Rowe, M. (2025). Context sovereignty for AI-supported learning: A human-centred approach. DOI: 10.31219/osf.io/8czva_v1
Many approaches to developing AI literacy include an emphasis on better prompting strategies, requiring students and educators to adapt to AI systems rather than having the systems adapt to us. While this isn’t wrong, prompting should be understood as a specific example of the more general concept of ‘context-setting’, and by extension, a set of principles that guide how we think about personal context.
Context sovereignty flips this relationship: instead of constantly explaining your background and goals to AI, the system should have a persistent understanding of your values, knowledge, thinking patterns, and learning objectives. And context engineering provides the practical framework to achieve this sovereignty through three key elements: personal context curation (structuring information to explicitly describe part of how you think), continuous learning (AI systems that evolve with you), and contextual interoperability (maintaining privacy while accessing AI capabilities).
For higher and professional education, this transformation towards a focus on context matters. Health professions students can develop AI partnerships build on a foundation where the system understands their development. Rather than generic interactions, learners engage in more nuanced and sophisticated cognitive partnerships that respect their individual intellectual journeys.
This approach preserves human agency while enabling authentic personal learning rather than mere algorithmic content matching, amplifying human capabilities through AI support.
Read more at : https://michael-rowe.github.io/emergent-scholarship/essays/context-sovereignty.html
Abstract
The current discourse around artificial intelligence in education has become preoccupied with prompting strategies, overlooking more fundamental questions about the nature of context in human-AI collaboration. This paper explores the concept of context engineering as an operational framework that supports personal learning and the philosophical goal of context sovereignty. Drawing from complexity science and learning theory, we argue that context functions as a dynamic field of meaning-making rather than static background information, and that ownership of that context is an essential consideration. Current approaches to context-setting in AI-supported learning—primarily prompting and document uploading—create episodic burdens requiring learners to adapt to AI systems rather than insisting that AI systems adapt to learners. Context sovereignty offers an alternative paradigm based on three principles: persistent understanding, individual agency, and cognitive extension. This framework addresses concerns about privacy, intellectual challenge, and authentic assessment while enabling new forms of collaborative learning that preserve human agency. Rather than treating AI as an external tool requiring skilful manipulation, context sovereignty suggests AI can become a cognitive partner that understands and extends human thinking while respecting individual boundaries. The implications extend beyond technical implementation to fundamental questions about the nature of learning, assessment, and human-AI collaboration in educational settings.