Surrendering to Powerlesness: Governing Personal Data Flows in Generative AI

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.}, booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

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Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713504
Citations
2
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
8.40
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article

Surrendering to Powerlesness: Governing Personal Data Flows in Generative AI

Hosana Cristina Morales Ornelas, Alejandra Gómez Ortega, Hüseyin Uğur Genç
2 citations
Privacy, Security, and Data Protection
8.40
article

Surrendering to Powerlesness: Governing Personal Data Flows in Generative AI

Hosana Cristina Morales Ornelas, Alejandra Gómez Ortega, Hüseyin Uğur Genç
article en
2 citations

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.}, booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

Stockholm University (SE), Delft University of Technology (NL)
Gender equality
Openalex Percentile: Top 4%
Privacy, Security, and Data Protection
8.40
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