Trump Campaign Used “Fashion Data” to Target Conservative Voters

According to Christopher Wylie, the Cambridge Analytica researcher-turned-whistle-blower, clothing taste is such a precise indicator of political preference that it was a key part of developing the now-infamous Facebook-aided AI models employed by the Trump Campaign in 2016.

“Fashion profiling played a bigger role in the 2016 American presidential election than anyone realized,” writes the New York Times, noting that “preferences in clothing and music are the leading indicators of political leaning.”

Calling fashion data a “key metric” during his address at the Business of Fashion conference last week, Wylie bluntly stated that internet-facing brand loyalty was “used to build AI models to help Steve Bannon build his insurgency and build the alt-right.”

“Fashion brands are really useful in producing algorithms to find out how people think and how they feel,” Mr. Wylie said, noting that Wrangler and L.L. Bean, in particular, were “brands that Cambridge Analytica aligned with conservative traits.”

(Wrangler and L.L. Bean both declined to comment for the story, presumably because they’re now getting charged rent between a Rock and a Hard Place — if they refute the notion, they piss off their current customers, if they affirm it, they can basically forget picking up new ones.)

As the Times explained, the “narratives of the great American brands, which play on the myths of the West and the (mostly male) frontier, are also the narratives of the Republican right. Those who choose to spend on the former are susceptible to the latter.”

“Cambridge Analytica preyed on [those choices] via algorithm, using data from the Facebook profiles of more than 50 million users without their permission.”

Getting a targeted ad in your feed is one thing, but “the fact that consumer preferences are used by influence Svengalis to sway votes means something else entirely.” We are what we wear, apparently.

You can read more about it at The New York Times.

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