CYJun 5

Reimagining Open Source and Openness in AI: Co-Creating Responsible Technological Futures

arXiv:2606.0776415.41 citationsh-index: 22Has Code
Predicted impact top 13% in CY · last 90 daysOriginality Incremental advance
AI Analysis

For AI governance researchers and policymakers, this work provides empirical insights into how diverse stakeholders negotiate openness, accountability, and power, though it is an incremental contribution as it primarily documents a workshop process.

This paper reports on a multi-sectoral workshop that used participatory futures methods to co-create visions and action pathways for responsible open source and openness in AI, identifying four core tensions in how stakeholders interpret openness. The findings reveal that responsible openness is a negotiated sociotechnical project rather than a singular technical solution.

Debates over open source and openness in artificial intelligence have intensified as policymakers, researchers, and practitioners grapple with how foundation models should be developed and governed to balance innovation, accountability, and public interest. However, there has been limited empirical work examining how diverse stakeholders collectively understand and negotiate responsible openness in AI, particularly through participatory processes that extend beyond industry-led definitions and frameworks. This paper presents findings from a multi-sectoral workshop grounded in futures thinking and participatory design methods. The workshop generated co-created visions of desirable futures and the role of AI, alongside a set of action pathways and a research roadmap focused on responsible open source and openness in AI. This paper makes three key contributions. First, it empirically documents the co-created visions, actions, and research priorities. Second, it identifies four core tensions that emerged as participants translated high-level aspirations into concrete actions, revealing conflicting interpretations of openness regarding its purpose (as an end or a means), its scope (expansion versus meaningful access), and its operation (mandatory versus conditional, sufficient versus dependent on governance and use). These tensions illustrate that responsible openness is not a singular technical solution, but a negotiated sociotechnical project shaped by values, positionalities, and priorities. Third, the paper advances methodological approaches in AI governance by demonstrating how participatory futures methods can surface plural visions, actions, and research priorities that extend beyond dominant, largely corporate, narratives, offering empirical insight into how openness, power, and accountability are negotiated in practice.

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