Tool/Heuristic/No. 0199

Consider-the-Opposite Strategy

Before sending a furious reply, you jot down three reasons your coworker’s message might not be an insult.

Also called Consider the Opposite · Considering the Opposite

a tool: pick it up

Evidence: Useful, modest evidence
Read: 6 min
Links: 27 connections
Useful when: Deciding under uncertainty · Evaluating a claim · Forecasting · Judging people and hiring · Reading data and statistics

01You've seen this when…

in life
Your friend cancels dinner again, and you start treating it as proof they don’t care. Before withdrawing, you list other explanations and notice that every cancellation falls on a caregiving night.
at work
You favor the familiar vendor. Before approving the renewal, you write the strongest case for switching and discover that your reliability comparison excludes the last two outages.
out in the world
You oppose a proposed bus lane because you expect worse traffic. Before submitting your comment, you look for evidence that giving buses priority could move more people through the corridor.

02The idea

Once a judgment feels right, the mind becomes good at defending it. Supporting details seem relevant. Awkward details seem exceptional. You can examine plenty of evidence and still give only one conclusion a fair hearing.

The consider-the-opposite strategy interrupts that process. Deliberately generate credible reasons your initial judgment might be wrong. Then examine whether those reasons hold up.

The point isn’t to become indecisive or switch sides. It’s to make an alternative available before you evaluate the evidence. If you think a colleague is careless, consider what would support the possibility that unclear instructions caused the mistake. If you think a price is reasonable, consider why it might be too high.

This targets confirmation bias, especially the myside bias that makes our own position easier to defend than examine. A general intention to be objective leaves the search process largely unchanged. A specific contrary possibility gives you something different to look for.

Use one prompt: “What would I expect to see if my first judgment were wrong?” The answer should identify evidence you can check to distinguish the explanations.

03How to use it

Write down the judgment before defending it. Make it specific enough to challenge. A prediction that a supplier will miss the deadline gives you a claim to test. A vague feeling that the supplier is bad leaves the concern unclear. Record your confidence if the decision matters; a decision journal helps preserve what you actually believed.
Choose a credible contrary possibility. Keep the challenge focused on the central conclusion and set irrelevant details aside. For the supplier, consider that delivery could be on time despite the warning signs. A plausible alternative is enough; a perfect logical opposite is optional.
Generate concrete reasons it could be true. Try two or three reasons. Look for overlooked evidence and ask whether a different explanation fits or an assumption may fail. Tie each reason to this situation. Generic reminders that anything is possible leave the judgment unchanged.
Look for a fact that separates the explanations. Ask what you could observe that would be more likely under one explanation than the other. A production milestone may distinguish a late supplier from one that merely communicates poorly. This is the practical spirit of a falsification test.
Update in proportion to the evidence. Let the quality of the reasons determine the update, regardless of how many you produced. Strong contrary evidence should move your judgment; weak possibilities should move it little. This resembles Bayesian updating. Automatically splitting the difference gives both judgments equal weight.

04A worked example

Consider an illustrative hiring decision. A manager interviews a data analyst whose answers are brief and restrained. The manager’s first assessment is that the candidate communicates poorly and should be rejected.

Before finalizing the score, the manager considers the opposite: the candidate may communicate clearly when the task and audience are well defined. Interview nerves or overly broad questions may have shaped the answers, and the candidate may be in the habit of answering only what was asked.

What it looks like Sensible screening. The job requires explaining findings to people outside the analytics team, and the interview felt difficult.

What’s actually going on A narrow observation has become a broad conclusion. The alternative explanations are hypotheses awaiting evidence, and they prompt a better search. The manager revisits the candidate’s writing sample and finds a clear explanation of a difficult result. The team broadens its assessment beyond interview manner by giving both finalists the same short exercise: explain an analysis to a nontechnical colleague. The restrained candidate performs well enough to stay under consideration.

What made it work The manager generated a testable alternative and collected comparable evidence. The exercise left uncertainty about both the first impression and the quality of a future hire. It kept one ambiguous interaction from deciding the outcome.

05When to reach for it

Your conclusion arrives before your investigation. You already know which applicant, explanation, investment, or policy you prefer.
A judgment concerns someone’s motives. The same behavior can fit indifference, confusion, fear, or competing obligations.
All your reasons point in one direction. This can reflect strong evidence, but it can also reflect a one-sided search.
An initial number dominates the discussion. Before accepting a budget or valuation, consider why that starting figure might be inappropriate.
The decision has meaningful consequences. Spend the effort where a mistaken judgment would cost money, opportunity, trust, or safety.

06When it misleads

You confuse possibility with probability. An alternative can be imaginable and still very unlikely. Keep established evidence and relevant background rates in view. Treat manufactured doubt about a well-supported conclusion as a misuse of the strategy.
You give every position equal weight. An alternative’s credibility depends on the evidence supporting it. Avoid false equivalence: evidence still gets to favor one side strongly.
You invent a weak opponent. A flimsy contrary explanation makes your original position feel stronger while leaving it untested. Steelmanning helps represent an opposing argument fairly; considering the opposite uses contrary possibilities to examine your own judgment. They overlap, but have different aims.
You repeat the exercise without learning anything. More hypothetical reasons can become delay or rumination. Put a time limit on the exercise and identify one useful check.
The argument is good but the environment is stronger. An individual prompt may be too weak to overcome rewards for defending the boss’s plan or a team that punishes dissent. Red teaming can make challenge a formal assignment, though it still needs permission to matter.

07Roots

Charles Lord was studying an uncomfortable problem: people could inspect the same research and give it different grades depending on whether they liked its conclusion. In a 1979 experiment with Lee Ross and Mark Lepper, people with strong views about capital punishment read studies pointing in opposite directions on whether it deterred murder. The mixed packet offered something for each side to welcome and something to attack. Participants tended to judge evidence supporting their existing position more favorably.

Supplying both sides of an issue left biased evaluation in place. The researchers needed a way to change how people evaluated the material already in front of them.

In 1984, Lord, Lepper, and Elizabeth Preston tested a more pointed instruction: consider the opposite. In their capital-punishment experiment, participants were prompted to consider whether they would evaluate the research similarly if its results pointed the other way. This targeted instruction reduced biased evaluation more effectively than a general instruction to be fair and unbiased.

The technique later traveled into research on numerical judgments. Thomas Mussweiler, Fritz Strack, and Tim Pfeiffer showed that considering contrary reasons could reduce anchoring, where a starting number pulls later estimates toward it. Across these settings, the useful move was changing which possibilities people actively examined while leaving room for the evidence to favor one conclusion.

08How solid is this?

Controlled experiments support reductions in biased evaluation and anchoring when people receive specific contrary-thinking prompts. Evidence is stronger for immediate, task-specific judgments than for lasting improvements across everyday decisions.

10Origin and sources

Charles G. Lord, Mark R. Lepper, and Elizabeth Preston developed and experimentally tested the strategy in 1984 as a corrective for biased social judgment.

[1]Lord, C. G., Lepper, M. R., & Preston, E. (1984). Considering the opposite: A corrective strategy for social judgment. Journal of Personality and Social Psychology, 47(6), 1231–1243.
[2]Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098–2109.
[3]Mussweiler, T., Strack, F., & Pfeiffer, T. (2000). Overcoming the inevitable anchoring effect: Considering the opposite compensates for selective accessibility. Personality and Social Psychology Bulletin, 26(9), 1142–1150.

Suggest an edit· Updated 2026-10-02