Altruism is not data-driven: Why a story prompts more actions than statistics

On September 2015, the body of a 3-year old Syrian boy (his name was Aylan) was found on a beach in Turkey. Photos of Aylan, with a red T-shirt, blue jeans and toddler shoes, lying lifeless face down in the beach, spread virally on both the social networks and mass media. Not only that, the tragedy prompted concrete actions. Major charities received massive boosts in donation, one of them recording a 1500% increase in 24 hours. Political leaders – a lot of whom had previously grudged about the “migrants” – were moved, and in the following days countries like Germany, Austria, and Britain announced that they would take more refugees.

Some people asked, why such a huge reaction, and why only now? Anyone reading the news regularly must have known that the Syrian Civil War killed a lot of people (220,000 according to UN on January 2015), many of them in no less tragic condition than Aylan. There are millions of refugees, a lot of them crossed dangerous terrains to flee their war-torn homeland to the safety of other lands. We’ve read about previous boat accidents which drowned hundreds. Why did this tragedy make so much difference?

According to the book The Upside of Irrationality by Dan Ariely (a best-selling writer who’s a professor of psychology and behavioral economics), something like this is hardly surprising. As a rule, people don’t always use rational pros and cons analysis to make decisions, including when helping those in need.

An experiment about how data affects donation

He described an experiment where he had 3 groups of participants to donate to the hunger crisis in Africa. The first group was given the story of a specific girl named Rokia, with her close-up photo and biography. The second group was given information about the crisis, including all the awful statistics like how many people died of hunger, that millions of people suffered, and so on. The third group was given both the story of the girl and the information. Can you predict which group gave the most donation?

In the experiment, a picture and a story of a girl like this prompted more donation than the full story and statistics about how awful the hunger crisis in Africa is

It’s the first group! They only saw the specific story of a single individual, but d
onated twice more than the second group which knew the full extent of the crisis. The third group donated somewhere in between the other groups. Ariely dedicated a chapter describing this phenomenon (corroborated by other observations), and subtitled this chapter “Why we respond to one person who needs help but not to many“.

There are several reasons that explains this. For one, the driving force behind donations and helping others are mostly emotion and empathy, not calculations. Adding data and statistics to the story only serves to trigger our cold calculations and suppress our compassion.

Closeness, vividness and the drop-in-a-bucket effect

If calculation does not inspire action, what does? Ariely mentioned 3 factors. The first is closeness, either in term of location, kinship or how you can identify with the victim. The second is vividness, e.g. whether you witness the tragedy or can strongly imagine doing so. The third is what he call “drop-in-a-bucket effect”, whether you can single-handedly and effectively help, as opposed to just contributing a small insignificant aid.

These 3 factors explains why a specific tragic story is more powerful than statistics. A lot of people have kids, siblings, nephews/nieces, neighbors, etc who are toddlers like Aylan. In my case, he was roughly the same age as my son Umar, had approximately the same physical shape, and wore the kind of clothing that Umar does. Looking at the photos greatly saddens me and it’s really hard not to feel empathy.

The photo is also vivid. Looking at it you can’t help imagining the boy, how helpless he probably was in the sea, meeting his death very tragically. You don’t get this kind of vividness from statistics and numbers.

In terms of the “drop-in-the-bucket effect”, with an individual story you can make people feel they can make a difference. You can’t sort out the war in Syria, or prevent 200,000 people from getting killed there, or take care of 4 million Syrian war refugees. But you can singlehandedly help a person, or a family like Aylan’s, so that they don’t have to make those dangerous trips. In developed countries, it would only take a fraction of an average person’s savings to provide food, water and shelter for an individual refugee. Suddenly you feel like your contribution is not a drop in a bucket anymore.

What does this mean?

Knowing our weaknesses and behaviour, we can use them to be better at giving. For individuals, this means that when you feel the impulse to contribute, just follow your heart. Don’t delay, and don’t make a complicated calculations or analysis about it. Just do it! Personally, I think religion is a major influence as well. The promise of a better rewards from the All-Powerful is a very powerful motivation compared to responding to numbers.

For charities or volunteers, this means that in events like fundraising, it’s more effective to focus on individual and vivid stories that people can identify with and do something about, and also importantly avoid emphasizing on data and statistics. This may sound counter-intuitive, but people are more willing to help one person than a million people.

You can watch Ariely explains this chapter here:

The book is The Upside of Irrationality, and the chapter discussed here is Chapter 9.

Altruism is not data-driven: Why a story prompts more actions than statistics

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