Creating (Open) Data Commons in the Age of AI and Big Data
There is increasing reuse of open data (and other public data) by AI technologies, albeit propelled by an extractive data political economy. While regulations and policies should enable innovative reuse of data for public interest AI, they should also address appropriation of open data by certain actors, privacy protection, and the lack of shared decision-making. Efforts for governance of AI can benefit from a commons-based orientation. Digital commons present a ‘third way’ of organizing society and the digital economy (different from purely state-based and marketdriven approaches), where data, information, and knowledge are shared in ways that avoids their capture by a few actors and expands digital rights. Our panel pro- vides new perspectives on open data commons. We focus on central themes of openness, value generation and redistribution, polycentric decision making, and sustainability.
• How can we critically formulate ‘openness’ from a commons perspective?
• What are the benefits and challenges of applying commons-based governance principles to data re-use initiatives?
• What role can licenses, standards, collective data governance structures, and regulations play in enabling responsible re-use of data for AI?
• How can we address scalability and replicability of commons-based data re-use initiatives?
Organised by Centre for Internet and Society (FR)
Moderator Alexandra Giannopoulou, Digital Freedom Fund/IViR (GR)
Speakers Renata Avila, Open Knowledge Foundation (UK); Yaniv Benhamou, University of Geneva/ Aegis Partners (SW); Ramya Chandrasekhar, CNRS (FR); Mélanie Dulong de Rosnay, CNRS (FR)
