Surrendering to Powerlesness: Governing Personal Data Flows in Generative AI

要旨

Personal data flows across digital technologies integrated into people's lives and relationships. Increasingly, these technologies include Generative AI. (How) should personal data flow into and out of GenAI models? We investigate how people experience personal data collection in GenAI ecosystems and unpack the enablers and barriers to governing their data. We focus on personal data collection by Meta, specifically Instagram, in line with their recent policy update on processing user data to train GenAI models. We conducted semi-structured interviews with 20 Latin American Instagram users, based in Europe and Latin America. We discussed the acceptability of their data flowing in and out of GenAI models through different scenarios. Our results interrogate power dynamics in data collection, the (inter)personal nature of data, and the multiple unknowns concerning data and their algorithmic derivatives. We pose provocations around feelings of powerlessness, reframing (inter)personal data, and encountering unknown data and algorithms through design.

著者
Alejandra Gomez Ortega
Stockholm University, Stockholm, Sweden
Hosana Cristina. Morales Ornelas
Delft University of Technology, Delft, Netherlands
Hüseyin Uğur Genç
TU Delft, Delft, Netherlands
DOI

10.1145/3706598.3713504

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713504

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Data Interpretation and Storytelling

G418+G419
6 件の発表
2025-04-28 23:10:00
2025-04-29 00:40:00
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