Thesis 71


We're not very good at doing "smart" yet, and we may never be.

After 230 pages in which we've explored the vast and sprawling terrain of everyware in a fair degree of detail, perhaps we would be safe in venturing some guesses about the deeper nature of its challenge.

At root, I see it this way: as a civilization, our production of high-technological artifacts does not yet display anything like the degree of insight, refinement and robustness that toolmakers, furniture artisans, and craftspeople have developed over the thousands of years of their collective endeavor. Our business practices and development methodologies, the complexity of our technology and even the intellectual frameworks we bring to the task, militate against our being able to do so.

Nor have we so far been able to design systems capable of producing inferences about behavior nearly as accurate as those formed in a split-second glance by just about any adult human being.

In other words, we simply don't do "smart" very well yet, and there are good reasons to believe that we may never.

With regard to the tools we build, compare one of the most accomplished fruits of our high technology, Apple's iPod, with just about any piece of furnituresay, an Eames Aluminum Group lounge chair.

The iPod can fail in many more ways than the chair can, yielding to anything from a cracked case to the exhaustion of its battery to a corruption in the software that drives it. By comparison, just about the only way the chair can truly fail is to suffer some catastrophic structural degradation that leaves it unable to support the weight of an occupant.

Nobody needs to be told how to use the lounge chair. "Users" of any age, background, or degree of sophistication can immediately comprehend it, take it in, in almost all of its details, at a single glance. It is self-revealing to the point of transparency. The same can be said of most domestic furniture: you walk on a floor, lie on a bed, put books and DvDs and tchotchkes on shelves, laptops and flowers and dinner on tables. Did anyone ever have to tell you this?

The same cannot be said of the iPodwidely regarded as one of the best thought-out and most elegant digital artifacts ever, demonstrating market-leading insight into users and what they want to do with the things they buy. To someone encountering an iPod for the very first time, it's not obvious what it does or how to get it to do that. It may not even be obvious how to turn the thing on.

You needn't configure the chair, or set its preferences, or worry about compatible file formats. you can take it out of one room or house and drop it into another, and it still works exactly the same way as it did before, with no adjustment. It never reminds you that a new version of its firmware is available and that certain of its features will not be available until you do choose to upgrade. As much as I love my iPod, and I do, none of these statements is true of it.

Many particulars of the chair's form and structure result from a long history of incremental improvements, though of course it doesn't hurt that it was designed by a pair of geniuses. It is very well adapted to everyday life, and unless this particular chair affronts your aesthetic sense, it is likely to provide you with all three of the classical vitruvian virtues of firmitas, utilitas, and venustas: durability, utility and delight. The iPod, also designed by a genius, is undeniably delightful, but it falls short on the other two scales. Its utility has been compromised to some degree by "feature creep": As a combination music player, address book, calendar, image viewer and video device, it now does more things than its elegantly simple interface can handle gracefully.

But most digital tools people use regularly are not nearly as refined as the iPod. As technology companies go, Apple devotes an exemplary and entirely atypical amount of time, money, and attention to the user experience, and even so, it still gets something wrong from time to time.

Nor, of course, is the issue limited to MP3 players. Digital products and services of all sorts suffer from the same inattention to detail, inability to model user assumptions correctly, and disinclination to perceive interactions from that user's point of view. Even today, you'll occasionally stumble across a high-profile Web site whose navigation seems intentionally designed to perplex and confound. How much worse will it be when the interface we have to puzzle out isn't that of a Web site or an MP3 player, but that of the toilet, the environment-control system, the entire house?

We've come a long, long way from the simple and profound pleasures of relaxing into a chair, wrapping our palms around the warm curve of a mug, or flicking on a lamp when the dusk begins to claim the fading day. If we've, by now, mostly overcome the legendary blinking-12:00 problem that used to afflict so many of us in our dealings with vCRs, that is still emblematic of the kind of thing that happensand will continue to happenroutinely when complex technology pervades everyday life.

And this only gets more problematic because, as we've seen, so many applications of everyware rely on machine inference, on estimates about higher-level user behavior derived from patterns observed in the flow of data. A perfect example is the "smart coffee cup" Tim Kindberg and Armando Fox refer to in their 2002 article "System Software for Ubiquitous Computing," which "serves as a coffee cup in the usual way, but also contains sensing, processing and networking elements that let it communicate its state (full or empty, held or put down). So, the cup can give colleagues a hint about the state of the cup's owner."

But the word "hint" is well-chosen here, because that's really all the cup will be able to communicate. It may well be that a full mug on my desk implies that I am also in the room, but this is not always going to be the case, and any system that correlates the two facts had better do so pretty loosely. Products and services based on such pattern-recognition already exist in the worldI think of Amazon's "collaborative filtering"driven recommendation enginebut for the most part, their designers are only now beginning to recognize that they have significantly underestimated the difficulty of deriving meaning from those patterns. The better part of my Amazon recommendations turn out to be utterly worthlessand of all commercial pattern-recognition systems, that's among those with the largest pools of data to draw on.

Lest we forget: "simple" is hard. In fact, Kindberg and Fox remind us that "[s]ome problems routinely put forward [in ubicomp] are actually AI-hard"that is, as challenging as the creation of an artificial human-level intelligence. The example they offerwhether a technical system can accurately determine whether a meeting is in session in a given conference room, based on the available indicatorscould be supplemented with many another. Knowing when a loved one's feelings have been hurt, when a baby is hungry, when confrontation may prove a better strategy than conciliation: These are things that we know in an instant, but that not even the most sensitive pattern-detection engine can determine with any consistency at all.

So there's a certain hubris in daring to intervene, clumsily, in situations that already work reasonably well, and still more in labeling that intervention "smart." If we want to consistently and reliably build ubiquitous systems that do share something of the nature of our finest tools, that do support the finest that is in us, we really will need some help.



Everyware. The dawning age of ubiquitous computing
Everyware: The Dawning Age of Ubiquitous Computing
ISBN: 0321384016
EAN: 2147483647
Year: 2004
Pages: 124

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