The Reason Why We Tell Stories

Kevin Ashton has one of those CVs that makes you do a double take. Scandinavian studies in London, worked at Procter & Gamble, took a deep dive into RFID technology that took him to MIT, where he coined the term "Internet of Things" and now, somehow, wrote a book about the nature of storytelling itself: The Story of Stories: The Million-Year History of a Uniquely Human Art. I loved the latter so much that I read it in a single sitting on a flight to San Francisco.

What struck me about Kevin is that his eclectic looking intellectual journey isn't random at all. The thread running through all of it, from his work at P&G to the connected sensors of the IoT era to his deep dive into how humans have told stories since they first gathered around a fire, is the same fundamental question: how do we actually process information, and what do we do with it? And that’s something that has fascinated me as well for the past decade. So I was honoured when he agreed to being interviewed for this Never Normal newsletter.

We don’t follow data. We follow stories.

Kevin describes his formative years at Procter & Gamble as something of a genuine anomaly as it was, and still is a company that spends tens of millions a year on data intelligence. "Nowadays, everybody claims to be data-driven," he says, with the kind of smile that tells you a punchline is coming. "My joke is always, well, show me the data that says you're data-driven." He pauses. "Because honestly, that’s almost never the case."

Kevin became fascinated by the fact that, even when companies generated mountains of information and had teams poring over it, their decisions were still being made on something else entirely. He discovered this difficulty from MIT linguist Noam Chomsky, who called it "Orwell's problem", “where you have all this information, and you're still not understanding any of it”. Kevin came to believe that our Enlightenment ideas about how we make decisions are wrong. “The notions that we are rational beings assessing information through probability and logic, or gathering clean data through our senses like blank slates filling up: these are beautiful ideas, but they are basically fictions.”

“What we actually do is live inside stories. We build up a library of them over a lifetime, they calcify and they become the lens through which we interpret everything new. And when something arrives from left field that doesn't fit that library, we don't update the library but reject the new thing.” That, Kevin argues, is the actual operating system of human cognition.

Stories came first, language second

Which naturally leads you to ask: where did these stories come from in the first place? How did a species that communicated in urgent calls and cries end up sitting around exchanging narratives? Kevin's answer here is one of the most wonderful ideas in the book. Early humans, he explains, started building fires which changed everything because that extended their day. Suddenly you had a group of people together at night with no immediate urgency, no predator to flee, no food to chase, and an overwhelming social impulse. They had to do something with sound, but all the sounds they had were sounds for urgent, immediate things. So they had to repurpose them. They had to invent a way of talking about things that weren't happening right now. "And that," Kevin says, "is storytelling. The drive to tell stories was the forcing function that turned cries and calls into language." It's one of those ideas that feels almost too elegant, until you realize it fits an astonishing amount of evidence from primatology and anthropology.

From there, Kevin traces the long arc of storytelling technology and what he found upended his own expectations. "I thought that when I looked at how technology transformed storytelling, I'd find that the stories themselves change; that television impacted what a story is, or the printing press changes narrative structure." That's not what happened. "What shifts," he says, "is how many storytellers there are, and how many people they can tell stories to." That's the variable that technology keeps moving. The printing press didn't change what stories are made of, it industrialized their production and distribution, exploding the number of people who could participate in the exchange.

And that framing, I told Kevin, cracked something open for me about the AI moment we're living through right now. Because we're now seeing an industrialization of labor and an industrialization of knowledge happening simultaneously. And the collision of those two forces is probably why we're seeing such spectacular adoption, such torrents of investment and such vertigo-inducing speed.

Critical thinking as moderation

Kevin isn't naively cheerful about where all this is heading. His deepest concerns about artificial intelligence are not, interestingly, about large language models like ChatGPT or its successors. What worries him is reinforcement learning, the technology that companies like Facebook have been quietly using for fifteen years to determine what you see when you open your feed. “Facebook uses an AI system with a single purpose: to increase the probability of you clicking on something. It doesn't understand what the content means. It doesn't know if it's true or harmful or beautiful or dangerous. It just knows that you are likely to click on it, and it optimizes relentlessly, individually, continuously. In doing so, it reinvents itself in the background in ways that nobody at Facebook actually understands.”

“The consequences of that became grimly visible during COVID, when Mark Zuckerberg wanted Facebook to be a beacon of light for vaccination.”, Kevin explained. The intention was good, but all the while Facebook was simultaneously pumping out millions and millions of anti-vaccination stories because the machine had learned that people click on them. "Facebook had no control over that," Kevin says flatly.

And here's where he gets surgical: this loss of control was not random or accidental. It was purely economic. He points to the one category of content Facebook does moderate consistently and automatically - explicit sexual content - and notes that Zuckerberg has admitted on record to shareholders that the reason is cost. Nudity is easy to recognize and therefore cheap to censor. Hate speech is much more expensive to identify. " Zuckerberg doesn't believe in freedom of speech," Kevin says. "He believes in cheap moderation."  The answer, Kevin argues, isn't hoping that the platforms will find their conscience. It's rebuilding critical thinking at the individual level, because that's the only moderation we're actually going to get.

Are we making any progress?

In spite of everything, Kevin remains optimistic, by looking at the long arc of history. "We take two steps forward and one step back.", is how he framed it. “Consciousness gets raised - for, for instance, gay people, transgender people or interracial couples - but then comes the violent backlash. It looks terrible, and it is terrible, but the people driving the backlash eventually die off and within a few generations things stabilize at a new level.” “Once consciousness is raised," Kevin continues, "it doesn't get lowered." He wishes we didn't have the backlash. But the direction of travel is real.

It’s a pattern I’ve noticed in many conversations, whether for this Never Normal newsletter or in everyday life. People are genuinely concerned about the very real challenges we face, whether technological, geopolitical, environmental, or otherwise. As they should. Yet when they zoom out and look at the long arc, most still consider society to be moving forward. And they believe we will find ways to solve the problems in front of us. And that shared confidence is what gives me hope.