic Justice League (AJL) is to raise public awareness about the impacts of artificial intelligence (AI), equip advocates with resources to bolster campaigns, build the voices and choice of the most impacted communities, and galvanize researchers, policymakers, and industry practitioners to prevent AI harms. The organization envisions a world where data is not destiny, where algorithmic decisions do not choke opportunities, and where every day people have the knowledge and power to shape AI systems to prevent harm and enjoy the promise of AI. AJL has three areas of work: it engages in storytelling and creative communication to raise awareness about the impact of AI; it maintains the Harms Reporting Tool which aims to capture people’s listed experiences with AI harms, connect them with resources, and identify areas where there are no or few resources; and it advocates for protocols and federal and industry practices that prevent future AI harms and works to ensure that people and communities who have experienced AI harms are acknowledged and seek redress. The award provides flexible support to AJL to advance the organization’s work.

Code for Science and Society empowers communities to work together and build innovative technology for the public good. It envisions a future where research, data, and technology initiatives shift power to communities. The award supports a REAL ML (Research, Engagement, Advocacy and Lived Experience in Machine Learning) event focused on generative AI. The purpose of the event is to explore the sociotechnical dimensions of generative AI and discuss advocacy and research interventions to safeguard human rights and social justice concerns in the use of generative AI.

Code for Science & Society empowers communities to work together and build innovative technology for the public good. It envisions a future where research, data, and technology initiatives shift power to communities. The award supports the 2022 REAL ML (Research, Engagement, Advocacy and Lived Experience in Machine Learning) virtual workshop in December 2022 that convenes experts from data science and advocacy to journalism and beyond to work on live projects addressing technology accountability and algorithmic justice issues. The workshop is an opportunity to connect disparate researchers engaged in similar research approaches and topics to advance methods and knowledge, while also forming stronger ties and networks.