Consider the opposite

type: technique · origin: study · evidence: supported · themes: judgements and probabilities

Claim assessed: Asking what you would believe if things were the other way round reduces judgement errors.

Published 2 October 2026 · how we work

In short

Considering the opposite means asking yourself, before a conclusion, what you would think if the evidence pointed the other way, or why you might be wrong. Lord, Lepper and Preston (1984) proposed the technique against the tendency to judge evidence in favour of one’s own view. It worked better than a simple call to be objective. Later studies found effects on anchoring and other judgements too, but a 2023 study gave mixed results.

What it says

The idea. Lord, Lepper and Preston (1984) start from an observation they attribute to Francis Bacon: many judgement errors come from failing to consider the possibilities that contradict what we believe at the moment. If someone is prompted to consider the opposite, they should judge less one-sidedly.

The first experiments. Lord et al. (1984) tested the idea in two areas: how people judge evidence on social issues, and how they test their impressions of someone’s personality. In one of the experiments they repeated the classic death penalty study, in which supporters and opponents found the study that confirmed their view more convincing. Participants in one group were asked to think about how they would have rated each study’s method if its results had been exactly the opposite. Others were only asked to be as objective and impartial as possible. The call to be objective didn’t help. Considering the opposite reduced both the biased judgement and the polarisation of views.

On anchoring. Mussweiler, Strack and Pfeiffer (2000) asked car experts to estimate the value of a ten-year-old car, after the experimenter gave his own estimate, either low or high. The anchor influenced their estimates. But those asked to find arguments for why the anchor was inappropriate were influenced less. This matters because, as Mussweiler, Englich and Strack (2004) note, explicit warnings about anchoring, even including the direction of the distortion, do not reduce the effect.

Not just the opposite. Hirt and Markman (1995) showed that it need not be the opposite: any plausible alternative makes you consider more possibilities and reduces the error. The alternative does, however, need to seem plausible.

Data from Greitemeyer (2023), statistics reported in the text. The lower the value, the less the rating depended on the initial view.

A recent test. Greitemeyer (2023) tested two versions of the technique on pandemic topics in 2022. Participants read summaries of two made-up studies, one for and one against their view, and rated them.

Study 1, 262 participants, on vaccine effectiveness. Some were asked to give at least three reasons why each study might have reached a wrong conclusion. This did not reduce the bias in rating the studies, but it brought the two camps’ final views slightly closer.
Study 2, 250 participants, on the need for restrictions. Some were asked to rate each study as if it had found exactly the opposite. This greatly reduced the bias, though it didn’t eliminate it. The technique also reduced participants’ impression that their views had become more extreme, but it didn’t change their actual views.

The author notes that the two studies also differed in topic: beliefs about the vaccine were stronger. The techniques might work less well when beliefs are strong.

Example

You read an article that confirms exactly what you believed about a diet, and it seems very well done. You ask yourself: if the same study, with the same method, had found the opposite, would I have thought it just as good? If the answer is no, you look more closely at the method. The example is an illustration, not a study cited here.

How to apply it

The steps below are a practical way of applying it that we propose, based on the cited studies.

Don’t rely on the intention to be objective. In Lord et al.’s study, the call to be impartial didn’t help.
Flip the result. When you judge a piece of evidence, ask yourself how you would judge it if it had shown the opposite. This was the version that worked in both studies that tested it on evidence.
When you start from a number, look for reasons it is wrong. In anchoring, arguments against the anchor reduced the effect.
The alternative must be plausible. It needn’t be exactly the opposite, but it must seem possible to you.
Expect a partial effect. Even at best, the bias dropped; it did not disappear.

Limits and nuances

Few large studies. We found no meta-analysis of this technique. The studies cited have a few hundred participants at most.
The results are mixed. In Greitemeyer (2023), the “give reasons the study is wrong” version did not reduce the bias, while the “rate it as if it had shown the opposite” version did. The two studies also differed in topic, so we can’t be sure which version is better.
The effect on views is small or absent. In 2023, considering the opposite changed how evidence was rated, but not the final view.
Convenience samples. The 2023 participants were recruited through social networks and a university mailing list, many of them students.
What we read. Greitemeyer (2023), in the copy from the University of Innsbruck repository, and the chapter by Mussweiler, Englich and Strack (2004), from the University of Cologne site, we read in full. For Lord et al. (1984), Hirt and Markman (1995) and Mussweiler et al. (2000) we read the abstracts. The details of the 1984 and 2000 experiments come from Greitemeyer’s (2023) description.

Sources

Charles G. Lord, Mark R. Lepper, Elizabeth Preston (1984). Considering the opposite: A corrective strategy for social judgment
Edward R. Hirt, Keith D. Markman (1995). Multiple explanation: A consider-an-alternative strategy for debiasing judgments
Thomas Mussweiler, Fritz Strack, Tim Pfeiffer (2000). Overcoming the inevitable anchoring effect: Considering the opposite compensates for selective accessibility
Thomas Mussweiler, Birte Englich, Fritz Strack (2004). Anchoring effect
Tobias Greitemeyer (2023). Counter explanation and consider the opposite: Do corrective strategies reduce biased assimilation and attitude polarization in the context of the COVID-19 pandemic?