2018 Outlook on Fake News

January 8, 2018

(This article was originally published at Big Data, Plainly Spoken (aka Numbers Rule Your World), and syndicated at StatsBlogs.)

Happy New Year to my blog readers!

I am starting the new year with a series of posts: each reviews a key issue covered on this blog in 2017, and I will discuss what might be in store for 2018.

First up is FAKE NEWS.

What happened in 2017

If I had a vote, I’d have chosen “fake news” as the phrase of 2017. Fake news is like that famous non-definition of pornography, you know it when you see it. It is this rare chameleon that pleases both parties equally. First, it was the Clinton supporters who claimed that voters were duped by “fake news” generated by Republicans or related entities. Then, when Trump became President, he seized the phrase, and made it his own – now, liberal-leaning news organizations are the “fake news media” who disseminate false information to the American public.

The term “fake news media” doesn’t make much sense – how does one “fake” a medium? But by adding the third word, the President has shifted the context of the issue from the contents of the news to the creators of the news. He portrays an awfully naïve, black-and-white world in which a media company is either “fake” or not “fake”, where all news reported by an alleged “fake” media company are “fake news.”

The emphasis on authorship runs against the recent current in media consumption. The invention of social media and user-generated content – much of which written pseudonymously or by people without name recognition – has tapered our awareness and appreciation of who’s doing the writing. When we consume Yelp or Amazon reviews, we barely register who authored them. Mainstream name-brand media has been withering before the President ironically saved them from the quicksand of online anonymity.

Suddenly, the technology giants also found themselves in the spotlight – for their alleged role in spreading “fake news.” In particular, Facebook and Google act as gatekeepers of online content. As startups, they cultivated a brand image of being objective, non-commercial, judgement-free “organizers” of information.

The “fake news” controversy has spotlighted that in later life, Google and Facebook morphed into gigantic advertising agencies, reliant on earning advertising revenues from commercial partners. The “eyeballs” of their users are the new oil. They must keep users coming back and sticking around, like drug addicts.

Advertisers want eyeballs, and Google and Facebook are extremely efficient at delivering them, through a number of tools such as “collaborative filtering” algorithms that control what individual users see when they search the Web or open their social media accounts, and A/B tests used to discover the conditions under which users interact with advertising messages. Needless to say, a lot of advertising messages can properly be called “fake news.”

Machine-learning algorithms fundamentally measure “success” based on view counts, which can easily amplify “fake news” through an well-known echo-chamber effect. Additionally, an army of “optimization experts” is available for hire to manipulate the output of those algorithms. The various futile attempts to “get rid of fake news” has awoken users to the amount of control Facebook, Google and similar companies exercise over one’s reading materials.

What to expect in 2018

The controversy over “fake news” and “fake news media” will not end in 2018. The President will continue to call out anyone daring to disagree with him as “fake news media.” Facebook and Google will roll out and roll back various “solutions” to combat “fake news” but no silver bullet will be discovered. The two tech giants will remain gargantuan advertising agencies seeking to monetize our attention: they won’t find enough paying customers to wean themselves off from advertisers.

The good news: the failed attempts to control “fake news” will teach us a lot about the nature of the search/discovery algorithms that control our online lives. Developers of these algorithms will benefit greatly from the increased scrutiny, and need to ply open the black box. We will appreciate that algorithms are neither objective nor judgment-free.

Three dead bodies will be resurrected: fact-checking, authorship, and expertise, in that order. Media companies will come under pressure to reinvest in fact-checking; authorship will become a key weapon in the fight against lies; and consumers will re-discover the value of experts, hopefully before the end of the year.

Please comment on the article here: Big Data, Plainly Spoken (aka Numbers Rule Your World)

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