The Shy Scientist
There has recently been a spate of best-selling popular science books that attempt to explain to the masses some fairly intricate ideas from fields such as psychology, neuroscience, mathematics, and biology. But they leave me somewhat uncomfortable. Most of them were written by non-technical authors.
Dan Pink 1 has written books about psychology and neuroscience, but he holds a degree in law, and has no technical background. Malcolm Gladwell 2 is a scintillating writer and a thorough journalist, but he too has no technical credentials. One exception who stands out is Jonah Lehrer, who, according to the bio on his dust jacket, actually spent time as a graduate student in a neuroscience laboratory.
Steve Pinker chastises Gladwell for getting the term “eigenvalue” wrong 3. At that point, Gladwell has surely lost almost all of his technical readers. How could he possibly move on to explaining concepts that are built on understanding what an eigenvalue 4 is, when he doesn’t understand what an eigenvalue (or linear algebra, for that matter) is?
But what about the actual scientists doing all this work that is being written about? Why aren’t they the ones writing books like these? For one, they’re too busy actually doing science, and writing up the results in technical papers, for a technical audience. But I don’t think that’s the real reason holding them back.
The central value drilled into scientists through their long years of training 5 is skepticism. This leaves them with a deep discomfort with blanket truths and generalizations. Scientific truth is extremely hard to pin down, and even then, it is usually preconditioned upon a long list of precise factors. Most scientists’ careers follow the path of narrower and deeper specialization, strengthening their aversion to wide generalizations.
Authors, on the other hand, want to believe. They want to find the parts of a dense technical paper that help them build a colorful story and support a somewhat related generalization.
Where does that leave the reader? If you truly want to understand a topic, treat these books as jumping points. Question their narrative. Most of all, flip back to the bibliography, and try to dig into the original sources.
2http://www.gladwell.com/bio.html
3http://www.nytimes.com/2009/11/15/books/review/Pinker-t.html?_r=2&pagewanted=print
4http://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
5 They are usually in their late 20s by the time they get their PhD’s, which is when their career actually starts