Tag Archives: Analytics

Predictive Analytics and The End of “Just Looking”

Anyone who’s spoken with me about it knows I’m a huge fan of good predictive analytics and the services built on them.  I use a machine-learning-algorithm based news reader (Prismatic) I listen to computer generated radio stations (on Spotify and Grooveshark, among others), and I let Google Now generate most of my driving directions for me.  These services yield two major benefits: first, they save me a TON of time, and second, they expose me to more content and with way greater variety than I would find on my own.  The obscure blog posts I find through Prismatic about database engines are amazing, and there isn’t a snowball’s chance in hell I would be spending my own time rooting through the dark corners of the internet for them.

The problem with these services however, is that they are extremely efficient learners. People love to hate Apple autocorrect – and I don’t blame them.  Their system is imperfect, and can be annoying or even harmful if you use it without paying attention to the output.  Don’t hit the send button immediately after sending a message to your crush or ex.  But by far my bigger worry with these systems is how quickly and how well they do learn to conform to my demands.

I find my iphone typing to be extremely accurate, given how much I write on that device and how small its virtual keyboard is.  People make typos using full sized keyboards (at least I do) that refuse to autocorrect their users, so some degree of inaccuracy is to be expected.  But my iphone comes as close to getting it as right as my laptop does, despite having a keyboard that A) doesn’t physically exist and B) is about 1/50th as big as the laptop’s.  Unfortunately, it also picks up my idiotic quirks and jokes, and assumes they are to be repeated in the future.  My repertoire is littered with garbage in real life, and my iphone reflects that.  Unfortunately, to give me maximal leverage, it offers me all these words in all situations, including MANY where they are either too casual or too awful to be used.

The problem gets far worse with services like Prismatic, which are tasked with figuring out what kinds of things I might like to read based on what I tell it I like and what it’s seen me read before.  In case I haven’t made it obvious, I love this service. LOVE it, go download it right now.  The problem in this case is not that they can’t figure out what I will look at if offered, but that they know EXACTLY what I’ll click if offered, no matter how little I actually want to read it.  Because of this, Prismatic has begun littering my stream with incendiary garbage from right wing nutjobs.

I have filters set up to catch news about Congress, the Democratic party, and all sorts of economic and political topics.  At first, these created a small trickle of crap from right wing sources, which I clicked through and read out of a mixture of fascination and curiosity.  (I am sad but not surprised to say I am no less enlightened after having read them.)  The problem is that as soon as Prismatic caught me reading a few of these, it figured out it had found my catnip, and started pushing it into my news stream at increasing rates.  The problem is that while I want lots of varied sources for my news, I have a finite amount of time, and I am unwilling to spend a lot of it filtering my already FILTERED content.  The twin joys of Prismatic are that it will search anywhere for a story I might read – and that it will discard everything I am not going to click on.  The problem is that there’s a trick-space between the two categories, and now I am stuck in the swamp of stuff I will click on but don’t want to read.

And it’s not just Prismatic, or for that matter only niche startups.  I hate buying anything on behalf of a family member on Amazon because their shopping preferences get woven into my recommended purchases pretty quickly.  This problem got even worse after a night browsing exotic sex toys on Amazon, for a practical joke that was never fulfilled (for a college friend – NOT a family member).  Problem is that although I abandoned the joke Amazon still thinks I might be interested in buying something raunchy along with my Javascript textbooks (see? coders CAN have sex lives!).

I see the same annoying problem in my Facebook feed – clicking on an annoying friend’s post to see what they’re talking about tells Facebook not that I want to see it but that I WILL engage the content if it’s put in front of me, and so they start shoveling more of it my way. This process can be managed, at least to some extent,  by pruning my newsfeed, and selectively telling Facebook what I don’t want to see.  The same is true of my Amazon account, Prismatic, and I’m guessing my iphone suggestions dictionary too.  But doing so robs these services of the advantages I wanted from them in the first place, which sucks.

I *could* spend time managing my iphone dictionary, but then I wouldn’t end up saving time typing.

I *could* trim everything I don’t want to see in my Prismatic, but if I force the feed to conform to my expectations it will stop giving me the good surprises (obscure coding posts etc).

I *could* tell Facebook every time I see something I don’t want to read, but that would make my social network a CHORE rather than an entertainment, and I don’t want more work from a hobby.

The problem with super sensitive learning tools like these systems is that they eventually push me to censor my electronic activities, because I know that they will be added to my suggestion algorithms, and that I will either have to put in lots of work later to fix them or deal with degraded services. Instead, I end up limiting my engagement ahead of time, to make sure that my electronic servants know a consistent, vanilla version of myself, and that they focus their efforts on serving him. Because my computers know me so well, and because they are by definition shameless (gmail has a fascinating sort-of counterexample) I can’t go around “just looking” like I can at a human run establishment, for example.  Imagine if every time you went to Old Navy someone came up to you with a pink thong and said “you looked at the ugly polka dot shirt last time you were here, maybe you’ll like this too!”.  Or if at a restaurant your waiter greeted you and a date with “Hey fatty – you want me to get you the quadruple cheeseburger with extra lard again?”.

Humans have in this case a useful combination of incompetence and emotional sensitivity that mostly keeps them from embarrassing us that way.  A mall employee can’t usefully track everyone in the building and every store they’ve gone to, and everything they’ve looked at there.  Google can.  Facebook can.  And it’s not just on their sites.  When you browse the internet logged into Facebook, every time you land on a page with a “Like us on Facebook!” button or the option to log into a service through Facebook (which – for the record – I use all the time) those trigger little programs that report your presence there to Facebook.  Keep an eye out for social icons next time you’re looking for porn frying pans online and you don’t want to be noticed.

The good news is that there’s a decent chance that as analytics engines get even better, services will begin including sensitivity training in them, to avoid embarrassing or inconveniencing us this way.  The really bad news is that all this really means is that invasive web services will be made less noticeable and annoying, NOT that they will stop watching us.  I’m not Amazon, but I’d bet that if I was I would be giddy every time a user told me to ignore something I had been looking at before, because it’s a far richer source of information than is the fact that I landed on that page.  Now Amazon knows not just what I looked at but how I want to be seen, or at least treated.  Same for Facebook, Google, etc.

To be clear, this isn’t a condemnation per-se.  Web services watch and collect this information because it does make them more attractive for users like me, and I am generally pleased by the level of service I get in return (for free usually).  The problem is it means they are strongly disincentivized from ignoring any useful information about me that they find, and doubly so for information I tell them not to pay attention to.

One sort of exception to this is Apple, which seems to have made their enhanced privacy offerings a point of differentiation from their competitors.  So for instance Apple is fighting to protect various privacy standards (as is Mozilla – to their credit).  But Apple is fundamentally a premium company, and they don’t compete in most areas with for-free services like Facebook and Google.  Moreover, the model of paying for expensive, high quality web products makes no sense in 2013, when the vast majority of dominant web technologies are available to users at zero cost and with insanely high quality.  There already exist for-pay social networks, and you’d have to threaten me with physical harm to get me to switch from Facebook to one of those.

What this means is that anyone wanting to use certain features of the modern tech world without undue attention will have to do so conscientiously and with some effort.  There simply is no replacement for the services I want and expect as part of the modern web that will give me free access without the annoying data-mining.  For me, being able to use Gmail, Facebook, Amazon, Prismatic etc is worth the trade-off.  No questions asked, I’d rather figure out how to get along with free tech than live without it.  The downside of this all is that for me, and for anyone else who wants to do the same, for now and for the foreseeable future there is no such thing as “I’m just looking”.