Personalization paranoia or how I was stalked by Daniel Tiger

The thing about personalized ads and content on Facebook is that you don’t know exactly why the content you see ends up on your News Feed. While this algorithmic black box is well known to many and probably ignored by most, academic analysis of behavioural advertising rarely take a closer look at what personalized ads do to a person’s psyche.

poster-daniel-tigers
The Fred Rogers Company

The other day I was taking a daily scroll through my News Feed when I noticed an article from the Atlantic titled Daniel Tiger is Secretly Teaching Kids to Love Uber. For those of you without toddlers or a peculiar interest in kids’ TV shows, Daniel Tiger  is a friendly 4-year old tiger who teaches children how to cope with failure with happy-go-lucky songs.

Was the article served to me because I subscribe to the Atlantic’s Facebook page? I read several of their articles a week, so seeing an article from the Atlantic isn’t  too strange. However, I don’t see all of their articles, and the ones I do tend to be focused on topics related to the Internet economy (for obvious reasons).

Was it, in fact, the article’s reference to Uber, not Daniel Tiger, that made Facebook present this particular article to me? Or was it because Facebook had identified me as a parent and tended to suggest similar content to parents? Or did Facebook register that I googled the show at some point, and if I did, had I been signed into my Facebook account at the time or used private browsing? Or did Netflix share some of their viewing data with Facebook?

In this targeted online environment consent to terms and conditions and privacy notices make little sense. It is impossible to keep track of the myriad ways companies share and collect data, and a carte blanche is usually required to even begin using the service. While the goal might be efficient targeting to make advertisers happy, it results in personalization paranoia. Calling Facebook’s targeting a black box is therefore not an entirely accurate metaphor. I would prefer to call it a one-way mirror — everything we do is monitored, we’re vaguely aware of it, but we have no idea who’s watching.

 

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The shrinking long tail of online media

For many media companies,  online distribution has been seen as a practical solution to audience fragmentation. Those who are not interested in primetime content can satisfy their needs by shows that are available online, on-demand. The problem with this “long tail” solution is finding the right content for these fragmented audiences. Going through an extensive catalogue of different tv and radio shows won’t bring you any closer to satisfaction than simply succumbing to the alluring yet numbing power of  American Idol or Big Brother.

The solution to this particular problem is, naturally, personalization. In an interview for Wired, Netflix’s Neil Hunt stated that in the future, Netflix’s recommendation algorithm will be so accurate that it will be able to give users “one or two suggestions that perfectly fit what they want to watch now.”

Obviously, Netflix is not there yet:

Huffington post
Source: Huffington post

Snide remarks aside, Hunt’s vision is probably true, but not because Netflix is about to find the golden piece of code that will make this prediction of the future reality, but simply because media consumption is very, very predictable. In a Harvard Business School study from 2008, Anita Elberse found that the top 10 % of songs on the music streaming service Rhapsody accounted for 78 % of all plays and that the top 1 % accounted for nearly one-third of all plays (cited in Misunderstanding the Internet, 2012). The tail had gotten longer, sure, but the big profits were still made where the tail was the thickest. A quick glance at YouTube statistics would confirm this.

“Predicting” that people will want to see Game of Thrones after seeing the Walking Dead isn’t difficult, it’s just … probable. Personal preferences play in, of course, but I don’t think I’m going out on a limb when I say that 10 viewing profiles with appropriate standard recommendations would fulfil 90 % of all viewers’ needs.

The thing with predictions is that they effectively make the tip of the long tail obsolete. It’s more likely that primetime shows will be predicted, since it is quite probable that a viewer will be content with what’s offered. Suggesting less-popular shows is riskier, as the prediction is more likely to go wrong. Instead of watching one primetime show we’ll watch nothing but primetime, as recommended by algorithms.  At least with Netflix’s failed recommendations, it’s possible to find something completely unexpected.

Not so neutral net neutrality?

Finnish MEP candidate Otso Kivekäs from the Greens recently compared the internet to road infrastructure. In his analogy, he said that removing net neutrality would be like allowing “the company that builds the highways to put different speed limits on different car brands: Audis could drive 100 [km/h] and all others 60 [km/h]. And everybody would pay the toll.”

If ISPs could discriminate as they wished and simply adjust the speed of different services, either according to the highest bidder or simply because of their own preferences (goodbye, Skype), this would surely be a great injustice to all internet users. A removal of net neutrality left completely unregulated is not ideal, to say the least. But let’s look at it from another perspective.

Wonder why Netflix, Google and Apple are such great supporters of this “consumer right”? Because 30 % of US internet traffic is used by Netflix, 15 % by YouTube and 2 % by iTunes, according to a study by Sandivine.  Still, these companies pay nothing for the infrastructure yet benefit from it immensely. It is not difficult to see why ISPs would seek to receive compensation from the two companies that use half of all bandwidth.

Sandivine: internet traffic statistics

Netflix and YouTube obviously top the charts because they are immensely popular services and because video uses a lot of data, especially full HD.

Now, using the road analogy once more, this is essentially a case where two companies fill up all the roads with their trucks and continue to be treated like regular commuters on their way to work.

An article from Financial Times also addressed this issue, and according to the editor, “net neutrality no longer works.”  FT applauded the FCC’s decision, expressing that “if customers are willing to pay more for a premium service, as they do with mobile phone contracts or business class travel, then they ought to have the right to do so.”

Business class travel is hardly a good analogy, as people already pay for faster internet subscriptions. Rather, one could take the road analogy one step further. There are a lot of rules which already dictate traffic in order to make it more effective: bike lanes, bus lanes, toll discounts for car pools, the obligation to give way to trams and so on.

What if internet traffic that serves the public interest could be given right of way? Setting aside the difficulty of defining the public interest for a moment, one could think of at least access to public documents and services to begin with. Services that eat up a disproportionate amount of all bandwidth (read: Netflix and YouTube), on the other hand, could then be “taxed” for their  excessive bandwidth use, a fee which would be earmarked for investment in new broadband infrastructure. Now, this might not be what the FCC (or FT) had in mind, but it is a conceivable alternative to net neutrality as we think of it today. Doesn’t positive net discrimination have a nice ring to it?

This would also prevent ISPs from using broadband infrastructure investment as their hobbyhorse excuse. Whenever proposals might make business more difficult (or less profitable) for ISPs, they always state that new regulation will slow down investment on broadband infrastructure (see here, here and here). The arguments are, of course,  just corporate BS, since in Europe broadband infrastructure has been highly dependent on tax money (roads anyone?). By combining so-called “premium access fees” with broadband investment, the ICT giants could help maintain the infrastructure they make their billions from.