BEYOND PERFORMATIVE TRANSPARENCY: LESSONS LEARNED FROM THE EU CODE OF PRACTICE ON DISINFORMATION
Keywords:disinformation, data colonialism, platform governance, performative transparency
AbstractThe EU Code of Practice on Disinformation has attempted to approach the issue of disinformation through a self-regulatory model, but this has seen limited success. We analyse 1114 self-reported actions from Code signatories (Google, Meta, Microsoft, Mozilla, TikTok and Twitter) taken from 47 monthly transparency reports addressing Covid-19 related disinformation. While the transparency reports were designed to provide clear, meaningful reporting, in reality the process of assessing each platform’s disinformation actions was difficult due to repetition, vague descriptions and a lack of quality data. Platform actions were often reported using a promotional tone and some were irrelevant to COVID-19 or disinformation. We argue that the way in which we understand the role that social media platforms play in both the collection of data and the social outcomes that result from these data extraction processes needs to be questioned. Drawing upon the concept of data colonialism, we call for transparent access to data based on the idea that what platforms view as property is based on a “commercially motivated form of extraction” rather than a “naturally occurring form of social knowledge”. European debates about regulating online disinformation need to be set against a broader perspective on regulating the digital environment as a public infrastructure. Policymakers can achieve better civic and democratic outcomes by focusing on regulating the digital environment through, for example, robust competition, data portability, and interoperability rules. Such actions have the potential to break the dominance of Big Tech while incentivising better and new services for citizens.
How to Cite
Park, K., & Culloty, E. (2023). BEYOND PERFORMATIVE TRANSPARENCY: LESSONS LEARNED FROM THE EU CODE OF PRACTICE ON DISINFORMATION. AoIR Selected Papers of Internet Research, 2022. https://doi.org/10.5210/spir.v2022i0.13067