Chris Anderson is editor-in-chief of Wired, and Malcolm Gladwell is a top brand name at The New Yorker, and as corporate cousins, clearly Condé Nast’s publicity machine must have engineered this beef, trying to boost sales of both their titles through a completely manufactured rivalry.
Their past titles have been champions of what I call the “Airport Books” genre: The elite class of business titles that I see sold in airport newsstands next to the magazines and crappy romance novels. (I might have unknowingly stolen “airport books” from someone else, but I can’t find a citation.)
Alas, I’m assured that this particular contretemps isn’t a planned corporate PR stunt. (Though I know lots of nice folks at Condé, they don’t seem to mimic street-level hip hop marketing as often as one might hope.) Instead, it seems the criticism and counter-argument are sincere.
The core of Gladwell’s argument is simple: “Free” fails to provide data to support its claims about the future of pricing, using anecdote and confident assertion in place of actual evidence. In his objection to this methodology, Gladwell seems uncharacteristically strident, compared to his usual measured tones. Whenever I see somebody getting their dander up, I think of one of the first things I ever blogged about 10 years ago: We hate most in others that which we fail to see in ourselves. Ah hah!
- The IUP sceptical Inquirer’s Wesley Cecil has a review of Blink which offers this up: “Gladwell relies heavily on anecdotal evidence. The centrepiece of each chapter is a short story or series of stories that are supposed to illustrate some aspect of his theory of snap judgments. … [I]ntuitive feeling triumphs over careful study. … [O]ne case does not an argument make.”
- Slate’s Jack Shafer on Gladwell telling a tall tale at The Moth, which kind of ridiculously insinuates that this is a character flaw instead of just a fun story.
- More definitively, the New York Times’ Michiko Kakutani made this point in her review of Outilers, but extends it to apply to all of Gladwelll’s books: “[His] books are filled with colourful anecdotes and case studies that read like entertaining little stories. Both use PowerPoint-type catchphrases (like the ‘stickiness factor’ and ‘the Rule of 150’) to plant concepts in the reader’s mind. … ‘Outliers’ Mr. Gladwell’s latest book, employs this same recipe, but does so in such a clumsy manner that it italicizes the weaknesses of his methodology. … [His examples are] all based not on persuasive, broadband research, but on a flimsy selection of colourful anecdotes and stories.”
- Joel Spolsky keyed off of Kakutani’s review on his popular blog: “what’s been driving me crazy over the last year… an unbelievable proliferation of anecdotes disguised as science, self-professed experts writing about things they actually know nothing about, and amusing stories disguised as metaphors for how the world works.” (Bonus points to Joel for swiping en passant at airport book titan Thomas Friedman and his cartographic ironing board.)
- Kevin Arthur’s post built on Joel’s rant, offering a slightly more measured, but still critical analysis: “I feel like clarifying my opinion on this… I think there is great value in pop science books, in articles written by non-experts, and in anecdotes. I read Joel’s piece not as a rant against all those things but against those things badly done.”
- Peter Coclanis at Open Letters just gets downright mean: “[L]et me say from the get-go that my goal in this piece, which focuses on Outliers, is to demonstrate at once how wildly overstated such just-jacket claims are and how egregiously incomplete, insubstantial, and unconvincing Gladwell’s explanation of success actually is. His methodology stinks, too, and, from his dust-jacket photo, he appears to need a haircut.” I know what fun it can be to bash someone from afar on the web, but I bet Coclanis is a lousy dresser. Just sayin’.
- And not to belabor the point, but let’s close up with Isaac Chotiner in The New Republic, taking a stridently snarky look at Outliers: “By the time Gladwell reaches his penultimate chapter, he is in full inspiration mode, and impervious to all forms of critical thinking. … Here is the Gladwell method nicely on display: a questionable assumption, a partial walk-back of an earlier claim, and finally another questionable assumption synthesizing the half-reversal.”
My goal is not to ennumerate all of the criticisms of Gladwell’s books — I enjoyed reading all of them, and I like his New Yorker pieces, and that’s kind of all I would ask of the guy. But I can’t help but wonder if being ceaselessly criticised for using assertions and anecdotes in lieu of hard statistical data has left him much more inclined to criticise others for using the same technique.
I haven’t had a chance to finish reading Free yet, but I am sure that both of these authors’ books absolutely do lean more towards anecdotal evidence than statistical proof. And honestly, it’s OK that these books don’t necessarily follow the tenets of hard science. In many cases, they’re arguing that a cultural trend is becoming true, or is about to become true, and the reality is that asserting that these trends are ascendent actually helps them come true. In short, these are books designed to create culture, presented in the guise of reporting on culture. I like that!
But of course there will always be those who disagree with the idea of starting from a premise first, and then finding examples to support it. Perhaps the last word in favour of using hard data to support social observations may be from a story package in Wired a year ago, which was headlined “The End of Science” and anchored by a story called The End of Theory:
This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behaviour, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.
… But faced with massive data, this approach to science — hypothesize, model, test — is becoming obsolete. … The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all.
The author of this compelling argument in favour of using overwhelming amounts of data to help replace formulating theories about human behaviour? Former scientist Chris Anderson.
Bonus link: If you’re interested in actual debate about the content of the book, Mike Masnick’s excellent overview over at TechDirt is a must-read.
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