Progress precision must match task predictability; false precision misleads

What it is

Calibrated progress precision aligns decimal places, percentage granularity, and time range with actual task predictability. “83%” or a second-precise completion time for uncertain navigation or search falsely implies measurement and model accuracy.

Why it happens

Fine numbers carry authority, and display resolution is mistaken for estimate accuracy. Smooth animation can fill unknown work until prediction fails, causing reversal or a frozen final step. Stages, broad intervals, and qualitative confidence preserve uncertainty for realistic planning.

Studying it

At equal underlying error, precise point, rounded value, interval, and stage can be compared on waiting plans, calibrated trust, surprise, repeated checking, and uncertainty comprehension. Error-to-display-granularity and estimate revisions should be reported. Preference for precision is not decision quality.

Where it stops holding

Repeated controlled cycles can justify precision; new external dependencies remove it. Very wide intervals can become useless and need causal explanation. Independently guaranteed safety countdowns should remain exact.

Applying it

• Derive display granularity and range from historical error, withholding unsupported significant digits.
• Preserve revision history and explain changes rather than silently reversing a bar.
• Compare users' leaving, intervention, and resource plans with actual completion to evaluate decision loss.

Related

• Same group: X3.05.1 Long tasks need visible progress rather than silent execution · X3.05.2 Remaining-time estimates support waiting decisions better than completion percentage alone · X3.05.3 Stalled progress should explain why rather than resemble failure
• Adjacent: X3.08 Communicating uncertainty · X3.07 Explainable decision basis
• Search terms: false precision · progress uncertainty · calibrated estimate