Advocacy, Policy, and Community Engagement in the Age of AI
Year: 2026
Type: preprint
Abstract: The rapid adoption of generative AI across organizations and society has outpaced the frameworks available to manage it. This chapter argues that existing change management theories, from Lewin's planned model through the emergent approaches of Kanter and Kotter, and even the more human-centered work of Armenakis and Harris, were not built for the unique disruption posed by large language models. Equally, dominant ethical frameworks grounded in deontological and utilitarian thinking have proven insufficient for the relational and contested ques-tions generative AI raises. Together, these gaps call for something different: a model that leads not with process or compliance, but with care. We propose the Care-First Change Framework, grounded in the Ethics of Care (Gilli-gan, 1977; Noddings, 1988; Tronto, 1993) and organized through a Freirean reflection-action cycle (Freire, 2001). Its four components, Modeling, Dialogue, Practice, and Co-Creation, offer a relational, iterative process by which any member of a community or organization, not just those in formal leadership roles, can navigate its relation-ship with generative AI and work toward agreements they believe in. We develop the framework through the prism of P-20 education, where these tensions are especially visible, while showing that the approach extends to advocacy, policy, and community engagement across other institutional and societal contexts.
Source: EdArXiv (OSF Preprints)
Authors: John Nash, Jason Johnston
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225455044