Normative Infrastructuring from the Ground Up: Experiential Pathways to Global AI Governance

AI is advancing fast, but how can policymakers build “real” norms—norms that govern behaviour effectively and take hold proactively in practice—even when the technology is opaque, evolving rapidly, and its impacts remain uncertain? What does democratic legitimacy look like in such an environment, where no stable “ground truth” exists?

Xueyin’s dissertation argues that such proactive norm construction is both possible and necessary. Drawing on pragmatist philosophy, empirical fieldwork on the EU AI Act, and interviews across the AI ecosystem, it introduces a pragmatist method of normative truth-seeking that enables what she terms full-stack norm alignment: aligning ethical commitments and technical practices with epistemic confidence and normative integrity.

The project yields three substantive outputs: a conceptual framework for full-stack norm alignment, an empirical mapping of practice-level experiential norms in AI communities, and a meta-governance strategy—normative infrastructuring—that equips policymakers with a pathway to uplift both the effectiveness and legitimacy of governance in existential global issues such as AI and climate change.

Speaker 

Xueyin Zha (she/her) is a PhD candidate in International, Political, and Strategic Studies at the Australian National University. Her research tackles a core challenge in global AI governance: creating alignment between high-level normative principles and the concrete technical norms that shape real-world AI practice. Beyond academia, she contributes to policy debates and public commentary on technology governance and informed trust in innovation.


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