Information bias (psychology)

Information bias is a cognitive bias to seek information when it does not affect action. People can often make better predictions or choices with less information: more information is not always better. An example of information bias is believing that the more information that can be acquired to make a decision, the better, even if that extra information is irrelevant for the decision.^[1]

Example[]

In an experiment (Baron, Beattie & Hershey 1988), subjects considered this diagnostic problem involving fictitious diseases:^[2]

A female patient is presenting symptoms and a history which both suggest a diagnosis of globoma, with about 80% probability. If it isn't globoma, it's either popitis or flapemia. Each disease has its own treatment which is ineffective against the other two diseases. A test called the ET scan would certainly yield a positive result if the patient had popitis, and a negative result if she has flapemia. If the patient has globoma, a positive and negative result are equally likely. If the ET scan was the only test you could do, should you do it? Why or why not?

Many subjects answered that they would conduct the ET scan even if it were costly, and even if it were the only test that could be done. However, the test in question does not affect the course of action as to what treatment should be done. Because the probability of globoma is so high with a probability of 80%, the patient would be treated for globoma no matter what the test says. Globoma is the most probable disease before or after the ET scan.

In this example, we can calculate the value of the ET scan. Out of 100 patients, a total of 80 people will have globoma regardless of whether the ET scan is positive or negative. Since it is equally likely for a patient with globoma to have a positive or negative ET scan result, 40 people will have a positive ET scan and 40 people will have a negative ET scan, which totals to 80 people having globoma. This means that a total of 20 people will have either popitis or flapemia regardless of the result of the ET scan. The number of patients with globoma will always be greater than the number of patients with popitis or flapemia in either case of a positive or negative ET scan so the ET scan is useless in determining what disease to treat. The ET scan will indicate that globoma should be treated regardless of the result.

References[]

^ Vaughan, Michael (2013). The Thinking Effect: Rethinking Thinking to Create Great Leaders and the New Value Worker. Nicholas Brealey Publishing. p. 29. ISBN 978-1-85788-933-8.
^ Baron, Jonathan (2006). "Information bias and the value of information". Thinking and Deciding (4th ed.). Cambridge University Press. p. 177. ISBN 978-0-521-68043-1.

Studies[]

Baron, Jonathan; Beattie, Jane; Hershey, John C (1988). "Heuristics and biases in diagnostic reasoning" (PDF). Organizational Behavior and Human Decision Processes. 42 (1): 88–110. doi:10.1016/0749-5978(88)90021-0. Archived from the original on 2016-03-05.CS1 maint: bot: original URL status unknown (link)

[Vaughan2013-1] Vaughan, Michael (2013). The Thinking Effect: Rethinking Thinking to Create Great Leaders and the New Value Worker. Nicholas Brealey Publishing. p. 29. ISBN 978-1-85788-933-8.

[Baron2006-2] Baron, Jonathan (2006). "Information bias and the value of information". Thinking and Deciding (4th ed.). Cambridge University Press. p. 177. ISBN 978-0-521-68043-1.

[1]

[2]

v t Biases
Cognitive biases	Actor–observer Acquiescence Ambiguity Anchoring Attentional Attribution Authority Automation Belief Blind spot Choice-supportive Confirmation Compassion fade Congruence Courtesy Cultural Distinction Dunning–Kruger Egocentric Emotional Extrinsic incentives Fading affect Framing Frequency Correspondence Halo effect Hindsight Horn effect Hostile attribution Impact Implicit In-group Mere-exposure effect Negativity Normalcy Omission Optimism Out-group homogeneity Outcome Overton window Precision Present Pro-innovation Response Restraint Self-serving Social comparison Status quo Time-saving Trait ascription von Restorff effect Zero-risk In animals
Statistical biases	Estimator Forecast Healthy user Information Psychological Lead time Length time Non-response Observer Omitted-variable Participation Recall Sampling Selection Self-selection Social desirability Spectrum Survivorship Systematic error Systemic Verification Wet
Other biases	Academic Funding FUTON Inductive Infrastructure Inherent In education Media False balance Vietnam War Norway South Asia Sweden United States Arab–Israeli conflict Ukraine Net Political bias Publication Reporting White hat
Bias reduction	Cognitive bias mitigation Debiasing Heuristics in judgment and decision-making
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Information bias (psychology)

Contents

Example[]

See also[]

References[]

Studies[]