Cognitive biases that shape how we read the news

We tend to seek, notice and remember information that agrees with what we already believe, and to scrutinise information that disagrees. Given a report that supports a view you hold, you may accept it quickly; given one that challenges it, you may look for flaws. Online, where algorithms show you more of what you engage with, the effect can be amplified.

People judge how common or likely something is by how easily examples come to mind. Dramatic events such as plane crashes, shark attacks and terror attacks are covered intensively, so they feel more common than they are, while quiet, slow causes of harm, such as heart disease or road accidents, are underestimated. Because news is by definition about what is unusual, a steady diet of it can leave you with a picture of the world that is more frightening than the figures support.

Bad news grabs attention more than good news, which is probably a legacy of a time when noticing threats helped survival. Headlines have learned to exploit this. Gradual improvements, such as falling child mortality or rising literacy, never have a day on which they are news, and so are easy to miss.

The first number you see tends to influence your judgement of later ones, even when it is arbitrary. A claim that a measure will cost a billion rupees seems more reasonable after you have been told that it could cost ten. Framing works similarly: a treatment with a 90 per cent survival rate sounds better than one with a 10 per cent mortality rate, although they are the same.

After an event, we tend to feel that it was predictable all along, which is hindsight bias, and which makes people in the past, and sometimes experts, look more foolish than they were. Survivorship bias is the habit of studying only the successes that are visible. Advice taken from successful companies tells you little if the many that followed the same strategy and failed are not counted.

Statements that we have heard before feel more true, whether or not they are, a result called the illusory truth effect. Forwards that circulate on messaging apps use this, as do headlines repeated across outlets. We also trust the opinions of people we see as part of our group, and discount those of outsiders, which can make us accept a claim because of who said it, not on its merits.

No technique is foolproof, but a few habits make a difference:

• Slow down on stories that make you very angry or very pleased; strong feelings are a prompt to check.
• Ask what the evidence would look like if the claim were false, and whether you have looked for it.
• Check base rates: how common is the thing, in the first place? Our guide to Bayes' theorem explains why this matters.
• Read about important events in more than one outlet, including ones whose tone you do not like.
• Keep a record of your own predictions, and check how often you were right.

The study of biases is itself a science, and it has had its corrections. Some well-known effects from the early studies, such as the idea that willpower is a limited resource, have not held up well when others tried to repeat them, and the popular picture of two systems of thought, a fast one and a slow one, is a useful metaphor, not a map of the brain. The work of Daniel Kahneman and Amos Tversky, for which Kahneman received the Nobel prize in economics in 2002, rests on firmer ground. Treat any single finding as a reason to look, not as the last word.

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• How science works: hypotheses, evidence and peer review

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