Browsing the previous content of Vodafone’s receiver, I ran across this old article by Adam Greenfield about persona that struck me as relevant for current discussions about the role of persona/use cases in design (in the context of video game design).

The main point of the article is that use cases, designed to capture the important aspects of various users’ interaction with an innovation are often “cooked and artificial with no realistic appreciation of people’s complex desires and contexts. This is often true and spectacular. if you ever participated in a discussion of personas, you’ve certainly noticed how sterile and utilitarian use case are described.

Some excerpts I found relevant:

“When considering the social practices around any new technology, the uses foreseen by designers, manufacturers and retailers - and, inevitably, featured in the advertising and marketing campaigns around these technologies - are so much less interesting than what people actually wind up doing with them. (…) I call the gaps between the assumptions and the reality “fault lines”: places where emergent patterns of use expose incorrect assumptions on the part of the designers, imperfect models of the target audience on the part of marketers, and social realities that might otherwise have remained latent.
(…)
there is good business sense in attending carefully to these fault lines, for along such lines is where the truly useful products and services wait to be born.
(…)
A basic problem with use cases, and the entire product development mindset in which they are embedded, is that they generally fail to anticipate the larger social context inside which all technology exists.
“

Why do I blog this? What is interesting here is that Adam is not suggesting to scenarios and use cases but simply to make them more realistic and human. Very often, the use case are so neutral and instrumental that they fail to capture the complexity of people’s ambivalent needs and desires. And of course, design needs to take this into account so that the innovation “become part of the everyday pattern of use for the majority of users”.

It would be relevant to understand why the situation if often like this, why use cases are sometimes futile and utilitarian, why people avoid to consider weird situations like the one described by Adam: “in the US, Cingular Wireless offers a service called “Escape-a-Date,” which provides its subscribers an emergency exit from bad dates“. Is it because it’s politically incorrect or worse is this because of wrong assumptions about what uses could be?

The problem with tools such as personas and use cases is less about the process itself, and rather about the type of behavior promoted (or forgotten) in them. Also read what Steve Portigal wrote about personas and how they patronize users.

Recently working on a project about gestural interfaces and the user experience of the Nintendo Wii, I had my share of discussions about sampling in user experience research and the role of exceptions. Quantitative researchers often drawn nice curves with cute statistical distributions with “means” and quantiles. The type of things I’ve done in my PhD research, measuring X and Z (satisfaction to a certain project, number of messages typed on a phone, number of time someone pressed a certain button, etc.). In the end, you get this sort of graph represented below with anonymized dots which eventually represents how normal humans did certain things.

In general, quant research (the sort I’ve done in the past yes) compares different “conditions”: you have two sorts of interfaces, each group of users test one of the interface and you compare the number of time a certain group did certain things on the interface they had. Say, the number of time they pressed on the button called “OK”. Applying different statistical techniques (like variance analysis is the distribution is normal in the statistical sense, checking variances and if you’re in trouble then you always employ “non-parametric tests”). This is robust no kidding, I don’t criticize that kind of method. However, what I am wondering about is when this sort of methodology is solely applied to design research.

And it leads me to the discussion I had the other day with a colleague about the importance of exceptions, dots which are not close to the means, the weird outliers, peeps who do not fall in the distribution like that weird circle on the upper right-hand corner on the boxplot below:

Depending on your mood, the research methodology and your colleagues’ attitude, there is a wide spectrum of reaction ranging from “WTF, that person screwing my distribution?” to “OK this is an extreme user, he/she is special, let’s have a look more closely”. And then, of course, because you’re a smarty pant and you ALSO have qualitative data you see what the person SAID or DID (or whatever other types of data sources you have). Then the real thing starts: who are the extreme users? how extreme are they? what makes them extreme? are there other data source which attest that they are “exceptions”. And obviously this leads you to the question the norm (the mean).

To some extent, that’s the story of why I slowly moved from quant research to a mix of descriptive quantitative and qualitative research in user experience projects. I started getting interested in the role of exceptions, especially with regards to their importance in design. Why exceptions are important in design? Perhaps because they might show peculiar behavior and routine which can announce futures norms or trends (and then inspire new products, features and services) but also to show that the notion of a “normal user” or “mean user” is difficult to grasp as diversity exist and is important. Surely a very relevant near future laboratory spin.

An interesting example of an extreme user was this deaf guy I saw the other day at the train station, walking and gesticulating in front of his video cell-phone. If you map the use of video-communication on cell-phone you get a very low usage of the feature in general but that guy would be an exception.

