the art of insight: in conversation with Alberto Cairo
Our friend Alberto Cairo published a brand-new book called The Art of Insight, which I promise you is unlike any book on visualization you've read to date. I was lucky enough to chat with Alberto on a recent episode of the storytelling with data podcast. Just as he had been on his three prior guest appearances, he was inspiring, supportive, informative, inspirational, and—yes—even insightful. But this time, the conversation touched on a number of unexpected topics (philosophy, history, tabletop games, politics, power, and even a bit of data visualization).
Here is just a sampling of excerpts from our wide-ranging discussion.
on losing, and re-discovering, enthusiasm
Alberto: I think that all of us who have worked in a field for so many years, at some point we lose a little bit of perspective. We also tend to forget that there is a whole world out there. It is very easy to assume that everything out there looks like it looks inside of our heads, and that the only way to practice a craft like visualization is the [specific] way that we practice it.
And what I try to explain in the book is that we all fall prey to that impulse, but at the same time, when we expose ourselves to other people in the field and their work and the way that they see the world and the way that they use data visualization in the world, and for the world, we understand that this is a very diverse craft, a very diverse way of doing things. And I really appreciate that.
So, I just wanted to build that appreciation or rebuilding and then cast my sights out there, cast a very wide net, and then talk to people and get inspired again.
on different “dialects” of data visualization
Alberto: There are really no rules of data visualization. There's just reason in data visualization. That's a very pragmatist approach, in my opinion. That's something that I describe in detail in the first part of the book.
Mike: Yes, for instance: “If visualization is a language, many dialects are possible.” There are many different ways of visualizing.
Alberto: I use terms from linguistics in a very loose way. I know that linguists would probably scold me on, oh, this is not really a language. But I hope that people will be a little bit forbearing with the way that I use certain terms. It's like, there is a grammar of graphics. There's a book titled The Grammar of Graphics. So if there is a grammar, well, I assume that this is sort of like a language. And the language can be practiced in different ways.
It's not only that there are different dialects in data visualization, so to speak. But also that data visualization can have a multiplicity of purposes. Data visualization can be essayistic, or explanatory, or narrated, which is the type of data visualization that I produce. Data visualization can be exploratory, right? We can create dashboards and other types of graphics to analyze data. But data visualization can also be poetic and artistic. And why not? That's still data visualization because it uses the grammar and the syntax of data visualization.
on the value, and limits, of artificial intelligence
Alberto: [When it comes to AI,] we should be as concerned as we are about any other technology that facilitates the work and lowers the barrier of entry to anybody in the field…which means that, in my case, is not that much.
It will be something that will extend our capacities. It may lower the barrier of entry to the fields. I think that it is wonderful, for example, that today I can avoid writing long lines of R code to generate my charts, and I can describe the R code that I need in natural language, and then the artificial intelligence text generator will spit out decent code that I can then tweak, right? And then I can add the variables that I need, et cetera, in order to generate a chart, for example. I think that that is wonderful.
Now, are there dangers in these types of technologies? I believe, obviously, yes, that there are. But discussing what those dangers may be, I think it is way above my pay grade. I cannot make any predictions about that.
But I'm not fearful. I'm not afraid.
I think that there's always going to be a role for people making decisions. I think that companies will understand that you need people to make these types of choices. No matter how rich and detailed your algorithms are, you still need the people to make the final call about a particular insight that you extract from data.
And if they don't understand this? Well, good luck to you, because you are going to run into a lot of problems.
I’d encourage you to download and listen to the entire episode, or to read the transcript if you prefer. It’s episode 72, “Alberto Cairo and the art of insight,” on the storytelling with data podcast, available from our website or wherever you get your podcasts.
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