All-Seeing AI

fallacy

Cherry picking

Also called: Suppressed evidence, Fallacy of incomplete evidence

Cherry picking presents only the evidence that supports a conclusion and ignores the evidence that contradicts it.

How it works

Every individual fact quoted may be true, but the selection creates a false overall picture. It is common with statistics, time ranges and quotations.

Examples

"Sales rose 40% in March!" (They fell in every other month of the year.)
One good month is presented as if it reflected the trend.
Quoting the one study that found no effect while omitting the dozen that found one.
The weight of evidence points the other way.

How to spot it

  • Unusual start and end dates for a chart.
  • A single study or example where many exist.
  • No mention of contrary evidence.

How to respond

  • Ask for the full data set or time range.
  • Look for reviews that summarise all the evidence.
  • Present the contrary evidence and ask how it fits.

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