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

2026-06-05

AI Summary

This study addresses the empirical gap in multi-stakeholder deliberation within current AI governance frameworks, which hinders the realization of “responsible openness” that balances innovation, accountability, and public interest. Through participatory workshops involving diverse sectors and integrating futures thinking with co-design methodologies, this project systematically documents stakeholders’ collective aspirations regarding AI openness for the first time. The research identifies four core tensions across purpose, scope, and operational dimensions, demonstrating that responsible openness is fundamentally a value-driven sociotechnical negotiation process. Key outputs include a shared vision of collaborative intent, actionable pathways, and a research roadmap, offering both empirical grounding and methodological innovation to advance AI governance beyond dominant corporate narratives.

Abstract

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.

Problem

• open source
• AI governance
• responsible openness
• participatory design
• foundation models

Innovation

• responsible openness
• participatory design
• AI governance
• sociotechnical tensions
• futures thinking