Article by Stefaan Verhulst: “As artificial intelligence systems rapidly evolve and start to impact nearly every sector of society, the conversation around governance has mainly focused on models (and their output): their transparency, fairness, accountability, and alignment. Yet this focus, while necessary, is incomplete. AI systems are only as reliable, equitable, and effective as the data (input) on which they are trained and operate.
Data governance is not peripheral to AI governance — it is its bedrock.
At the same time, the rise of AI is not simply placing new demands on data governance; it is fundamentally transforming it. What counts as data, how it is curated, who has a say in its use, and which institutional arrangements govern it are all being reimagined in response to AI’s capabilities and risks.
This essay examines 10 key areas or shifts where data governance is being reshaped—either to accommodate AI or as a direct consequence of it…(More)”.
