# Relational AI in Education: Reciprocity, Participatory Design, and Indigenous Worldviews

arXiv: https://arxiv.org/abs/2604.19099 · HTML: https://mlsanity.com/paper/2604.19099/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 50 references that are in the map.
- First posted on arXiv 21 Apr 2026.

## Builds on (most cited first, 4 of 4)

- [Beware of Metacognitive Laziness: Effects of Generative Artificial Intelligence on Learning Motivation, Processes, and Performance](https://mlsanity.com/paper/2412.09315/) (2024)
- [The Ethics of AI in Education](https://mlsanity.com/paper/2406.11842/) (2024)
- [Towards social generative AI for education: theory, practices and ethics](https://mlsanity.com/paper/2306.10063/) (2023)
- [When Machines Join the Moral Circle: The Persona Effect of Generative AI Agents in Collaborative Reasoning](https://mlsanity.com/paper/2511.01205/) (2025)

## Abstract (arXiv)

Education is not merely the transmission of information or the optimisation of individual performance; it is a fundamentally social, constructive, and relational practice. However, recent advances in generative artificial intelligence (GenAI) increasingly emphasise efficiency, automation, and individualised assistance, risking the weakening of relational learning processes. Despite growing adoption, AI in education (AIED) research has yet to fully articulate how AI can be designed in ways that sustain the social and ecological relationships through which learning occurs. In this paper, we re-centre education as relational and frame learner-AI interactions as context-specific relationships with clearly defined purposes and boundaries, rather than positioning them as substitutes for, or replacements of, human interaction. Grounded in participatory design practices and inspired by Indigenous worldviews (including Aboriginal Australian, Native American, and Mesoamerican traditions) that foreground reciprocity and relational accountability, we argue that meaningful educational AI should support learning with others rather than replace them. We advance this perspective by: i) conceptualising AIED as a relational design problem grounded in reciprocity; ii) articulating key tensions introduced by GenAI in education; and iii) outlining design directions that expand the AIED design space toward reciprocity, including when not to use AI, how to define pedagogical boundaries, and how to support responsible uses of AIED innovations that sustain communities and natural environments.