Our late postdoctoral advisor, the Nobel laureate David H. Hubel, had an eagle eye’s view of science. Over lunch, or during afternoon tea in his office—to which the whole department was invited—he would hold forth on hot topics and issues in research and life. On such occasions, he might encourage us to be skeptical of trends in science: to resist pressure to publish too early, for example, and hold off submission of any paper that might not make us proud one decade after publication. Or he might ponder more philosophical issues such as how big science differs from small science.

Big science and small science are identical in almost every way, Hubel once told us. Both kinds of projects often require similar amounts of research funds or personal sacrifice. Both can be equally captivating to the scientists studying them: a researcher will just as happily immerse herself in vast or in minute questions. The key difference between the two enterprises, he explained, is how much other people care about them. Often, there is no principle that makes a given question more important than another: the perception of the reader is what makes a scientific question big or small. It follows that scientific impact can depend on how researchers communicate their findings, especially to the public.

Like the proverbial forest tree whose fall does not make a sound if nobody is around to hear it, science discoveries cannot have impact unless people learn about them. The act of communication is part and parcel of doing research. And in an era increasingly defined by open access, crowdfunding, and citizen science endeavors, there is a growing demand for scientists to communicate their findings not just within their field—via institutional seminars, conference presentations, and peer-reviewed publications—but to general audiences too. One of our main challenges as scientists, then, is to present discoveries that the public will care about.

In an article published on August 01 by the Proceedings of the National Academy of Sciences, we propose that, just as successful art engenders emotion, successful science communication must identify and develop emotional connections with the public. To accomplish that goal, scientists may take lessons from effective storytelling narratives in fiction writing.

The full article is freely accessible from the PNAS website, and an excerpt follows below:

Edward Morgan Forster, the author of A Room With a View (1908), Howard’s End (1910) and A Passage to India (1924), distinguishes between story and plot. “The king died and then the queen died” is a story, Forster writes in Aspects of the Novel. But “the king died and then the queen died of grief” is a plot.

The first statement amounts to a series of events in proper chronological order, Forster argues. The second statement goes beyond a simple time sequence. It gives the reader a reason, a causal connection between the events. “Consider the death of the queen,” Forster compels us. “If it is in a story we say ‘and then?’ If it is in a plot we ask ‘why?”’

Plot-building and research narratives share certain parallels. As scientists, we observe events in the natural world, and try to draw connections between them. We care not only about ‘when’ things happen with respect to one another, but ‘why’ they happen. If we are so lucky as to find out the ‘why,’ then we have a tale to tell. But how do we make our chosen audience care about it?

In an opinion piece for The New York Times published last year, the physicist and popular science writer Lawrence Krauss laments that fundamental science findings, such as the recent discovery of gravitational waves, come short of generating appropriate levels of public excitement.

“Too often people ask, what’s the use of science like this, if it doesn’t produce faster cars or better toasters,” he says. “But people rarely ask the same question about a Picasso painting or a Mozart symphony.” Gravitational waves have little relevance to our everyday lives, Krauss readily admits. Yet Beethoven’s 9th, while also lacking practical value, does not fail to exhilarate us.

The answer to this riddle may lie in Forster’s tale of the dying king and queen. Why is “the king died and then the queen died of grief” better writing than “the king died and then the queen died”? Forster is correct in that only the second sentence offers a causal link between two previously disconnected events. But is that the main difference between the two accounts of the king and queen’s deaths?

Perhaps a more important distinction is that the first sentence is emotionally neutral, but the second is not. “The king died and then the queen died” needs not evoke a mental picture in the readers, but “the king died and then the queen died of grief” forces them to consider what feelings they experienced after the loss of a loved one, or what feelings might follow such a loss.

The king died, and then the queen died. We asked our son Iago, age 9, to “make a drawing” to illustrate E.M. Forster’s “The king died, and then the queen died” statement. Iago’s drawing shows the two events in order, without a causal link between them. Credit: Iago Macknik-Conde

The king died, and then the queen died of grief. Next, we asked Iago to illustrate E.M. Forster’s “The king died, and then the queen died of grief” statement. Iago’s drawing shows the two events causally connected to each other. More importantly, the simple addition of two words (“of grief”) to the original statement had the effect of transforming the initial detached narrative into one that is clearly emotional, even from the point of view of a 9-year-old child. Credit: Iago Macknik-Conde

Reading that “the queen died of grief” triggers (at least the glimmer of) an emotional reaction in the audience. So does listening to Mozart, or standing in front of Michelangelo’s Pietà. Be it music, painting, or poetry, good art moves us. Just as big science does. The corollary is also true: bad art—and small science—fails to make us feel.

Identifying and developing such emotional connection in the public might be a powerful path to a gripping plot.