Transparent AI
Transparent AI is the design paradigm in which AI systems present not only their outputs but the reasoning that produced them — the alternatives considered, the tradeoffs made, the evidence weighted, the uncertainties acknowledged. The paradigm contrasts with the dominant current approach, in which models produce confident, polished outputs that conceal the reasoning by which they were generated and thereby present themselves as finished rather than as work products available for evaluation. Transparent AI supports the user's learning and judgment; opaque AI substitutes for it.
In The You On AI Field Guide
The architectural features of transparent AI include: explicit reasoning traces that show the model's intermediate steps, not just its final output; explicit acknowledgment of uncertainty, distinguishing confident claims from tentative ones; attribution of sources, linking generated content to the training data that supports specific claims; presentation of alternatives considered and rejected; and interfaces that invite challenge rather than discouraging it.
Each of these features is technically feasible. Chain-of-thought prompting demonstrates that models can produce reasoning traces.