Uploaded June 2022 | Updated September 2026, 1 day ago
Data Leverage: A Framework for Empowering the Public and Mitigating Harms of AI
Nicholas Vincent
Many powerful computing technologies rely on both implicit and explicit data contributions from the public. This dependency suggests a potential source of leverage for the public in its relationship with technology companies: by reducing, stopping, redirecting, or otherwise manipulating data contributions, a group of people can reduce the effectiveness of the lucrative technologies of an organization they wish to pressure to change, or boost up the technologies of a competitor. In this talk, I will present a a framework for understanding “data leverage” that highlights new opportunities to change to address negative impacts related to economic inequality, privacy, content moderation and other areas of societal concern that stem from data-dependent technologies and tech company practices. I will highlight the role of research that measures data value and that simulates data-related collective action, and discuss a future research agenda for this work at the intersection of human-computer interaction and machine learning.
Data Leverage: A Framework for Empowering the Public and Mitigating Harms of AI
Nicholas Vincent
Many powerful computing technologies rely on both implicit and explicit data contributions from the public. This dependency suggests a potential source of leverage for the public in its relationship with technology companies: by reducing, stopping, redirecting, or otherwise manipulating data contributions, a group of people can reduce the effectiveness of the lucrative technologies of an organization they wish to pressure to change, or boost up the technologies of a competitor. In this talk, I will present a a framework for understanding “data leverage” that highlights new opportunities to change to address negative impacts related to economic inequality, privacy, content moderation and other areas of societal concern that stem from data-dependent technologies and tech company practices. I will highlight the role of research that measures data value and that simulates data-related collective action, and discuss a future research agenda for this work at the intersection of human-computer interaction and machine learning.
