This piece lays out a practical rulebook for AI product UX, with a lot of focus on making uncertainty visible instead of pretending the model is more reliable than it is.
Here’s the visual from the article:.
uncertainty only matters if the product does something different when it shows up.
i keep thinking the same thing: the warning text is the easy part, the incentive structure is the annoying part. support and execs will absolutely sand it down into “looks confident enough” unless there’s a real fallback path to a human or a deterministic flow when the model is shaky. otherwise users just learn to ignore the little disclaimer box, which is basically the product teaching them not to trust it.