“Technological Landscapes” by Richard Rogers is an essay about “relevant past futures”, i.e the “past roads not taken”, in which he invites us to re-read the history of technological culture “to inform the selection of the technological landscapes of our day”:

“Historical comparison with imagery of previous technological landscapes fires the imagination. It is also the stuff of argument and defence for an idea or a project
(…)
The rationale to looking closely into the early history of current dominant systems relates (…) to challenging the commonplace idea that the marketplace sorts out the ‘best’ technology and that the consumer and society are the beneficiaries. (…) the ‘alternatives paths’ or ‘roads not taken’ historians examine the effects on society (and increasingly the environment) of having lost a potentially viable system - technology opportunity cost.

After mentioning some examples such as FM radio, Rogers goes on with:

“When new and ‘better’ technological systems are trumpeted, it is worth recalling these and other specific examples of lost battles, from the level of abstractions of craft versus mass production down to that of keyboard layout. In confronting better technologies of the future, the question always remains ‘better for whom’?“

And then some more elaborate thoughts about how past futures are used or can be relevant:

“The Nineties [case for space exploration] also shows us how earlier models (relevant pasts) are employed as ‘guides’ to make current futuristic cases more compelling. To make a case for a futuristic technological project, the promoter often must finds ‘usable pasts’ or indeed ‘usable past futures’.
(…)
We learn the past futures for at least two reason. They aid us in thinking through the ideals, principles and social relations which have been and could be reflected in and designed into our technologies, bringing within our grasp the ability to ‘imagine alternative technological designs’ and act accordingly. Secondly, comparison is the stuff of case building. Drawing the right parallel (or spotting the spurious analogy) is one step in proposing or opposing particular cases to be made for new technology and new forms of decision-making on technology.“

Why do I blog this? collecting material for a project about technological failures. I am interested in the role of failures in foresight and design. Rogers describes some pertinent ideas about how failed futures can frame design, and the intrinsically political imaginary realm of this practice.

(via) In The Disruptive Potential of Game Technologies: Lessons Learned from its Impact on the Military Simulation Industry, Roger Smith discusses how computer games have a disruptive impact on military industry and suggest that these will disrupt other industries in the future.

It basically tells the history of military simulations and how video-games’ relationship to them, showing how game technologies rapidly moved into the industry from which they were originally created (military simulation). What happened is that new types of defense simulation companies “have emerged and do not attempt to re-create products from scratch, but instead seek out customers who require modifications to commercial tools with which they are proficient“.

Why do I blog blog this? Personally, I am less interested in the “serious game” aspect of this (plus I don’t like that term), but instead, by the conclusive sidebar of the paper, which is about how we can draw lessons for other industries. Some excerpts:

“Specific lessons that have been learned in the military simulation industry are:

1. Not Good Enough. The game technologies often do not appear to be good enough for the core customer base of the industry. However, (…) game technologies have the power of Silicon Valley behind them and the potential to become more than good enough for core customers.
2. Raising the Standard. The visual appeal and human usability of games is far beyond that of most industrial software applications. These features are very attractive to customers and enable vendors to sway customers to their products much more easily than is possible with the traditional software tools.
3. Customer Pull. As customers become aware of game-based tools in their industry they pull on their current suppliers to offer similar products. If established companies ignore these requests it creates a disruptive opportunity for an upstart company that will satisfy these needs.
4. Explore Applicability. Established players in other industries should explore the potential improvements that game technology offers for their customers.
5. Build Capabilities. If game technologies are entering an industry, leaders must determine whether to create their own in-house expertise or develop relationships with smaller game technology studios. There are a number of game studios that have been only marginally successful in selling games for entertainment, but who possess the skills necessary to apply these technologies to a new industry.”

Some more general lessons about innovation and how people from the military industry sees the video-game business.

Last week, the NYT had an intriguing story about pinball machines, or - more specifically - the survivor of the pinball industry. Some excerpts I found interesting below:

About how it went downhill (”a painful fading”) that may be “turned around”:

““There are a lot of things I look at and scratch my head,” said Tim Arnold, who ran an arcade during a heyday of pinball in the 1970s and recently opened The Pinball Hall of Fame, a nonprofit museum in a Las Vegas strip mall. “Why are people playing games on their cellphones while they write e-mail? I don’t get it.”

“The thing that’s killing pinball,” Mr. Arnold added, “is not that people don’t like it. It’s that there’s nowhere to play it.”
(…)
Corner shops, pubs, arcades and bowling alleys stopped stocking pinball machines. A younger audience turned to video games. Men of a certain age, said Mr. Arnold, who is 52, became the reliable audience.
(…)
the pinball buyer is shifting. In the United States, Mr. Stern said, half of his new machines, which cost about $5,000 and are bought through distributors, now go directly into people’s homes and not a corner arcade “

About the design process per se:

“Some workers are required to spend 15 minutes a day in the “game room” playing the latest models or risk the wrath of Mr. Stern. “You work at a pinball company,” he explained, grumpily, “you’re going to play a lot of pinball.” (On a clipboard here, the professionals must jot their critiques, which, on a recent day, included “flipper feels soft” and “stupid display.”)

