DTPR for AI
MakeShift 2026, School of Visual Arts
Helpful Places · May 2026
At MakeShift 2026: Accountable Tech by Design, a two-day convening on design, technology, and power at the School of Visual Arts in New York, I gave a plenary launching DTPR for AI.
Nutrition labels translate ingredients, Energy Star ratings translate efficiency, and pictograms warn us about chemicals. What about the algorithm watching you cross the street, the AI deciding your school placement, or the chatbot answering for your city? DTPR for AI extends the Digital Trust for Places and Routines standard from data collection in public space to algorithms and AI. It's an open source visual language and methodology that turns the growing patchwork of AI disclosures, from regulators, vendors, and researchers, into something anyone can read. It comes with a new schema, an icon language, REST and MCP APIs, UI components, and an agent skill that gets AI to describe AI.
The next day I ran a hands-on workshop. Participants installed the DTPR for AI agent skill on the AI agent of their choice and used it to turn a real AI disclosure into a published, visual DTPR datachain.
