Artificial intelligence (AI) encompasses a broad set of technologies with intelligent capabilities, such as learning, image and language processing, planning and possibly reasoning. Depending on its context, AI can function as a club, private, or public good. As a knowledge resource (Ostrom and Hess, 2007), AI’s production, sharing, and use benefit the broader public but, similar to some common pool resources, remain vulnerable to excludability and enclosure. These challenges are especially pronounced in the developing world, where colonial and postcolonial legacies exacerbate these problems. As initiatives around AI and its governance continue to expand, understanding the current state of public involvement in the production, deployment, regulation, and use of AI—and exploring how it can be broadened to promote sustainable development and a more equitable global society—becomes increasingly important.
This paper addresses this question by analyzing the landscape of AI and development through the lens of two frameworks: knowledge commons and public participation. Using the Governing Knowledge Commons framework (Frischmann, Madison, & Strandburg, 2014), we examine international and national guidance documents that address AI in the context of development, including the outputs from the UN and the World Economic Forum, and the collection of documents under the Executive Order on Artificial Intelligence in the US. In this analysis we will be looking for the extent to which existing definitions focus on the social and the technical sides of AI and for how various attributes of AI, such as data, infrastructure, models, and communities around it are envisioned and conceptualized in these documents. We then compare these discussions to public participation literature on AI, exploring how these approaches align with the principles of equity, safety, responsibility, and localization.
We conclude by highlighting areas for empirical research that could strengthen responsible and equitable AI development and by presenting several key questions for further discussion on the barriers to collective action and public participation in AI.
