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Archive for People

Big Data and Bespoke Experiences

“The information is then wiped from our system…” is the promise of Alibaba’s new robot-hotel chain, where guests must provide biometric (in the form of facial recognition) information in order to get access to their rooms. The company promises that the guests information will be wiped from the system, but let’s face it, it never is. This isn’t some high-tech insider information I’m imparting here. This is simple observation of the numerous times that a data breach has revealed that information that was supposed to have been deleted was hoarded on a server somewhere. So why do people engage with digital services that collect this data? Why are people sharing all kinds of personal information and biometrics in the service of “convenience” and “frictionless transactions”.

Line drawing of a service robot
Companies are banking on robots being able to offer a bespoke consumer service.

Part of the attraction of ANY service is that your experience with it as a consumer evolves over time. You go to the same bar after work every Friday night? The bartender is going to learn and know your name and your favorite drink. Stay at the same hotel every time you travel to Schenectady to visit your parents? Guess what, they’re going to remember you too (and that towels keep mysteriously going missing from your room.) In a purely physical form, this has emerged in the form of various reward systems (buy three bagels, get the fourth free, for example).

This familiarity over time is part and parcel of delivering a recurring service to people. It’s okay when humans do it to humans, right? The fact the Jim the Barista recognizes you on sight is a comfort rather than creepy. But when a computer does it, it becomes a conspiracy. It becomes “Big Data”. It becomes, as we are told, yet another form of control rather than a convenience.

This is the big disconnect that those who sound alarm bells bout data collection and aggregation are missing. Almost daily I encounter rants and discussions about the ethical collection of information, about how we’ve allowed our homes to essentially be wiretapped through our screens and devices. And generally, they all end with something like “wake up sheeple”. But what they all miss is that these devices and services are, ultimately, tapping into a long-ingrained comfort system. It’s not that people are not aware that their information is being collected, it’s that the information is being used to provide them with a more personal experience and thusly, the collection is acceptable. It’s like the old Cheers tagline “where everybody knows your name”. These online services and devices are simply a continuation of that understanding of how hospitality works best.

 In order to provide the best possible service to a customer/client, data must be collected. This goes the same for the guy tending bar at Cheers and the web-service you buy your bespoke knitted socks from. The big difference to you as a consumer is that the guy at the bar is a dead-end, the information may go out in gossip and casual conversation, but it’s not going anywhere else. In the case of the little web-service, that’s a different story. That information may (depending on who they are using to provide their services to you) be polished, anonymized and added to a much larger pool of data out there. Or it may be stored online so they know just who you are and how many pairs of pink-cherry alpaca socks you bought from them. In either case, you get a warm fuzzy whenever you reconnect with that bar or service.

So what you are fighting against, if you truly want to change the minds of all those “sheeple” who are willingly sharing their personal information willy-nilly all over the internet, is THAT feeling. You’re not fighting an idea, or a sense of security or even a lack of digital education. When you can marshal a way to counter that feeling of bespoke, the warm fuzzies that come with feeling like a service *knows you* the way your favorite supermarket checker does, then and only then will you have a way to bring data sharing back under control on the consumer side of things.

An Internet Analogy via the Futility of a Horny Spotted Towhee

I’m sure they have a word for this, the rest of the birds that litter my yard post-sunrise must have seen this kind of obsession more than once, Spotted Towhee.  Repeatedly flinging yourself at an imaginary enemy, ignoring any and all actual challengers in favor of this one, true nemesis. Your development has been stunted, sidetracked by a challenger of your own making, by your inability to simply turn your head to see that there is more to do in a day than just batter the glass.

When you arrived, you had a girl.  I saw her. Shy and dim-colored, you told her you’d be right back, didn’t you.  That you just had to prove this one guy, this one imaginary foe you saw through your pane of glass was wrong.  Then you would be free, then you could be together. But every morning, every time you look, there’s another one.  And another. It’s like they don’t hear you, like they don’t understand that you’re right. There’s always another bird in that little window.

Where is she now Towhee?  Did she get tired of waiting while you ranted and raved at your glittering screen?  This perfect specimen of opposition that exists only because you keep going back to call it out, rather than stretching your wings and considering the rest of the world.

I’ve blocked you from the object of your obsession more than once now.  Chased you off, spent time and energy, erected barriers of tinsel and fabric to keep you from seeing that imaginary enemy. Tried to get you to see that your time would be better off spent building your bower, on paying attention to that shy lady bird who waited every night for you to finish your screed.  Instead you flung yourself at an illusion until panting and spent, energy poured out in a tirade that feels like a real fight, that feels like a defense of that idea you hold most dear.  But your dear has left, flown off with another bird who was more interested in being there than in being the victor over an imaginary foe.

And at the end of the day, when that shining pane of glass finally goes dark and you pick and pluck at the remnants of cheese puffs and bits of bread the other birds felt beneath their notice, you feel strangely unfulfilled.  There was no victory. There was no triumph. There was only a null response as the other bird vanished due to a change you couldn’t comprehend. Look up, Spotted Towhee, look out into the larger world. Forget the glass, forget the enemy that cares not for winning or losing.  Go find another shy bird and be free.

