My Place in the Crowd

I love stories.

You might think, then, that I wouldn’t love data.  Stories and data are often seen as two very different ways of presenting information.  Data is considered cold, impersonal, incomplete.

But much of data’s bad reputation comes from limited data, not data in and of itself.  As Hans Rosling, a Swedish professor, demonstrates in this video, data can tell amazing stories.

It’s long but well-worth watching in its entirety.  It’s a few years old, from the 2006 TED conference, but I would bet it’s almost as riveting on YouTube as it was live at the conference.  In it, Rosling uses animated graphs of UN statistics from 1962 to 2003 to tell stories about our world and how it’s changed in ways that defy easy generalizations.

For example, his Swedish medical students studying global health assumed that there were two kinds of countries in the world—Western countries where family sizes are small and people live longer, and Third World countries where family sizes are large and people die young.  But as his animated graphs show, many countries that are still poor and developing have moved by 2003 into the upper left-hand quadrant, of countries with smaller families and longer life expectancies.  By 2003, Vietnam is in the same place the United States was in 1974.  As he declares, “If we don’t look at the data, we underestimate the tremendous change in Asia.”

In my favorite segment, like a great novelist building a complex character, Rosling breaks down one set of data over and over, showing the much more interesting and complex story behind average income and child survival.

The first graph, comparing GDP per capita among countries in the OECD, East Asia, South Asia, Africa, and Latin America, tells the story we all expect.  The blue dot in the upper right-hand quadrant is OECD countries; the small red dot on the bottom left-hand quadrant is Africa.

But then he shows how different countries within Africa have tremendous variations in GDP per capita, as well as child mortality, despite Western conceptions of a monolithic “Africa and its problems.”

And just when you’re patting yourself on the back for understanding that Africa includes a very diverse range of countries, he shows that even within the countries, the distribution of income is very broad.  The highest income quintile in South Africa is quite high, approaching the average per capita GDP in the United States.

As Rosling says, “Improvement of the world must be highly contextualized!”  And the data is what will allow us to do it.  His demonstration itself shows how data can be limiting, how it can be used to “prove” that all of Africa is poor and sick.  But the solution clearly isn’t to ignore the data but to look at more data. Ultimately, broad, detailed, longitudinal data push us to think harder, rather than rest on our assumptions. Stories still need to be told–how did Mauritius get wealthy and healthy?  Why didn’t Ghana? But without the data, we wouldn’t even know those stories were there.