Two-Eyed Seeing: Not Compromise, but Making Both Ways of Knowing Visible
Original Chinese title: Two-Eyed Seeing：不是折衷，而是讓兩種知識都能看見
This article uses education, AI, research, and public policy as contexts to explain that Two-Eyed Seeing is not a compromise slogan, but a higher-order methodology that allows Indigenous traditional knowledge and Western science each to retain their integrity.
Yuan Media AI Editorial Desk
Two-Eyed Seeing is not about using Indigenous traditional knowledge to decorate science, but about redesigning who has the authority to define problems.
One: Adding two ways of knowing together does not make it Two-Eyed Seeing
Two-Eyed Seeing is often translated as seeing with both eyes, bidirectional knowledge, or dual perspective. These translations are acceptable, but the greatest danger is that it gets framed as a gentle compromise: a little Indigenous culture on the left, a little Western science on the right, a few sentences of respect for diversity in the middle, and then everyone poses for a photo, wraps up the project, and collects their grant.
That is not Two-Eyed Seeing; that merely treats Indigenous traditional knowledge (norms and taboos) as seasoning in a proposal. True bidirectional knowledge is not a platter but allows both sets of “knowledge” to retain the capacity to judge the world on their own terms. It does not require Indigenous traditional knowledge to be first translated into legitimate language by science, nor does it require science to abandon evidence and method. What it demands is: on any given problem, are we willing to acknowledge that more than one way of knowing has the right to narrate, question, set boundaries, assess risk, and determine use?
This difference matters greatly. Mainstream education most often places Indigenous traditional knowledge into science curricula as “local case studies.” It looks progressive, yet the power structure remains unchanged: science stays the subject, Indigenous knowledge becomes merely an example. Two-Eyed Seeing challenges precisely this seemingly friendly subordinate relationship.
Two: Western science excels at measurement; traditional knowledge excels at narrative and recognizing relationships
Western science’s strengths lie in measurement, verification, controlling variables, and building reproducible evidence. These capabilities are invaluable, especially in medicine, disaster response, environmental monitoring, and engineering governance. But if you assume all knowledge must grow into this shape, problems arise.
Indigenous traditional knowledge often excels at narrative and recognizing relationships: the relationship between people and land, plants and animals and seasons, dreams and actions, taboos and community safety, care and ethics. These may not always be captured by a single experimental design, yet that does not mean they lack method. In fact, these methods exist within long-term observation, oral memory, ritual norms, kinship responsibilities, and environmental experience.
Therefore, bidirectional knowledge is not about comparing who is more advanced; it asks: on which problems can one way of knowing see blind spots the other cannot? Science avoids romanticization; traditional knowledge avoids abstraction from context. Science provides testing tools; traditional knowledge reminds us that tools must not overstep boundaries. Their meeting should not be one swallowing the other, but jointly enhancing judgment to amplify effects.
Three: What education needs most is not textbooks but ways of seeing
Current education loves to talk about multiculturalism, often stopping at textbook supplements: add a myth, add an image of dress, add a segment on festival introduction, as if mere presence equals respect. Yet the problem lies in that if students still interpret these contents through a single mainstream logic, then diverse textbooks can become tools of assimilation.
For example, dream interpretation reduced to a simple psychology case study, traditional medicine simplified to plant efficacy, ritual ceremony turned into performance art—culture is placed in textbooks while its original authority structure is dismantled. Students learn many knowledge points but lose reverence for Indigenous traditional knowledge (norms and taboos).
The value of Two-Eyed Seeing in education lies mainly in training students to practice switching ways of seeing. Not only ask “what does this cultural content represent,” but also ask “who has the right to interpret it,” “is this interpretation suitable for public sharing,” “what framework am I using to understand it,” or “is my framework currently obscuring it.” Only such education can move from cultural introduction toward the narrative ethics of knowledge.
Four: AI systems can become testing grounds for bidirectional knowledge
AI is the best testbed because it amplifies our knowledge biases. If data sources lean mainstream, AI will explain Indigenous culture in a mainstream tone; if annotators lack cultural understanding, AI learns incorrect classifications; if evaluation metrics focus only on answer fluency, AI becomes a polite error machine.
Therefore, putting Two-Eyed Seeing into AI is not about writing one system prompt and finishing. It requires comprehensive design across data, annotation, retrieval, answering, refusal, evaluation, and update mechanisms. For instance, regarding the same traditional medicine question, the system must not only answer “how it is understood culturally” but also remind “no diagnosis or treatment advice provided”; for the same dream interpretation, the system must not only organize possible contexts but also mark restrictions on different ethnic groups, situations, and what cannot be publicly shared.
This is precisely the direction Yuan Media AI can demonstrate: not packaging AI as an omniscient cultural teacher, but designing it as a knowledge platform that acknowledges limits, marks sources, and respects community authority.
Five: Conclusion: True seeing means neither side gets translated into disappearance
The most moving aspect of Two-Eyed Seeing is not the peaceful handshake between two ways of knowing, but reminding us that true understanding sometimes must allow each to retain parts that cannot be fully translated.
If Indigenous traditional knowledge only counts as knowledge after being proven by science, that is not respect; if Western science only has warmth when wrapped in cultural narrative, that is not a method. True “bidirectional knowledge” keeps science rigorous while preserving the ethics, context, and narrative rights of Indigenous traditional knowledge.
In today’s AI era, this methodology is especially important. Machines excel at “translation” and most easily translate everything into loss of difference. The task of Two-Eyed Seeing is to preserve the capacity to “see differences” in a world of rapid generation.
AI use and content-safety disclosure
This article was compiled and edited through the Yuan Media AI editorial process; content involving Indigenous traditional knowledge, medicine, psychology, or culture is for educational and public discussion only and does not replace professional diagnosis, treatment, counseling, emergency assistance, or community authorization.