Beyond Visualisation
TRAVIS as an adaptive causal intelligence for participatory systemic inquiry
Daiki Matsumura
Butterfly Lab Inc. / Institute of Science Tokyo
KEYWORD
#causal intelligence #knowledge infrastructure #participatory design
#transition design #epistemic commons
ABSTRACT
Shared systemic understanding resets with every new meeting, every language or code. TRAVIS turns meeting notes, fieldwork and workshop dialogue into causal maps that are versioned, contested and revised. Structure is computed deterministically by code, never asserted by the model; a claim survives only where its quotation is verified in the source. A second contributor never overwrites the first: disagreement is recorded, not averaged. The map does not reach completion; it accumulates, and remembers having been wrong.
CREATIVE PROCESS
TRAVIS emerged from practical overload, not theory. Leading several transition design projects at once, the volume of notes and workshop material exceeded what one person could synthesise. Building an assistant to keep one designer’s map current revealed something else: the same loop — question, response, revision — worked for groups contributing asynchronously, specialists and newcomers alike.
IMPLICATIONS & NEXT STEPS
If causal structure accumulates across projects, systemic inquiry stops depending on the presence of a skilled facilitator. Whether asynchronous participation reaches the depth of live dialogue remains untested. Next: holding contradictory models from different cultural contexts within one structure — as productive pluralism, not error to resolve.
References
Escobar, A. (2018). Designs for the pluriverse. Duke University Press.
Hovmand, P. S. (2014). Community based system dynamics. Springer.
Irwin, T., Kossoff, G., & Tonkinwise, C. (2015). Transition design provocation. Design Philosophy Papers, 13(1), 3–11.