Information Bias

Category: Decision Making

The tendency to seek information even when it cannot affect action.

How it works

We carry a deep, mostly-unexamined belief that more information is always better, that the responsible, intelligent move is to gather one more data point before acting. Information bias is what happens when that belief runs past its usefulness: you seek out facts that cannot possibly change what you do, simply because acquiring them feels prudent.

The mechanism is partly a confusion between feeling informed and being better off. Collecting data is concrete and reassuring; it postpones the scary, irreversible moment of deciding. So the search itself becomes a comfort blanket, a way to look and feel diligent while actually avoiding commitment. It also offers a defensive alibi: 'I gathered everything available' protects you from blame if things go wrong.

The rational test is brutally simple and almost never asked: for every possible result of this inquiry, would my action be the same? If yes, the information has zero decision value no matter how interesting it is. We rarely run this test because curiosity and the more-is-better heuristic answer the question for us before we even pose it.

Where you'll see it

• A patient pushes their doctor for an expensive extra scan even though the doctor has already said the treatment will be identical regardless of what it shows, the result can't change the plan, only the bill and the anxiety.
• An investor refreshes the stock ticker forty times a day on a holding they've committed to keep for ten years; the minute-by-minute price can't alter a decade-long plan, but checking *feels* like staying on top of it.
• A hiring manager insists on a fourth interview round for a candidate everyone already wants to hire, gathering more 'signal' that won't reverse a decision that's effectively made, while the candidate accepts a faster offer elsewhere.

Where it comes from

Information bias was demonstrated in a 1988 study by Jonathan Baron, Jane Beattie, and John Hershey using diagnostic-reasoning problems. They presented participants with medical scenarios in which a particular test, though informative-sounding, could not change which treatment was optimal, yet people consistently chose to run the test anyway. The work showed that subjects valued information for its own sake, divorced from its actual bearing on the decision, and helped formalize the idea that the worth of information should be judged strictly by whether it can alter a choice.

How to counter it

Before any search, ask the decision-value question: 'If this comes back A, what do I do? If it comes back B, what do I do?' If the answer is the same, stop, you've already decided, and you're just delaying. Write the action down first, then see whether more data could move it.

Set a gathering budget in advance: a deadline or a fixed number of sources. Open-ended research expands to fill all available time and anxiety; a budget forces you to convert information into a decision rather than hoarding it.

Distinguish curiosity from decision-making. It's fine to want to know things, just don't let an interesting-but-inert fact hold a real choice hostage. Park genuine curiosities in a 'later' list and make the call with what's actually load-bearing.

The tell

You're doing it when you're still researching a choice you'd make identically no matter what the research turns up.

Related biases

• Anchoring Bias
• Sunk Cost Fallacy
• Framing Effect
• Zero-Risk Bias
• Decoy Effect
• Endowment Effect

Featured in

• How Rational Are You, Really? (take the 5-minute bias test)
• The Complete List of 58 Cognitive Biases (with real examples)

Common questions

What is Information Bias?

Information Bias is the tendency to seek out information even when it cannot affect what you do. Under Information Bias, people gather extra facts because acquiring them feels prudent, not because the facts could change any decision or action. It is the point where the pursuit of data runs past its actual usefulness.

Why does Information Bias happen?

Information Bias happens because we carry a deep, mostly unexamined belief that more information is always better and that the responsible, intelligent move is to gather one more data point before acting. Information Bias occurs when that belief runs past its usefulness, so we collect facts that cannot possibly change our course simply because acquiring them feels prudent and reassuring.

What is an example of Information Bias?

A clear example of Information Bias is a patient pushing their doctor for an expensive extra scan even though the doctor has already said the treatment will be identical no matter what the scan shows. Because the result cannot change the plan, the scan adds only cost and anxiety, which is exactly the trap of Information Bias.

How do you avoid Information Bias?

To avoid Information Bias, ask the decision-value question before any search: 'If this comes back A, what do I do? If it comes back B, what do I do?' If the answer is the same either way, stop, because you have already decided and are only delaying. A practical safeguard against Information Bias is to write the action down first, then check whether more data could actually move it.

What is the difference between Information Bias and Sunk Cost Fallacy?

Information Bias is seeking data that cannot change your decision, wasting effort on inputs before acting. Sunk Cost Fallacy is continuing a course of action because of resources already spent, letting past costs distort a forward decision. Information Bias looks forward at useless new information, while Sunk Cost Fallacy looks backward at irrecoverable past investment.

References

1. Baron, J., Beattie, J., & Hershey, J. C. (1988). Heuristics and biases in diagnostic reasoning: II. Congruence, information, and certainty. Organizational Behavior and Human Decision Processes, 42(1), 88-110
2. Baron, J., & Hershey, J. C. (1988). Heuristics and biases in diagnostic reasoning: I. Priors, error costs, and test accuracy. Organizational Behavior and Human Decision Processes, 41(2), 259-279
3. Nelson, J. D. (2005). Finding useful questions: On Bayesian diagnosticity, probability, impact, and information gain. Psychological Review, 112(4), 979-999
4. Baron, J. (2008). Thinking and Deciding (4th ed.). Cambridge University Press