The nonsense – and danger – behind the algorithm economy

What do your Facebook likes say about you? Writer Sue Halpern discovered that algorithms, based on data collected about her, had assumed she was male, gay, single with a taste for cookie dough and dinosaurs when she is female, heterosexual, married, a coelic (can’t eat cookie dough) and once “liked” a female boxer nicknamed T-Rex… J.D.Allan

A few months ago The Washington Post reported that Facebook collects 98 data points on each of its nearly 2 billion users. Among this 98 are ethnicity, income, net worth, home value, if you are a mother, if you are a soccer mom, if you are married, the number of lines of credit you have, if you are interested in Ramadan, when you bought your car, and on and on and on.

How and where does Facebook acquire these bits and pieces of one’s personal life and identity?

First, from information users volunteer, like relationship status, age and university affiliation. They also come from Facebook posts of vacation pictures and baby pictures and graduation pictures. These do not have to be photos one posts oneself: Facebook’s facial recognition software can pick you out of a crowd. Facebook also follows users across the internet, disregarding their “do not track” settings as it stalks them. It knows every time a user visits a website that has a Facebook “like” button, for example, which most websites do.

The company also buys personal information from some of the 5000 data brokers worldwide, who collect information from store loyalty cards, warranties, pharmacy records, pay stubs, and some of the 10 million public data sets available for harvest. Municipalities also sell data – voter registrations and motor vehicle information, for example, and death notices, foreclosure declarations and business registrations, to name a few.

Facebook knows every time a user visits a website that has a “like” button. The trouble is, the algorithms then created by Facebook or other agencies for assessing all those “likes” can come to some very misleading assumptions about you, your credit rating, your hireability, and whether you may one day commit a crime. Judy Green

In theory, all these data points are being collected by Facebook in order to tailor ads to sell us stuff we want, but in fact they are being sold by Facebook to advertisers for the simple reason that the company can make a lot of money doing so.

Not long ago I dug into the depths of Facebook to see what information it was using to tailor ads for me. This is a different set of preferences and a different algorithm – a set of instructions to carry out an operation – than the one Facebook uses to determine which stories it is going to display on my so-called news feed, the ever-changing assortment of photos and posts from my Facebook friends and from websites I’ve “liked”.

Internet travels

These ad preferences are the coin of the Facebook realm; the company made $US2.3 billion ($3.2 billion) in the third quarter of 2016 alone, up from about $US900 million in the same three months last year.

And here is some of what I discovered about myself according to Facebook:

It’s hard to hide from the internet data collectors – and the consequences of what they then do with the results. Natalie Boog

That I am interested in the categories of “farm, money, the Republican Party, happiness, gummy candy, and flight attendants” based on what Facebook says I do on Facebook itself. Based on ads Facebook believes I’ve looked at somewhere – anywhere – in my internet travels, I’m also interested in magnetic resonance imaging, The Cave of Forgotten Dreams and thriller movies.

Facebook also believes I have liked Facebook pages devoted to Tyrannosaurus rex, Puffy AmiYumi, cookie dough and a wrestler named the Edge.

But I did not like any of those pages, as a quick scan of my “liked” pages would show. Until I did this research, I had never heard of the Edge or the Japanese duo Puffy AmiYumi, and as someone with coeliac disease, I am constitutionally unable to like cookie dough. I did “like” the page of the Flint, Michigan, female boxing sensation Claressa Shields, whose nickname is “T-Rex”. And that is as close as Facebook got to matching my actual likes to the categories it says – to advertisers – that I’m keen on.

And this is odd, because if there is one incontrovertible thing that Facebook knows about me, it’s the Facebook pages that I have actively liked. But maybe I am more valuable to Facebook if I am presented as someone who likes Puffy AmiYumi, with its tens of thousands of fans, rather than a local band called Dugway, which has less than 1000. But I will never know, since the composition of Facebook’s algorithms, like Google’s and other tech companies’, is a closely guarded secret.

It would be naive to think that there is a firewall between commercial surveillance and government surveillance. There is not. Michael Mucci

While Facebook appears to be making seriously wrong and misdirected assumptions about me, and then cashing in on those mistakes, it is hardly alone in using its raw data to come to strange and wildly erroneous assumptions.

Personality profile

Researchers at the Psychometrics Centre at Cambridge University in England have developed what they call a “predictor engine”, fuelled by algorithms using a subset of a person’s Facebook “likes”, that “can forecast a range of variables that includes happiness, intelligence, political orientation and more, as well as generate a big five personality profile”. (The big five are extroversion, agreeableness, openness, conscientiousness and neuroticism, and are used by, among others, employers to assess job applicants. The acronym for these is OCEAN.)

According to the Cambridge researchers, “we always think beyond the mere clicks or Likes of an individual to consider the subtle attributes that really drive their behaviour”. The researchers sell their services to businesses with the promise of enabling “instant psychological assessment of your users based on their online behaviour, so you can offer real-time feedback and recommendations that set your brand apart”. …

… read on at afr.com

© 2016. New York Review of Books. Distributed by the New York Times Syndicate.

Originally posted by Sue Halpern at Financial Review
27th December 2016

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