Originally published in CivicHall.org
For the past week or so, an article titled “The Data That Turned the World Upside Down” has been following me around like a bad headcold.
The article tells a compelling “whodunit” story of data scientists, engineers, and political communicators, all fighting for control of a new, weaponized form of online political propaganda. It leads readers to the conclusion that conservative data vendor Cambridge Analytica (CA) used Big Data and “psychometric targeting” (also called psychographic targeting) to propel Donald Trump to the White House.
I’ve written about Cambridge Analytica before (several times, in fact). I am on record as a loud CA skeptic. I have described them as the Theranos of political data: I think they have a tremendous marketing department, coupled with a team of research scientists who provide on virtually none of those marketing promises.
And though I tried my best to read the article with an open mind, I am still left with the same fundamental skepticism about this new brand of political data alchemy.*
To be clear, I am not questioning the underlying science of psychometric targeting. Psychometric targeting simply categorizes individuals according to the standard “big five” personality traits, then treats these categories as market segments for the delivery of targeted advertising. Targeted advertising based on psychometrics is conceptually quite simple and practically very complicated. And there is no evidence that Cambridge Analytica has solved the practical challenges of applying psychometrics to voter behavior.
Here is a list of what you would need in order to apply psychometrics to voter behavior:
Dave Karpf is an assistant professor in the George Washington University School of Media and Public Affairs. He conducts research on the internet and organized political advocacy, and is the author of The MoveOn Effect: The Unexpected Transformation of American Political Advocacy (2012, Oxford University Press). When he writes about civic technology, he tries to play the role of “helpful critic.” He mostly focuses on the places where our proposed technologies presume a more willing government or a more uniformly engaged public than we actually have.