13.6.2024 CIS #40 Jessica Feldman

Le séminaire du CIS reçoit Jessica Feldman (American University of Paris), jeudi 13 juin 2024, de 11h à 12h30, à Paris (site Pouchet) et en visioconférence. Merci de vous inscrire.

Collective Trust? Comparative Commons-Centric Design for AI and Algorithmic Trust

This seminar introduces a new research project investigating the concept of “collective trust” vis-à-vis AI and algorithmic decision-making. Based on fieldwork and interviews with horizontal and decentralized community groups and social movements, Jessica Feldman will present some observed problems arising with the use of algorithmic digital security and digital democracy tools. She will then outline preliminary reviews of the state-of-the-industry for trust in digital design, and of literature on existing theoretical paradigms of trust which undergird digital models. 

The groups studied are often stymied in their democratic practices at the layer of digital security, where power bottlenecks around the holder of the passwords or the managers of the social media accounts, and struggles ensue. More challenges arise as they seek to scale up across distances, work remotely, or automate decisions, requiring the use of digital tools for a form of deliberative decision-making that generally does not rely on binary or predictive logic. This often leads to serious rifts within the groups, disrupting their dynamics of trust and processes of governance. 

In computer science, the problem of trust in AI has arisen as a question of accuracy in prediction, or transparency about decision making processes, rather than something communal, dynamic, or relational. Most existing research on public trust in AI largely focuses on developing methods to explain AI in order to encourage adoption of the technology by individual users, and to encourage public acceptance that AI will be used “on them” in the realms of policing or governance service provision. Research on “Trust and Computing” also tends to conceptualize the trust relationship as a dyadic one between an individual human user and technology.  

These perspectives evidence themselves in the fact that very few designs exist that imagine the user as a collective rather than an individual. This research project will attempt to articulate what algorithmic decision making tools would look like if conceived to support and respect “collective trust” and solidarity in democratic groups.

Jessica Feldman is a researcher and an artist. She is an Assistant Professor at the American University of Paris in the Department of Communication, Media, and Culture. Before that, she was a Postdoctoral Fellow at the Digital Civil Society Lab at Stanford University, after earning a Ph.D. in Media, Culture, and Communication from New York University.

Jessica Feldman

Her research focuses on the intersection of new information and communication technologies and social justice, mainly by connecting ethnographic fieldwork with social movements and design collaborations with engineers. Her current book project articulates core design priorities that emerge in alternative computing tools developed by grassroots social movements focused on values of democracy, solidarity, and inclusive participation. Her artwork addresses similar issues by experimenting with emerging technologies and practices of listening. Her research has been published in English and French in international journals and edited volumes and her artwork has been shown internationally in venues such as galleries, museums, concert halls, public parks, and city streets.