The hundred-billion-dollar question: do the products and services we've been discussing truly constitute a system, a continuous fabric of computational awareness and response?
Someincluding, it must be said, some of the most knowledgeable, prominent, and respected voices in academic ubicompwould say that they clearly do not. Their viewpoint is that originators such as Mark Weiser never intended "ubiquitous" to mean anything but locally ubiquitous: present everywhere "in the woodwork" of a given, bounded place, not literally circumambient in the world. They might argue that it's obtuse, disingenuous, or technically naive to treat artifacts as diverse as a PayPass card, a SenseWear patch, a Sensacell module, a Miconic 10 elevator system, and a GAUDI display as either epiphenomena of a deeper cause or constituents of a coherent larger-scale system.
If I agreed with them, however, I wouldn't have bothered writing this book. All of these artifacts treat of nothing but the same ones and zeroes, and in principle there is no reason why they could not share information with each other. Indeed, in many cases there will beor will appear to bevery good reasons why the streams of data they produce should be merged with the greater flow. I would go so far as to say that if the capacity exists, it will be leveraged.
To object that a given artifact was not designed with such applications in mind is to miss the point entirely. By reconsidering them all as network resources, everyware brings these systems into a new relationship with each other that is decidedly more than the sum of their parts. In the chapters that follow, I will argue that, however discrete such network-capable systems may be at their design and inception, their interface with each other implies a significantly broader domain of actiona skein of numeric mediation that stretches from the contours of each individual human body outward to satellites in orbit.
I will argue, further, that since the technical capacity to fuse them already exists, we have to treat these various objects and services as instantiations of something largersomething that was already by 1990 slouching toward Palo Alto to be born; that it simply makes no sense to consider a biometric patch or a directional display in isolationnot when output from the one can furnish the other with input; and that if we're to make sense of the conjoined impact of these technologies, we have to attend to the effects they produce as a coordinated system of articulated parts.
One of the more significant effects we should prepare for is how fiercely relational our lives will become. In a world saturated with everyware, responses to the actions we take here and now will depend not only on our own past actions, but also on an arbitrarily large number of other inputs gathered from far afield.
At its most basic, all that "relational" means is that values stored in one database can be matched against those from another, to produce a more richly textured high-level picture than either could have done alone. But when the number of available databases on a network becomes very large, the number of kinds of facts they store is diverse, and there are applications able to call on many of them at once, some surprising things start to happen.
Consider the price of your morning cup of coffee. At present, as any businessperson will tell you, retail pricing is one of the black arts of capitalism. As with any other business, a coffee retailer bases its pricing structure on a calculus designed to produce a profit after accounting for all of the various costs involved in production, logistics, marketing, and staffingand in many cases this calculus is best described as an educated guess.
The calculus is supposed to find a "sweet spot" that balances two concerns that must be brought together to conclude a sale: the minimum the retailer can afford to charge for each cup and still make a profit, and the maximum you're willing to pay for that cup.
Famously, though, there's many a slip 'twixt cup and lip. For one thing, both values are constantly changingmaybe as often as several times a day. The first fluctuates with the commodities market, transportation costs, and changes in wage laws; the second responds to moves made by competitors as well as factors that are far harder to quantify, like your mood or the degree of your craving for caffeine. Nor does any present pricing model account for things like the variation in rent between different retail locations.
There's simply no practical way to capture all of this variability, and so all these factors get averaged out in the formulation of pricing structures. However expertly devised, they're always something akin to a stab in the dark.
But remember the event heap? Remember how it allowed a value entered here to affect a process unfolding over there? A world with ubiquitous inputs and event-heap-style coordinating mechanisms writ large turns this assumption upside down. Imagine how much more fluid and volatile the price of a tall decaf latte would be if it resulted from an algorithm actually pegged to something like a real-time synopsis of all of the factors impingent upon itnot only those involved in its production, but also whatever other quantifiable considerations influenced your decision to buy it.
Objections that consumers wouldn't stand still for such price volatility are easily countered by arguing that such things matter much less when the customer does not attend to the precise amount of a transaction. This widely happens to be the case already when the point-of-purchase scenario involves credit and debit cards, and it will surely happen more often as the mechanism of payment increasingly dissolves in behavior.
Say the price was a function of the actual cost of the Jet-A fuel that flew this lot of beans in from Kona, the momentary salary of the driver who delivered it...and a thousand other elements. Maybe it reflects a loyalty bonus for having bought your morning jolt from the same store on 708 of the last 731 days, or the weather, or even the mass psychology of your particular market at this particular moment. (Derivedwho knows?from the titration of breakdown products of Prozac and Xanax in the municipal sewage stream.)
This is economics under the condition of ambient informatics. As it happens, many of these quantities are already easily recoverable, even without positing sensors in the sewers and RFID tags on every bag and pallet.
They exist, right now, as numeric values in a spreadsheet or a database somewhere. All that is necessary to begin deriving higher-order information from them is for some real-time coordinating mechanism to allow heterogeneous databases, owned by different entities and maintained in different places, to talk to each other over a network. This way of determining price gets asymptotically close to one of the golden assumptions of classical economics, the frictionlessness of information about a commodity. Consumers could be sure of getting something very close to the best price consistent with the seller's reasonable expectation of profit. In this sense, everyware would appear to be late capitalism's Holy Grail.
And where sharing such information was once anathema to business, this is no longer necessarily true. Google and yahoo! already offer open application programming interfaces (APIs) to valuable properties like Google Maps and the Flickr photo-sharing service, and the practice is spreading; business has grown comfortable sharing even information traditionally held much closer to the vest, like current inventory levels, with partners up and down the supply chain. When mutual benefit has once been scented, connection often follows.
Beyond this point, the abyss of ridiculously granular relational micropayment schemes opens up. Accenture Technology Labs has demo'd a payper-use chair, for example, which monitors use, charges according to a schedule of prices that fluctuates with demand, and generates a monthly statement. While one hopes this is at least a little tongue-in-cheek, there is nothing that separates it in principle from other everyware-enabled dynamic pricing models that have been proposedclose-to-real-time insurance premiums, for example, based on the actual risk incurred by a client at any given moment.
Relationality has its limits. We know that a change anywhere in a tightly-coupled system ripples and cascades through everything connected to it, under the right (or wrong) circumstances rendering the whole mesh exquisitely vulnerable to disruption. Nevertheless, it's hard to imagine that a world so richly provisioned with sources of information, so interwoven with the means to connect them, would not eventually provoke someone to take maximum advantage of their joining.