Fake Transparency: When Mobile Apps Say One Thing but Do Another

Alejandro Pérez-Fuente, Pablo-Abel Criado-Lozano, M. Mercedes Martínez-González
Proceedings of Fourth European Workshop on Algorithmic Fairness, PMLR 294:369-375, 2025.

Abstract

Mobile apps are extensively used. Transparency about the use of personal data is a requirement, both from a legal perspective and from an ethical perspective: users should know what data is accessed by these applications and how it is treated afterwards. Sharing sensitive information with third parties can result in negative consequences for the data owner due to biased algorithms. Consent is necessary, as well as awareness that this will happen; the right to fair information is violated otherwise, particularly for collectives such as minors, who cannot consent to this processing. To help prevent these problems, we propose an audit system in which conflicts between declarations made to users and declarations that accompany the software executed on mobile devices are detected. Our thesis is that this is feasible and beneficial for end users, developers, and other agents involved in app preparation.

Cite this Paper

BibTeX
@InProceedings{pmlr-v294-perez-fuente25a, title = {Fake Transparency: When Mobile Apps Say One Thing but Do Another}, author = {P\'erez-Fuente, Alejandro and Criado-Lozano, Pablo-Abel and Mart\'inez-Gonz\'alez, M. Mercedes}, booktitle = {Proceedings of Fourth European Workshop on Algorithmic Fairness}, pages = {369--375}, year = {2025}, editor = {Weerts, Hilde and Pechenizkiy, Mykola and Allhutter, Doris and Corrêa, Ana Maria and Grote, Thomas and Liem, Cynthia}, volume = {294}, series = {Proceedings of Machine Learning Research}, month = {30 Jun--02 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v294/main/assets/perez-fuente25a/perez-fuente25a.pdf}, url = {https://proceedings.mlr.press/v294/perez-fuente25a.html}, abstract = {Mobile apps are extensively used. Transparency about the use of personal data is a requirement, both from a legal perspective and from an ethical perspective: users should know what data is accessed by these applications and how it is treated afterwards. Sharing sensitive information with third parties can result in negative consequences for the data owner due to biased algorithms. Consent is necessary, as well as awareness that this will happen; the right to fair information is violated otherwise, particularly for collectives such as minors, who cannot consent to this processing. To help prevent these problems, we propose an audit system in which conflicts between declarations made to users and declarations that accompany the software executed on mobile devices are detected. Our thesis is that this is feasible and beneficial for end users, developers, and other agents involved in app preparation.} }
Endnote
%0 Conference Paper %T Fake Transparency: When Mobile Apps Say One Thing but Do Another %A Alejandro Pérez-Fuente %A Pablo-Abel Criado-Lozano %A M. Mercedes Martínez-González %B Proceedings of Fourth European Workshop on Algorithmic Fairness %C Proceedings of Machine Learning Research %D 2025 %E Hilde Weerts %E Mykola Pechenizkiy %E Doris Allhutter %E Ana Maria Corrêa %E Thomas Grote %E Cynthia Liem %F pmlr-v294-perez-fuente25a %I PMLR %P 369--375 %U https://proceedings.mlr.press/v294/perez-fuente25a.html %V 294 %X Mobile apps are extensively used. Transparency about the use of personal data is a requirement, both from a legal perspective and from an ethical perspective: users should know what data is accessed by these applications and how it is treated afterwards. Sharing sensitive information with third parties can result in negative consequences for the data owner due to biased algorithms. Consent is necessary, as well as awareness that this will happen; the right to fair information is violated otherwise, particularly for collectives such as minors, who cannot consent to this processing. To help prevent these problems, we propose an audit system in which conflicts between declarations made to users and declarations that accompany the software executed on mobile devices are detected. Our thesis is that this is feasible and beneficial for end users, developers, and other agents involved in app preparation.
APA
Pérez-Fuente, A., Criado-Lozano, P. & Martínez-González, M.M.. (2025). Fake Transparency: When Mobile Apps Say One Thing but Do Another. Proceedings of Fourth European Workshop on Algorithmic Fairness, in Proceedings of Machine Learning Research 294:369-375 Available from https://proceedings.mlr.press/v294/perez-fuente25a.html.

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