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 re-use 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 market-driven approaches), where data, information, and knowledge are shared in ways that avoids their capture by a few actors and expands digital rights. Our panel provides new perspectives on open data commons. We focus on central themes of openness, value generation and redistribution, polycentric decision-making, and sustainability.
