Jonah Lehrer and the Problems with "Pithy" Science Writing
Jonah Lehrer at PopTech.
Photo Credit: PopTech via Flickr
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There is little doubt that Jonah Lehrer is a brilliant writer and fluid storyteller, but let’s face it: the reason he jumped to the top echelons of the media landscape in so short a time at such a young age is the type of stories he chose to write: behind-the-scenes looks at how our brain and psychology work, philosophical insights into what makes us successful (or nervous), and the science behind intangible things such as creativity and altruism.
In the past few years, American culture has harbored an insatiable love affair with snappy, part-science, part-anecdotal pronouncements of the abstract.
With a global economic crisis fueling rampant job losses, scarcity of resources inflating the price of everything from food to oil, and unforeseen terrorist attacks stirring up debate over privacy and security, delving into obscure concepts presents a sort of balm to problems that we can’t solve with real, tangible solutions.
In such a situation, arose first Malcolm Gladwell and then Lehrer, espousing theories about modern life and culture, overlooking real problems, and offering pithy observations and insights, with just a hint of scientific backing. In an era where it isn’t sufficient to rely on one’s own hard work and mettle to make it anymore, it’s easy to grab on to the surefire trends and magic bullets that these writers so convincingly present to us.
The world economy is crumbling and unemployment is soaring. But let me talk to you about an intangible tipping point that could change your life forever or tell you what happens in your brain when that proverbial light bulb goes off in the cartoon equivalent of a thought bubble. Because talking about the actual economy is much too real and depressing.
Eric Garland puts this better than anyone else in his piece, “ Jonah Lehrer, Malcolm Gladwell and our thirst for non-threatening answers.”
Of course, not every journalism piece ever written has to have a real-world immediate-impact objective to it, but these authors don’t seem to fulfill an educational goal either. While there is a pretense of breaking down complex concepts to a popular science level, the scientific basis of both Gladwell and Lehrer’s writings have been widely questioned.
Science writers have always had to try harder to be interesting. In trying to entice the general public with the tedious, sometimes boring work that goes on in a research lab, they often reduce the nuances and complexities of science—workings of intricate systems like evolution and the human body, the mathematics of financial bubbles, and the inevitable warming of the earth— to interesting tales that combine a tiny bit of data with copious amounts of speculation without context or background. This is what leads to stories with ridiculously overreaching headlines like “ Rain causes Autism,” withering portrayals of very complex ailments like depression and addiction as the cause for all evil, and dueling wars between opposing camps around one dubious aspect of a rising epidemic.
Pop-science writers like Gladwell, Lehrer, Dan Ariely, and Charles Duhigg take a slightly different approach—they combine decades of scientific research with hearsay and speculation, metaphysical analysis and societal trends, and offer it to the audience in bite-size palatable pieces. Hip, new phrases to be thrown around in water cooler conversations—real or virtual—such as Gladwell’s “stickiness factor,” Lehrer’s “bias blind spot,” and Duhigg’s “power of habit” as proxies for real explanation don’t hurt.
As Eric Price puts it, “That's exactly what smart, curious, and busy readers like you and I want: surprising, Fun-Size ideas with just enough academic heft.”
In addition to trivializing scientific studies, which may present an even bigger danger, these works are peppered with frivolous analogies (think Gladwell’s comparison of epidemics to the hushpuppy trend), conclusions far removed from the original research, and misinterpretations of scientific studies based on inconclusive data.