Attempts at artificial intelligence (AI) governance are inadequate in promoting social well-being. In the West, the EU’s AI Act is leading in its support of algorithmic transparency and human-centered approaches to AI, while the United States’ legislation on AI is wholly lacking. However, we maintain that the glaring problems are that (1) individuals are viewed only as agents entangled in acts of resistance, and (2) that existing AI applications are developed with little regard for local meaning, community knowledge-checks, and counter-narratives. While human-in-the-loop approaches have been introduced to bring more value and meaning to AI-enabled products, their involvement does little to promote grass-roots democracy. The current article addresses these shortcomings by developing a framework for AI development that elevates and democratizes local knowledge: A People’s AI. In this regard, A People’s AI refers to grass-root efforts that embody local strengths, needs, and control. A People’s AI addresses these issues by constructing several guiding elements that will be discussed in this manuscript. A preliminary discussion of what A People’s AI should look like is presented in an attempt to describe the utility of each guiding principle. Fundamental, however, is that A People’s AIrequires that any relevant AI system have a thorough community grounding. @font-face {font-family:"Cambria Math"; panose-1:2