Tracking menopause: An SDK Data Audit for intimate infrastructures of datafication with ChatGPT4o
This article presents a novel methodology to examine the tracking infrastructures that extend datafication across a sample of 14 menopause-related applications. The Software Development Kit (SDK) Data Audit is a mixed methodology that explores how personal data are accessed in apps using ChatGPT4o to account for how digital surveillance transpires via SDKs. Our research highlights that not all apps are equal amid ubiquitous datafication, with a disproportionate number of SDK services provided by Google, Meta, and Amazon. Our three key findings include: (1) an empirical approach for auditing SDKs; (2) a means to account for modular SDK infrastructure; and (3) the central role that App Events—micro-data points that map every action we make inside of apps—play in the data-for-service economy that SDKs enable. This work is intended to open up space for more critical research on the tracking infrastructures of datafication within our apps in any domain.
Authors
- Muhammad Hussain Mir (ORCID: https://orcid.org/0009-0006-8326-8468)
- Jennifer Pybus (ORCID: https://orcid.org/0000-0002-1136-1237)
Institutions
- York University (CA)
Publication Details
- Journal
- New Media & Society
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1177/14614448251314401
- Citations
- 1
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 2.37