The Simple Exchange of Please and Thank You

I’d like to make a request of all you personal AIssistant programmers, you engineers at Apple, Google, Microsoft, all of you who are responsible for iterating on human/AI exchanges.

I’d like to be able to say please and thank you to my voice controlled computing.

It seems like a minor thing, doesn’t it?  A quaint nicety falling by the wayside in the pursuit of one more step towards the Singularity.  But what you are forgetting, my engineers, is that while you are training your AI’s to talk to us, those AI’s are training us to talk to them.

Much like cats, but with less shedding.

A request from a person often forms a sort of closed-loop.  It’s a format we learn, something that most cultures have.  An In, a Confirmation, A Request, a Confirmation and an Out.  To your average human, this feels complete.  In fact, interrupting this sequence feels rude.  Failing to complete this sequence just leaves one feeling uncomfortable, the same kind of uncomfortable you get when someone fails to say “good bye” before they hang up the phone.  Depending on the person/culture this feeling can range from a mild annoyance to an offence that requires a response.

It’s not always pretty.

 

As an example, let’s say we have a diner in a restaurant, ordering a meal from an AIssistant (like Siri or Hey Google).  The interaction might go something like this:

DINER: “Hey Waiter.” (In)

WAITER: “What do you want to order?” (Confirmation)

DINER: “I would like the Salmon Mousse, please.” (Request)

WAITER: “One Salmon Mousse, coming right up.” (Confirmation)

DINER: “Thank you.” (Out)

You’ve probably had thousands of exchanges like this over the course of your lifetime.  At the end the waiter is released from the encounter by the Out and both parties are free to move on to other things.  There is a clear In and Out, nobody is left hanging, waiting for a followup or a new request.  In fact, you may have had an experience or two when the Waiter has left the exchange early, before the second Confirmation or before the Out.

It left you feeling a bit slighted, didn’t it.  Maybe a little confused.  Definitely not quite right, though you might not have understood why.

This type of exchange flows smoothly, we have an idea in our heads of how it will play out.  It’s comfortable, familiar.  It’s successful execution triggers a feeling of satisfaction in both parties similar to the way you feel when picking up resources in Clash of Clans or creating a cascade in Candy Crush.

With the current state of Voice Recognition Technology, this same exchange is truncated, cut short:

DINER: “Hey, Waiter?”

WAITER: “Yes?”

DINER: “I would like the Salmon Mousse, please.”

WAITER: “Salmon mousse with peas.”

And boom, you’re done.  Misunderstanding of the word please aside, there’s no Out here.  The Diner has to trust that they will get what they want.  They are left hanging and, when the Waiter delivers peas alongside the Salmon Mousse they are frustrated, annoyed.  The exchange fails in the users mind, the AIssistant is cast as unreliable.

Once you’ve had a few of these sub-optimal exchanges with your AIssistant, you stop using natural language.  Every please and thank you, because they are so often misunderstood or they are ignored, or they cause a misunderstanding, gets dropped.  These conditioned responses, designed to get the best possible reaction from a human, become a burden when talking to an AI.  Your exchange becomes:

DINER: “Hey, Waiter. Salmon Mousse, plate, dining room, extra fork.”

WAITER: Delivers plate of Salmon Mousse on a plate to the dining room with an extra fork.

Yikes! This is no longer a “natural language” request.  The diner had started to simply deliver a string of keywords in order to get the end result they are looking for.    The user, the human part of this equation that natural language voice recognition is specifically being designed for, has abandoned natural language entirely when talking to their AIssistant.  They have run up against the Uncanny Valley of voice and have begun treating the AIssistant like a garden variety search engine.

Which wouldn’t be a problem if it only affected the AIsisstant.  In fact, it makes things run much more smoothly.  But these voice patterns tend to stick.  They backflush into the common lexicon of words (look at words like LOL and l33t that have entered spoken language and are here to stay, they exist only because of the constraints of technology).  Listen to a voice message left by someone who habitually uses Voice to Text.  You’ll find they have a tendency to automatically speak their punctuation out loud, just like you need to when dictating an email or a text message.

Please and thank you cease to be Ins and Outs of a conversation, they instead become stumbling blocks, places where your command sequence fails.  These niceties that we use to frame requests in the spoken language start to get dropped not because nobody’s teaching them, not because humans are getting ruder, but because they are being trained back out again by interaction with AIssistants that fall a bit too shy of being human.

The next step becomes complex.  Do we split language into a “conversation” and a “command” form?  Or do we end of abandoning the conversational form altogether in favor of the much more efficient (but far less communicative) string of key words?  It will be interesting to see if we pass each other in the night, humans and AIssistants, with the human language patterns becoming even more AI friendly as the AI language recognition software gets better at handling our natural way of speaking.

Either way, please and thank you, those natural addresses that help to keep requests couched in a tidy little package, may be one of the first victims.