And in a testing laboratory devoted to the physics of all of this, silver balls bounce around alone in cases for hours to record how well certain kickers and flippers and bumpers hold up.“

Why do I blog this? cultural interest in how certain things work and then fade away for diverse reasons that are interesting to observe. Some lessons can be drawn here about innovation, especially about the role of contexts (or the absence of context of play).

The twelfth episode of The Simpsons’ fourth season, called Marge vs. the Monorail is maybe one of my favorite episode and is definitely a great lesson in design. And this, not only in the conception of public transport, but also in terms of innovation as a whole.

This episode focuses around the town of Springfield buying a monorail from a Lyle Lanley after earning lot of money, and instead of fixing more urgent problems like cracks on the streets. Only Marge seems to dislike the purchase but everyone in town seems to succumb to the glossy value of the Monorail. After a quick training, Homer happens to be the monorail driver. At first things run okay, but then some malfunction occur and the monorail accelerates dangerously. It’s eventually stopped by Homer who launched an anchor on a big donut.

What does that say about design/innovation?

First, it’s an interesting example of how a group of people puts lots of money in some sort of crazy things utterly cool that is not the most necessarily need of a community. When Marge tells Bart “Main Street’s still all cracked and broken“, he replies with the wisdom of the crowd motto: “Sorry, mom, the mob has spoken… Monorail! Monorail! Monorail!“. As if the street, as a means of mobility, was boring, old-fashion and useless compared to the shiny representation of the future depicted by the monorail. What’s funny is that even Lisa is fooled by the salesman when she tells him that such a transportation system would be useless in a low-density town such as Springfield. The promise of the value of a futuristic device such as the monorail is almost unquestionable (ah… progress), based on the common sense of the group.

Second, and surely a corollary, it also shows (and criticizes) how social pressure is important in the diffusion and acceptability of an innovation. “Ah it’s not for you, it’s more of a shelbyville idea” or”I’ve sold monorails to Brockway, Ogdenville, and North Haverbrook, and by gum, it put them on the map!” says the salesman showing a map of the US with only these cities on the map. To some extent, it follows innovation researcher from the 19th century Gabriel Tarde’s laws of imitation: innovation are adopted faster when they have already been accepted elsewhere.

Why do I blog this? preparing material for a course, looking for interesting examples of failures. Reminds me of some innovations-who-became fads right? Of course every fad are not always comparable to the “springfield monorail” (scholars would say “isomorphic”) but there are some good points in that episode.

People interested in the diffusion of innovation can find perfect exemplifications here:

• The monorail as the invention
• Springfield’s inhabitants as the social structure. As usual when they have to decide municipal decisions, they gather in the townhall, under the guidance of Joe Quimby (the mayor), showing a very swiss landsgemeinde way of making decisions. Innovation researchers who employ the term “authority-collective decision” to describe how this choice to buy and build a monorail is made.
• Lyle Lanley, the salesman, as the change agent external to the system
• Lisa and then Marge as people who are part of the social system but who have doubts.
• The monorail value proposition is the one of an innovation: faster than other means of transport, more sexy, complex and launched with the help of a VIP: Leonard Nemoy from Star Trek.

Of course, it does not depict the whole innovation diffusion, only the recurring failure of the monorail (based on different iterations) and how the salesmen made money out of it.

The inevitable aging and depletion of components of a design object is an often overlooked topic that is addressed in this IEEE Spectrum article. Some excerpts I found relevant:

“ At the very least, the quest for an obsolete part can escalate into an unexpected, budget-busting expense. Electronics obsolescence—also known as DMSMS, for diminishing manufacturing sources and material shortages—is a huge problem for designers who build systems that must last longer than the next cycle of technology.
(…)
The crux is that semiconductor manufacturers mainly answer the needs of the consumer electronics industry, whose products are rarely supported for more than four years. Dell lists notebook computer models in its catalog for about 18 months. This dynamic hurts designers with long lead times on products with even longer field lives, introducing materials, components, and processes that are incompatible with older ones.
(…)
The systems hit hardest by obsolescence are the ones that must perform nearly flawlessly. Technologies for mass transit, medicine, the military, air-traffic control, and power-grid management, to name a few, require long design and testing cycles, so they cannot go into operation soon after they are conceived.“

