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Uncertainty indicator

As explained in The Art of AI Product Development

An uncertainty indicator is a visual or linguistic signal that marks content or conclusions whose reliability is limited or unclear.

An AI-generated answer may read smoothly even when some details need checking. An uncertainty indicator uses visual or linguistic cues to show users where reliability is unclear, rather than leaving them to treat the whole output as equally dependable. section 10.2.2

Mark what needs verification

In generated text, highlight the tokens or factual claims a user should verify. The cue directs attention to specific parts of the output without requiring the user to interpret a score. section 10.2.2

Choose the cue with the user’s next action in mind. Confidence scores are another way to communicate uncertainty, but fine-grained numbers add little when users can only accept or reject an output. Footprints and source citations offer separate ways to investigate how an answer was produced. section 10.2.2

How The Art of AI Product Development covers it

How deep it goes
Defines visual and linguistic cues and illustrates highlighting, without specifying implementation or measurement.
Examples
Illustrates highlighting tokens and facts in AI-generated text for user verification.
What you can do after
Practice/perform uncertainty marking by identifying generated tokens and facts users should verify.
How it connects
Connects uncertainty indicators with confidence displays, trust calibration, footprints, and source citations.

This explainer was generated by Manning's knowledge graph from the text of The Art of AI Product Development. The section links point to the parts of the book it draws on.