critical infrastructure lab

Artificial Intelligence relies on data. Currently, we see a “bigger is better” mentality in both AI research and AI business models. This leads to ever more complex AI systems and massive data sets. But are they sustainable? Currently, the ensuing environmental, social and economic harms are ignored both by established data governance regimes and regulatory approaches such as the DSA/DMA, Data Act or AI Act. We have yet to find data governance approaches that adequately respond to the unsustainability of extractivist AI data collection and data processing and their underlying technical infrastructures. In this panel, we will discuss the global harms of AI systems and shortcomings of established data governance approaches, as well as new ideas for regulations geared towards more sustainable data governance and AI policies in an age where Artificial Intelligence is becoming a general-purpose technology.

the global harms of powering ai – towards a sustainable future of data use and governance @computers, privacy, and data protection (cpdp). View the panel here.