Fooled by Narrative

John grew up solidly middle class, in a solidly middle-class town in Middle America, to solidly middle-class parents, where he went to a solidly middle-class school.

He had a nice upbringing; his father worked in IT for the biggest computer software company in the state, and his mother was an elementary school teacher. John grew up with a deep love for learning and computers, and especially learning about computers. You can say it was in his blood.

John didn’t have many friends in school, but that was fine by him — he had his books and his computers, and especially his books about computers. Apart from books about computers, John loved sci-fi and was often lost in the utopian worlds of some far off galaxy.

Despite his solidly middle-class upbringing, John demonstrated a proclivity for computer science, coding his first software program when he was just 12 years old. His prodigal abilities allowed him to develop a hankering for entrepreneurship, as well, and at age 16 he created his first Internet business.

After graduating high school a year early, it was off to Stanford, where John, for the first time in his young life, finally felt belonging. It was there in his college dorm that he met Eric, who quickly became his best friend and co-founder.

John and Eric’s business catapulted to success, and the rest is history.


We tell stories to make sense of an over-complicated world, with much too much information to process. The stories we tell aim to help us make sense of the sequence of events we experience — to determine causality — in a world filled with randomness.

Our inclination to create narratives to explain events, however, increases the likelihood that we use stories inaccurately, to provide a nice, comforting explanation for something that cannot or should not be explained nicely and comfortably. This cognitive bias is called the narrative fallacy.

As Nassim Nicholas Taleb explains in The Black Swan— 

The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship upon them. Explanations bind facts together. They make them all the more easily remembered; they help them make more sense. Where this propensity can go wrong is when it increases our impression of understanding.

Taleb argues in The Black Swan, as well as in his preceding book Fooled by Randomness, that we humans, given the complexity of the world and our inclination to use heuristics greatly underestimate or are unaware of the role randomness plays in the world.

Consider the fictional story above, of John the entrepreneur. Why is he successful? There is a myriad of factors, of which his upbringing is but one. But randomness, without question, plays a significant role — John winding up in the same dorm as his future business partner Eric is evidence of that.

There is another phenomenon at play that makes stories like John’s so compelling — the heuristic known as representativeness. As Daniel Kahneman and Amos Tversky illustrate in “Judgments under Uncertainty”, we assess the probability that a person is a particular occupation “by the degree to which [that person] is representative of, or similar to, the stereotype [of that occupation]”.

My guess is that, while reading the introduction to John, you assumed John is a tech entrepreneur. After all, his story of prodigal programming abilities, introversion and Stanford schooling are representative of a tech entrepreneur. But go back and read that first section — notice how we don’t actually know what business John and Eric started. Maybe they started a fashion brand for nerds. Or a pet food company. Who knows?


If you were just fooled by narrative, don’t feel bad — even the most esteemed individuals fall victim, as well.

Just last weekend I watched the incredible story of Elizabeth Holmes and Theranos, as told in HBO’s “The Inventor: Out for Blood in Silicon Valley”. The documentary, with the benefit of hindsight, demonstrates just how Holmes leveraged representativeness to make the world believe her and her company were the real deal.

Holmes in interviews shared that “growing up her best friends were books”; that she wears black turtlenecks in the morning to cut down on decisions in the morning (but that “she had worn black turtlenecks since she was 7”); she was a Stanford dropout; she told stories of the higher purpose of Theranos and their mission, and of the heartbreak of her uncle passing away of cancer too soon; she was described as brilliant (or at least appeared to be so) but also viewed as a little quirky, as many tech moguls are; she appeared on the front page of esteemed magazines; Theranos’ offices were in the famed Stanford Research Park; their odes to Thomas Edison and Yoda tell further stories on their behalf.

If it looks like a duck, swims like a duck, and quacks like a duck, then it probably is a duck.

However, for the careful readers, you’ll also notice that I’ve just now fallen victim to the narrative fallacy myself. I’ve packaged a nice, comfy story — of Holmes’ representativeness — to explain why she was able to defraud so many investors. The reasons why, of course, are much greater than merely her representativeness.

Randomness clearly played a large role in Homes’ fraud, as well. Consider one of Theranos’ early investors, billionaire venture capitalist Tim Draper, who just happened to be the Holmes’ neighbor while Elizabeth was growing up in Washington, D.C. Would Holmes have been able to recruit — and defraud — such a high profile list of investors if not for this serendipitous relationship? Could she have pulled off this heist 10-years from now, when the business of venture is surely to have evolved? Or, did she benefit from an especially bullish time in Silicon Valley’s history, where anticipated returns far outweighed diligence and scrutiny?


There’s the Silicon Valley adopted adage “fake it ’til you make it”. However, psychologist Amy Cuddy in her TED Talk on body language coined the phrase “fake it ’til you become it”. Though in Holmes’ case, she could never become it. It raises the question — especially considering how many esteemed investors were defrauded — how do we guard ourselves against the narrative fallacy?

Understanding the narrative fallacy is the first line of defense — we can ask ourselves where might our need for causality or our tendency to stereotype create biases in our understanding of a situation. From there, we can begin to apply a greater level of rationality and skepticism a given scenario.

Wall Street Journal journalist Jon Carreyrou, who first broke the news of Theranos’ fraud, alluded to some elements of Holmes’ story not standing up to strict scrutiny. In particular, Theranos purported to have a groundbreaking technology that functioned across medicine, biochemistry, and engineering (both hardware and software). While Holmes may have been a once-in-a-lifetime visionary, how many groundbreaking advances in medicine or science have been made by someone of Holmes’ age and/or with a lack of medical experience?

Theranos’ investors unquestionably deserve criticism for not applying a requisite amount of diligence, especially in a once-in-a-lifetime situation, and one fraught with narrative. It has been reported that many never even asked for the company’s financial statements — and with the benefit of hindsight we can see that Holmes’ angry reactions to questions about technology demonstrated she was a fraudster and not the genius she purported to be.

In line with general advice on decision-making, applying systems and processes when faced with uncertainty and strong narratives can greatly help, as well. Courtesy of Farnam Street,

From Taleb himself… when searching for real truth, favor experimentation over storytelling (data over anecdote), favor experience over history (which can be cherry-picked), and favor clinical knowledge over grand theories.

In the case of Theranos, we can see how Holmes leveraged anecdote, fabricated experiences and applied grand, visionary theories to win over the hearts and minds of investors and the public alike.

These suggestions are not exclusive, nor are they entirely prescriptive. It is with good intentions — in an effort to make sense of and function in a complex world — that we apply and desire narratives and causality. Yet, doing so opens us up to advantageous practitioners, from the most unassuming, to the media, to the largest fraudsters or con artists out there. 

Take heed with the stories you hear — you may be fooled by narrative. 

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