How your views are shaped by the websites you visit

by Marc Wilson / 20 March, 2018
Photo/Getty Images

Photo/Getty Images

RelatedArticlesModule - How your views are shaped
Am I alone in wondering why the list of things that websites tell me “You may also like …” doesn’t include things I actually would like? There’s a lot of money in getting this right. But rather than having a human army tabulating who watched, read or bought what, then collating the information and feeding it back, computer algorithms are behind this.

At work are machine-learning programs that not only cross-tabulate people’s likes, but also use neural-style networks to build a broad set of preferences and potential preferences: things you mightn’t think you’ll like but will; things you don’t even know exist because they’re so new.

It’s a phenomenon people are increasingly worried about, because it calls to mind The Terminator’s Skynet and HAL’s wilful “I’m sorry, Dave, I’m afraid I can’t do that” in 2001: A Space Odyssey. YouTube users, for instance, are querying the logic behind the selection of videos that automatically loads when the current one finishes. Even if you die in front of the screen, they’ll just keep cycling and, ironically, adding this to the data from which the algorithm draws.

Following a recent Guardian story about promoted YouTube material in the lead-up to the 2016 US presidential election, Virginia Senator Mark Warner has warned that the video host may be a threat to democracy. The Guardian reported a small increase in conspiratorial, disproportionately anti-Clinton “fake news” landing in people’s feeds before the November election.

That’s ironic, if true, given that “fake news” is the term electoral victor Donald Trump pushed into the mainstream to describe negative stories about him, his campaign and, now, his Administration.

Dartmouth College political scientist Brendan Nyhan.

There’s been a lot of lefty-liberal hand-wringing over the rise of internet-driven spaces where people with even the weirdest views can find kindred spirits, as well as “evidence” to support their beliefs. People are worried that these “echo chambers” insulate the wacky from the mainstream and render anyone else directed there by YouTube an uncritical idiot consumer.

Hyperpartisan “news” sites (not to mention Macedonian teenagers just making stuff up for clicks) have become all the rage, but they pre-date the 2016 US election. Just look at New Zealand’s Whale Oil “scandals” of 2014, back when we were still so idealistic. These have proliferated, however, like a virus.

What would your internet history look like if you made it available to me? Again, researchers are using automation to gather this data. In the US, you can sign up to let survey firm YouGov install a plug-in that will record the websites you visit and how long you spend on them and in what order.

Dartmouth College political scientist and professor Brendan Nyhan and his colleagues have made hay with YouGov data, after working out how to crunch the huge numbers it generates. For instance, he’s particularly interested in news consumption, but notes that people use the internet for a lot of other things. “There’s a lot of porn,” he says, and there’s a lot of work to sift and crunch it all.

So, what’s the evidence for the scary echo chamber? Or fear that ilovemyfreedom.org and the like are polluting democracy and convincing voters that Trump (or, in a minority of cases, Clinton) is The Saviour? Nyhan’s research is sort of reassuring. Most people draw about equally from news sites across the political spectrum. But about 10% of those who read fake news read only pro-Trump fake news. Of course, these people are probably Trumpian to the core, so they’re more than likely reading news that supports what they already believe. What it does mean is that they’re unlikely to ever swing back to Clinton, however.

“Do the people who use fake news also watch more porn?” I ask Nyhan. He pauses thoughtfully, before saying he hasn’t looked to see. I bet he will when he gets back to his office.

This article was first published in the March 10, 2018 issue of the New Zealand Listener.

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