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Wednesday, May 3, 2017

Former Facebook Exec: "They're Lying Through Their Teeth"

Authored by Antonio Garcia-Martinez (former Facebook product manager), author of Chaos Monkeys: Obscene Fortune and Random Failure in Silicon Valleyoriginally posted at The Guardian,
For two years I was charged with turning Facebook data into money, by any legal means. If you browse the internet or buy items in physical stores, and then see ads related to those purchases on Facebook, blame me. I helped create the first versions of that, way back in 2012.
The ethics of Facebook’s micro-targeted advertising was thrust into the spotlight this week by a report out of Australia. The article, based on a leaked presentation, said that Facebook was able to identify teenagers at their most vulnerable, including when they feel “insecure”, “worthless”, “defeated” and “stressed”.
Facebook claimed the report was misleading, assuring the public that the company does not “offer tools to target people based on their emotional state”. If the intention of Facebook’s public relations spin is to give the impression that such targeting is not even possible on their platform, I’m here to tell you I believe they’re lying through their teeth.
Just as Mark Zuckerberg was being disingenuous (to put it mildly) when, in the wake of Donald Trump’s unexpected victory, he expressed doubt that Facebook could have flipped the presidential election.
Facebook deploys a political advertising sales team, specialized by political party, and charged with convincing deep-pocketed politicians that they do have the kind of influence needed to alter the outcome of elections.
I was at Facebook in 2012, during the previous presidential race.
The fact that Facebook could easily throw the election by selectively showing a Get Out the Vote reminder in certain counties of a swing state, for example, was a running joke.
Converting Facebook data into money is harder than it sounds, mostly because the vast bulk of your user data is worthless. Turns out your blotto-drunk party pics and flirty co-worker messages have no commercial value whatsoever.
But occasionally, if used very cleverly, with lots of machine-learning iteration and systematic trial-and-error, the canny marketer can find just the right admixture of age, geography, time of day, and music or film tastes that demarcate a demographic winner of an audience. The “clickthrough rate”, to use the advertiser’s parlance, doesn’t lie. 

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