In their article, “The Data That Turned the World Upside down,” writers ANNES GRASSEGGER AND MIKAEL KROGERUS explain, “Big Data means, in essence, that everything we do, both on and offline, leaves digital traces. Every purchase we make with our cards, every search we type into Google, every movement we make when our mobile phone is in our pocket, every “like” is stored. Especially every “like.”
The same company which was behind both Trump’s online campaign and the early stages of Leave.UK was Cambridge Analytica – a Big Data cruncher.
A Spectator article reported the claims that the data crunchers had engineered Trump’s victory, through their analysis of vast amounts on online digital data, or “digital exhaust”, on the US electorate. ‘There are two assumptions: first that people who buy the same things and have the same habits — the same ‘data points’ — have similar personalities; secondly that your personality will help predict, say, whether you go for Coke or Pepsi, Clinton or Trump. ‘Behaviour is driven by personality,’ Nix [the head of Cambridge Analytica] said.”
Despite the counter claims online, I didn’t know what was more scary: that the data existed, that it could be analysed to such predictive and startling effect, or that it was a commodity to be traded to the highest bidder.
This segmenting of a population or “micro-targetting” has a worrying downside as expressed by Jill Lepore, a historian of polling at Harvard: “Politicians’ views were dictated by consultants, not principle, while voters were told only what they wanted to hear… ‘Data science is the solution to one problem but the amplification of a much bigger one — the political problem.’
These are just some of the issues that are raised by Big Data, and will be at the heart of this blog. The algorithms which drive our online habits, the fact that our social media data is for sale, that corporate or political interests can manipulate them for their own agendas, all revolve around the future implications of Big Data on how we, as a planet of more than 7 billion individuals, co-exist.
Questions need to be asked about who owns the data. What do they want to do with it? What skills are required to effectively interpret and visualize it? What impact will it have on developing economies? Will a focus on Big Data analysis come at the expense of other development issues? Is it skewed to a connected urban elite rather than the marginalized and vulnerable, risking a widening of the digital divide?
This is just the tip of the iceberg in a dizzying fast-changing field. But it’s immediately clear that big data isn’t a “neutral” tool, and exists within its own social, political and economic ecology which needs to be interrogated. What can we learn from the big data (r)evolution – from movies to politics, mobile health to disaster mapping – in relation to development theory, practice and new directions?
That’s what we’re hoping to explore in this blog.
THE SPECTATOR: The British data-crunchers who say they helped Donald Trump to win (Dec 3, 2016), by Paul Wood
BLOOMBERG: No, Big Data Didn’t Win the U.S. Election (Dec 8, 2016), by Leonid Bershidsky
VICE: The Data That Turned the World Upside Down (Jan 28, 2017), by HANNES GRASSEGGER AND MIKAEL KROGERUS