Designing Participatory Algorithmic Decision-Making Processes

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Session Description

Algorithms play an increasingly relevant role in shaping our digital and physical experiences of the world. It is frequently the case that data from our digital footprints is used to predict our behavior and make decisions about the choices available to us. This unprecedented capacity to collect and analyze data has brought along with it a troubling dismissiveness of user agency, participation, and ownership. Such systems assume that it is an acceptable by-product for their users to have no understanding of the decisions being made about them and no agency in that decision-making process. For the most part, the invisiblized nature of these decisions are seen as a feature, not a bug, of a good user experience. As we begin to use algorithmic decision-making in areas of our lives that are increasingly high-stakes, it is essential that we create and utilize processes that maintain user agency and understanding. In this session, participants will be imagining and designing user experiences that employ participatory algorithmic-decision making processes. The session will be open to folks from all experience levels. I would be excited to see folks from a variety of different backgrounds, including designers, data scientists, data journalists, privacy & security practioners, and organizers from marginalized and frequently surveilled communities.

Designing Participatory Algorithmic Decision-Making Processes
Presenter/s Tara Adiseshan
Bio/s Tara Adiseshan is a Knight-Mozilla Fellow currently working on The Coral Project, a collaboration between The New York Times, Washington Post, and Mozilla to build better communities around news. Tara is a data scientist and designer who enjoys thinking about online comunities, learning tools, and computational social science.
Language English

Session Comments