August 20, 2012

Narrative Believability Trumps Probability in Decision Making

We are not statisticians by nature, but storytellers.  Why don’t we make better use of that insight in our effort to predict and understand complex problems?

British economist John Kay presented the following problem in a recent Financial Times column When Storytelling Leads to Unhappy Endings:

Linda is single, outspoken and deeply engaged with social issues. Which of the following is more likely? That Linda is a bank manager or that Linda is a bank manager who is an active feminist?

If you chose the second answer you are in good company. Most of us do. Sadly, we’re wrong. Kay explains:

Many people say that the second option is more likely. Yet, the standard response goes, this cannot be. The rules of probability tell us the probability that both A and B are true cannot exceed the probability that either A or B is true. It is less likely that someone is a female Jamaican Olympic gold medalist than that a person is female, or that a person is Jamaican, or that a person is a gold medalist. Yet even people trained in probability make a mistake with the Linda problem.  Or is it a mistake? Little introspection is required to understand what is going on. Respondents do not interpret the question as one about probability. They think it is a question about believability.

Believability, as Kay explains further, is narrative’s emblem.  In the face of the messy, multi-faceted and open-ended situations that confront us, we humans tend to produce “simplifying narratives” that help make sense of events in a way we find believable, based on our personal, cultural and historical predispositions.

Storytelling vs. Statistics

In modern societies, and nowhere more than in the United States,  our narrative predisposition is viewed with suspicion. We value rationality, which we equate with scientific and quantitative reasoning.  As a result, science is “true” and stories are “false.”

Our increasingly vast computational ability seems to have made us even more certain that we can find truth in numbers.  Nassim Taleb, whose book about improbable events The Black Swan was popular with Wall Street traders and CIA analysts, our tendency to create causal links between events—that is, to make make sense from order through simplifying narratives—is problematic.  It makes us susceptible to seeing patterns even when they may not exist, which can be as dangerous as not seeing anything at all.

George Soros displays similar dismay about how humans—especially participants n financial markets and economists—make decisions when they (inevitably) lack complete knowledge.  In such cases, he reports in a slightly horrified tone in The Crash of 2008 and What it Means, they have to “make up for it with guesswork based on experience, instinct, emotion, ritual, or other misconceptions. . .”.  In other words, people make up stories.  Yale Law Professor Ian Ayers in SuperCrunchers: Why Thinking by Numbers is the New Way to Be Smart argued that computational crunching of massive data sets, provides decision makers with the information, in opposition to “intuition” and “traditional expertise.”

Soros and Ayers are both responding reasonably to a tradition of relying on experts rather than numbers, a standing controversy in decision making scholarship, but in doing so they may be throwing out the baby with the bathwater.   Computation will never stand alone in decision making, since it is surrounded by personalities, politics and social contexts.  People decide what to measure and what to do with their findings.  It is impossible to eliminate human tendencies–including the one to create a believable story–from decision making.

Using the Storytelling Tendency to Make Better Decisions

Rather than try to dismiss our storytelling tendencies, we could seek to understand them to generate better decisions. For example, marketing professor Robert Yale has produced a Narrative Believability Scale, which breaks down the components of narrative that make it believable. In experiments, the scale appears to be a valid way to predict jury verdicts.  Yale’s work suggests that it is possible to systematize our understanding of what makes a believable narrative on which people base decisions.  Venkatesh Rao, who writes and consults on decision making and perception in a high tech world, has explored how “narrative rationality” is especially useful for  complex, open ended problems

Modern history has left us with a cultural predisposition to think that science and stories are opposites.  But they are not opposites. Indeed, they are entwined: as moral philosopher Mary Midgely observed in The Myths We Live By,  it is not the uncovering of facts that make science interesting but rather “the huge, ever-changing imaginative structure of ideas by which scientists contrive to connect, understand and interpret these facts”

Understanding the nature of narrative believability is probably the best way to reduce its distorting effects on decision making.

To learn more about how organizations can use narrative, also read:

  • If  You Want to Generate Strategies for Future Success, Start with Narratives and Metaphors (Global Strategy Forum Video), HERE
  • Overconfident Narratives Skew Decision Making, HERE
  • Communities and the New Narratives they Need, in Governing Magazine: HERE
  • How Narratives Drive Resources following Public Crises, in The Globalist, HERE

Learn more about how your organization can benefit from a Narrative Audit HERE.


3 thoughts on “Narrative Believability Trumps Probability in Decision Making

  1. Paul,

    Good to hear from you and thank you for bringing up this interesting project in which events are collectively predicted. If narrative is viewed as an unfolding event, one that we are always collectively “writing” in our public spaces, it makes sense that both of your suggestions are true. The collective narrative may override substantially some of the outlying predictions, but those may live on too, as substrata of the collective mainstream story of what is happening.

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