This weekend I had a treat when I read that noted science writer Jerry Coyne, author of Why Evolution Is True, took up the central argument of my essay on Gladwell, Lehrer and the search of non-threatening answers in his piece Science writing: lite and wrong.
Over at his eponymous website, writer and corporate consultant Eric Garland takes up an issue which has started to bother me lately: “science-lite” books that offer superficial analyses of and solutions to social problems or—most disturbing to me—superficial descriptions of scientific work. To me, these include books like Malcolm Gladwell’s The Tipping Point (a page-turner, but one that left me cold), Jon Haidt’s The Righteous Mind (with its unfortunate concentration on group selection) and The Happiness Hypothesis, David Brooks’s execrable The Social Animal, Nicholas Wade’s The Faith Instinct (funded and vetted by the Templeton Foundation), and all of the books and writing of the now-disgraced Wunderkind Jonah Lehrer.
What these books have in common is a) enormous appeal to the popular mind, especially the part that wants easy answers and doesn’t want to think too hard about science, b) good writing (usually), c) a “self-help” aspect, which promises that you can improve either your life or your business by applying or recognizing a few easily-digestible bits of modern science, and d) annoyingly superficial analyses of difficult problems.
To borrow Jerry’s phrase – right on. Give it a read.
EXTRA SPECIAL BONUS – Malcolm Gladwell himself stopped by to defend his work. I didn’t see that coming, but welcome, Malcolm! We have a lot of dialogue ahead of us about why the intellectual environment of our elites seems insufficient in the management of our critical institutions.
The roots of my discontent about science lite
So let me expand a bit more on why I am so allergic to “science lite.” My own background is in competitive intelligence and futures studies, which are both outrageously generalist professions in that they involve knitting together massive amounts of data to form coherent narratives in the hopes of improving the decisions of leadership. What makes both fields so interesting is the incredible, unmanageable variety of fields you must understand to work on most projects. Demographics, materials science, advances in biotechnology, real estate trends, the dynamics of the nuclear power industry, new research about atypical antipsychotics, what’s up with global warming, legal frameworks of national lottery systems – these are just a tiny fraction of the subjects and fields I have had to deal with in the recent past. Add my colleagues to the mix, and you’re talking about professionals expected to be reasonably conversant about half of Wikipedia.
What do these field have dangerously in common? I’m not an expert at any one of them. My expertise – if you want to call it that – is in how to research relevant data, analyze it, and present it to people who have to make a decision. But this dynamic is terribly perilous, because the devil is most certainly in the details. When you are looking at competition between major firms, or more challengingly, scenarios of the future, you have to get the details right about some very sophisticated subjects, or you lose all credibility. Let me underline this, I learned this the hard way. Let me tell you, if you are presenting to a pharmaceutical executive about product development in their competitors, and you screw up the different between the words agonist and antagonist in your delivery of findings, you are going to end up in the parking lot with a horribly damaged reputation. (Hint: One makes something happen more, the other makes it happen less. Turns out that’s a big deal.)
And what about forecasting the future of science. I remember being 25 years old back in the late 1990s, first sitting down at Joe Coates’ futurist firm and breathlessly researching the AWESOMENESS of quantum computing. I researched how scientists were experimenting with making chips whose logic would derive from the quantum properties of the atom, not just the position of the electron, so, like, they could maybe make chips with a BAJILLION times the processing power. Wicked!
Of course, I had a bachelor’s in International Business, and no freaking idea of what I was really discussing, so when I called some of the people working on these projects and asked them excitedly if WE WERE ON THE CUSP OF, LIKE, MAJILLIONS OF TIMES THE PROCESSING POWER, they paused as if thinking of how to explain this to a small child, and told me, “Uh, Eric, we’re talking about very bleeding edge understanding of basic physics. There is nothing resembling a product plan in place now or in the near future.” Easy, killer, and don’t always be looking for the splashy headline. Because real science reveals her secrets coquettishly, and the applications of such revelations may come late or never. Such is the world of real science. And if you don’t want to be some fantasist who blathers about future possibilities good and bad, get your story straight and make sure that scientists will not step forward to correct your horribly obvious mistakes of ignorance.
The telltale signs of graphs without numbers
What gets me about popular authors who base their work on “science” or “scientific principles” or “recent discoveries” is their seeming lack of respect for this principle. In the years since Gladwell, I saw a number of popular authors giving keynotes based on science lite observations. At the annual convention for the Society of Competitive Intelligence Professionals I sat there while James Surowiecki – a colleague of Gladwell and Lehrer’s at The New Yorker – explained to an audience full of analysts that “crowdsourcing” produced superior results. He gave a couple of anecdotes about horse race handicapping, something about intuition. He then provided nothing in the way of “P values” so we could look at just how many examples he had in his data set, gave nothing to us about how this worked in issues of pure probability versus, say, the mindsets one might encounter among executives in a major institution. Nope, he just got paid to remind us, “Ask a bunch of people tough questions. Studies show it, like, works.” I took the free copy of his book back to my hotel room to find out if he was just shorthanding more major research that was available in his masterwork.
The next year I saw Frans Johansson, author of The Medici Effect give a keynote. He was a charismatic speaker, and his presentation was very slick. His subject was enhancing creativity by juxtaposing different themes, arts, cultures. He spoke eloquently about the need to re-unite the arts and the sciences, explaining how this is what made Florentine Italy such a hothouse of intellectual, scientific and cultural output during the Medici era, despite the harrowing violence of the period. Very cool, right in my sweet spot.
Then he threw up a chart about how studies showed that creating cross-functional teams improved “productivity.” To my memory, there was a comparison of teams comprised of a single expertise, and another trend line showing team made up of marketing, science, HR, finance, and so on. What stuck out was good Christ, there are no numbers. What am I looking at? What’s the goddamn P-value? Where was this done? Who did it, ferchrissake? Is this just America, Sweden, The West in general? Is Asia involved – since they have totally difference dynamics in hierarchies?
No answers forthcoming – on to the next point. Music swelled people clapped. Everyone should work together. Teamwork is great. No man is an island. Thanks for having me.
My memory is extremely faulty for having small children and low-grade insanity, so maybe I totally missed Johansson’s scientific rigor and am bordering on libel. If that is the case, I beg his pardon. But I don’t think so.
Can we get back to rigor, please?
Johansson and Surowiecki’s presentations made up the larger trend of the type of writing that found success in the delirium of the Post Dot Com Crash, the world after 9/11, the period of time when we lost our collective minds, started jacking up college tuition, began torture regimes, and blew an enormous asset bubble. If some theory made us feel good, it just needed to be science-y enough to fit into the corporate management of the day, which substituted spreadsheets for wisdom, statistical regressions for common sense. This is the same period of time when PhD mathematicians told Wall Street and Washington that they could set up a quadrillion dollars (look it up) in derivatives to back a senseless inflammation of housing values around the world, because – look! – it’s math! This makes no goddamn sense at all, replaces social stability with rampant speculation, but we have formulas that say it’s OK. Go back to sleep.
I’m glad to see the scientists get up in arms over the usurpation of the respect that comes with their rigor. The scientific method is the towering intellectual achievement of humanity, and it’s why we’re not drowning witchs, experiencing 70% infant mortality and basically rooting around in the mud. Science isn’t always exciting, doesn’t always lead to easy answers, and cannot be expected to puke out “innovations” to juice earnings reports for Wall Street. Science is a demanding master, a religion of its own. A cheap version of it has been borrowed of late by people who want to justify a certain type of managerial thinking. The recent defenestration of popular authors has been a long time coming. Perhaps it is time to move our culture back to something less exciting and, well, more scientific.