Surrendering to Powerlesness

Governing Personal Data Flows in Generative AI

Conference Paper (2025)
Author(s)

Alejandra Gómez Ortega (Stockholm University)

Hosana Morales Ornelas (TU Delft - Knowledge and Intelligence Design)

Uğur Genç (TU Delft - Human-Centred Artificial Intelligence)

Knowledge and Intelligence Design
DOI related publication
https://doi.org/10.1145/3706598.3713504
More Info
expand_more
Publication Year
2025
Language
English
Knowledge and Intelligence Design
Publisher
ACM
ISBN (electronic)
979-8-4007-1394-1
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

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.