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Narrative Intelligence teaches that every narrative evolves over time, undergoing changes in both meaning and usage. There is perhaps no better example of this rule than the concept of narrative intelligence itself. While the phrase used to mean one thing, now it refers to something else altogether.
The Cambridge Dictionary has two definitions for it. The first is “a story or a description of a series of events.” The second is “a particular way of explaining or understanding events.”
Merriam-Webster largely concurs with this assessment. Its first definition is anything “that is narrated.” This might mean a book, a film, a sermon, a piece of advertising, and so on. Merriam’s second definition, however, is much more telling. Essentially, a narrative is also “a way of presenting or understanding a situation or a series of events that reflects and promotes a particular point of view or set of values.”
A narrative, therefore, is not merely what is said, but how it’s said.
So, which of these definitions is narrative intelligence most concerned with? Well, it actually focuses on both. Imprecision in language means that inaccuracies frequently arise in even the best efforts at truthfulness. In other words, what is said is just as important as how it’s said.
Those who work in narrative intelligence tend to ask themselves a few basic questions about a given piece of content.
Narrative intelligence, then, can be thought of as the information culled from analyzing of public narratives. And, yes, literally anything can become a public narrative. Post an update on social media and congratulations. You’ve just created a public narrative.
The term ‘narrative intelligence’ used to mean something entirely different, though. In fact, it began its life not as a business or public policy concept, but as a technological one.
The earliest online reference to narrative intelligence is from a research paper simply titled "Narrative Intelligence" by Michael Mateas and Phoebe Sengers. They borrowed the phrase from a couple of researchers who had coined it in 1997, David Blair and Tom Meyer. Presented at the 1999 American Association of Artificial Intelligence (AAAI) Spring Symposium, the paper speculated about what was then a highly theoretical issue. Might it be possible to someday build an AI with storytelling and narrative capabilities?
Mateas and Sengers defined narrative intelligence as “the ability to generate and understand narratives.” Today, we think of narrative intelligence as gleaned information. Mateas and Sengers, however, couched it not as a product but as an ability, an aptitude. It referred to the state of being capable of something.
Within the closed world of theoretical computational research, that definition is still somewhat in use. A research paper from 2021, for example, speaks of “narrative intelligence as the next step for mental health chatbots,” envisioning a scenario in which virtual therapists are able to follow and engage with patient narratives, while also crafting their own.
Not long after Mateas and Senger introduced their concept, however, narrative intelligence found footing among psychological researchers. What had been a merely technological concept now became a human-centered one. It still referred to the same ability, though the emphasis was now on people, instead of software.
A paper published in 2001 by Kerstin Dautenhahn, for example, theorized that narrative intelligence facilitated transactional communications between “humans and other social animals.” Other research emphasized the importance of narrative intelligence in teaching, leadership, nursing, and even the practice of law.
It was not until the past few years, though, that narrative intelligence took on its most current meaning. Writing in 2019, a communications scholar named Leigh Jerome lamented that we had arrived at an age when “people must sort through fake news, misinformation, and disinformation,” without ever really knowing which is which. Might narrative intelligence offer a solution?
At the time, narrative intelligence was beginning to be used interchangeably with the term ‘narrative analysis.’ Researchers were in a desperate search for a tool or method that might mitigate the worst effects of bad-faith narratives, such as the fallout that occurred in the wake of the 2016 presidential election.
Over the past few years, though, narrative analysis has become the methodology by which narrative intelligence is derived. Indeed, recent published works now argue that narrative analysis can help identify false narratives, remedy the spread of disinformation on social media, and enable us to evaluate online claims for accuracy.
Narrative intelligence as we now speak of it is still in its infancy. Yet, as fake news and false narratives continue to proliferate, its importance in business, healthcare, consumer protection, and other sectors will only grow. Yes, lies and exaggerations have become permanent fixtures of online narratives. But now we have a way to protect ourselves.
