The first episode of season 4 of Mad Men opens with Don Draper being interviewed by a journalist. He doesn’t tell him anything that’s of interest and then dodges the question Who is Don Draper? by claiming that he was taught as a child not to talk about himself. Scientists do an equally terrible job at communication, and for many of the same reasons. Cornelia Dean’s book Am I Making Myself Clear? offers fascinating insights into both journalism and science, and provides concrete ideas for how to do better.
Dean is the former science editor for the New York Times. Her extensive anecdotes and insights demonstrate how much experience she has working with both scientists and science writers. From this perspective, she shows incredible understanding why scientists are often wary of talking to journalists, what they think about them (and vice versa), etc. You really get the feeling that she understands both sides equally well, which gives a lot of weight to her advice (i.e., she’s not just a writer chiding scientists for being such bad communicators).
The first few chapters of the book give a rationale for why scientists should talk to the public, and discuss what works and what doesn’t in today’s science coverage in the news. That may not sound terribly interesting, but Dean covers a wide range of topics, including why journalists often feel the need to give equal weight to both sides of debates, even when there really is none, and the effect recent changes to media consumption and newsroom sizes have had on science coverage (hint: not a good one). Dean’s writing is also eloquent, engaging, and simply a joy to read. If you want to see a sample, I recommend one of her articles that she also cites in the book, Rousing Science Out of the Lab and Into the Limelight.
Every scientist (or technically-minded person, for that matter) should read her list of criteria that make for a good story (Chapter 3). Even if you still think there should be more science coverage on the news, this list tells you why there isn’t. It’s not that the criteria are all that surprising, but the way Dean frames and presents them makes you realize why they make sense.
The entire book is an example for how to write. Dean repeats a lot of the advice you’ve probably heard before: use the active voice, avoid the the verb to be, etc. Chapter 10 is essentially a tutorial for good writing, whether you’re a science writer or a scientist trying to communicate your ideas to the public. What makes this book so powerful is that it doesn’t just tell you how to write, it shows you how it’s done.
I did not expect to get much out of Chapters 13 and 14, On The Witness Stand and Making Policy. After all, I don’t expect to draft the UN Resolution on Visualization any time soon, nor do I think they’ll call me as an expert witness when those claims about parallel coordinates causing brain cancer turn into lawsuits. But like the rest of the book, those chapters provided not just useful insights into the processes and good advice, they argued for the importance of offering your expertise and taking a stand to make a difference. In a sense, the logical consequence of communicating your work is to try and make the world a better place with it.
At the end of that episode of Mad Men, Don Draper is again talking to a journalist. Only this time, he has a message, he has a plan, and has prepared stories to tell. That is a big part of what Dean recommends for scientists talking to reporters. Chapter 5 gives a lot of good advice about how to do that, how to prepare, etc. Perhaps the most important point is that you have to have a message. You can’t just talk about your research, you have to frame it in a way that shows where it is going to lead, or provide some other interesting thing to say that’s more than just your results. Dean quotes Frank Kauffman, who said: A message is not a fact, a message is a point of view. Facts, like statistics, prop up the message, but the message is bigger than the fact.
Why am I telling you all this? I think we’re lacking a message in visualization. We haven’t figured out how to explain what we are doing and what our work is really good for. This is rooted in our inability to even define what visualization is (and, consequently, what it is not). Just like the scientist who thinks that explaining his work in laymen’s terms means dumbing things down, we can’t let go of anything that might remotely be called visualization. As a result, we can’t explain what it is. And anybody can call anything visualization without a need to defend that (because nobody can claim that it’s not).
But that’s just part of the problem. How do you convey visualization as a story (and not just by showing pretty pictures)?. Say you’re supposed to explain visualization on the radio, how do you do that? And how do you tell a story in which visualization plays a role but that is not primarily about a particular visualization?
I don’t have answers to those questions, but I think we need to figure them out. And we need to do it quickly, before there’s even more confusion and visualization turns into a completely diffuse mess of stuff nobody understands.