Mapping WUN expert discourse on responsible and ethical AI: a multinational expert network analysis

The global discourse on artificial intelligence (AI) ethics represents a critical site of scientific and expert communication, where meanings are negotiated, and priorities are set. This study investigates how a transnational network of experts constructs and communicates the concept of “responsible AI.” We analyze the deliberative discourse from the World University Network (WUN) initiative on Responsible & Ethical AI (2023) through a multi-method framework combining computational text analysis (TF-IDF) and network analysis (co-occurrence networks) of semantic relationships. By examining expert webinar transcripts, we move beyond isolated principles to map the communicative architecture of this debate, visualizing how core themes like accountability, transparency, and equity are framed and interconnected across academic, policy, and practitioner perspectives. Our findings reveal that expert consensus is built not on a glossary of terms but on a shared conceptual network where technical, governance, and ethical concerns are deeply intertwined. This study contributes to science communication research by: (1) offering a novel methodological pipeline for mapping consensus and divergence in expert discourse, and (2) providing empirical evidence that collaborative academic networks function as vital “communicative infrastructures” for translating theoretical ethical frameworks into actionable policy paradigms.