Can be harnessed to build trust when *relevant* info is surfaced selectively.
Causes decision fatigue and overwhelm when users get irrelevant detail.
Information Bias was formally studied by Baron, Beattie, and Hershey in a 1988 research paper. Their study tested how people evaluate the usefulness of diagnostic information. Participants were asked to assess a fictional patient’s risk of a disease and were offered various tests, some of which provided relevant information and others that didn’t affect the outcome. The study aimed to see if people would favour more information, even when it had no bearing on the decision.
Participants often chose to receive additional information—even when told it wouldn't affect the diagnosis. This revealed a cognitive tendency to overvalue information for its own sake, leading to less efficient or slower decisions. It showed that people can confuse more data with better judgment, even when the data is irrelevant.
1.
Avoid overloading users with data that doesn’t change the outcome.
2.
Prioritise decision-critical info over completeness for its own sake.
3.
Design interfaces that simplify rather than flood the user with options.