Hence the existence of “company that provides obsolescence-related resources” such as Qinetiq Technology Extension Corp and the need to develop “tools to forecast and resolve obsolescence problems”:

“To deal with that growing pile of unavailable supplies, engineers in charge of long-lasting systems must basically predict the future—they must learn to plan well in advance, and more carefully than ever before, for the day their equipment will start to fail.
(…)
Such companies as i2 Technologies, Qinetiq, Total Parts Plus, and PartMiner have produced commercial tools that forecast obsolescence by modeling a part’s life cycle. To derive a forecast, the services weigh a product’s technical attributes—for example, minimum feature size, logic family, number of gates, type of substrate, and type of process—to rank parts by their stages of maturity, from introduction through growth, maturity, decline, phase out, and obsolescence. (…) However, predicting when parts will become unavailable is still not enough information on which to build a business plan. “

Why do I blog this? curiosity towards this intriguing and overlooked problem.

11 innovation lessons from creators of World of Warcraft by Colin Stewart is a very interesting discussion. I don’t agree with all of them but some are important.

That one struck me as relevant:

“6. THE IMPORTANCE OF FREQUENT FAILURES
“One of the mantras that a large software development company uses is ‘Fail Often, Fail Fast,’ ” Wartenberg said.
“As Alan Mullaly said when he led Boeing Commercial Aircraft, ‘We celebrate mistakes; bring them into the open, because we can’t help fix what we don’t know about.’ ”
To show Blizzard’s devotion to this principle, CEO Morhaime and other executives listed the titles of canceled games Blizzard had worked on: Nomad, Raiko, Warcraft Adventures, Games People Play, Crixa, Shattered Nations, Pax Imperia, and Denizen.
“We don’t have a 100 percent hit rate. We just cancel all the ones that aren’t going well,” Morhaime said.
“Failure begets success,” intellectual property attorney St. George said. “Many successful companies and CEOs have noted that their best successes have come from failures. The lessons learned from failures will provide the stepping stones for the next innovation.”“

Why do I blog this? gathering notes about failures for a personal project. It’s also interesting to see that game companies are only reaching the stage where they figure out the lessons described in that paper (”GO BACK TO THE DRAWING BOARD“, “MAKE CONTINUAL IMPROVEMENTS“).

Glenn Derene in Popular Mechanics address the reasons why it took so long for Microsoft Surface to be “finally here”:

“Microsoft’s initial plan was to put a very limited number of Surface machines in stores and hotels with demonstration software just to show what the thing could do. But now AT&T has come along and leapfrogged over that demo mode to Surface on a larger scale—and in a much more useful way.
(…)
What struck me at the time was that the hardest part of the project seemed to be complete (…) All that was really left was for partners to design software customizing the Surface platform to their businesses. But that part of the equation seems to have taken forever.
(…)
What’s ironic is that Microsoft has traditionally been a software company (Surface is one of the few pieces of hardware it actually makes), and it has all the necessary programming talent to build generic templates for Surface
(…)
it seems that Microsoft is more interested in launching what could be a breakthrough product solely with image-conscious partners who want to use the Surface as an attention-grabbing, brand-building device
(…)
this particular delay was probably more a result of the bureaucracy of complex business partnerships than of any defects in the design and engineering of Surface itself. But the end result is the same: Those of us who get excited about new technologies feel disappointed, and maybe even a bit embarrassed, for our own initial enthusiasm.“

Why do I blog this? The article interestingly illustrated the gap between the glamorous projected at first by a technological innovation such as Microsoft Surface and where we stand one year after (” a classic example of how a lot of hoopla followed by a long delay can drain much of the excitement out of a technological innovation“). Especially when examined in the context of other interactive surface projects (also mentioned in the PM article). That’s of course a common situation in the tech industry.

It’s often when reading obscure and never translated european writers that I find the most intriguing ideas, especially when it comes to foresight and innovation. The book “Les sens de la Technique” by Victor Scardigli is no exception to this; the title is a sort of pun since “sens” in french means both “meaning” and “direction”. Thus you can read the title as “The Meaning of Technique” or “Where Technique is heading”, which reveals the ambivalence of technical innovation. What’s intriguing here is that the author, for once, do not distinguish “techniques” and “technologies”, rather taking techniques as a whole that encompass vaccines or ICTs.

Above all, the book is above the gap between the expectations our societies put into innovation AND the weak consequences of the first change we can notice. After inventions and R&D processes, innovation is expected by some (especially the inventors) to diffuse in society and “impact it” (for best or for worse). Different rationales are at stake here since engineers or biologists expect Sciences to serve Progress, the reciprocal adaption of human beings and techniques and hence measure the “social impact” of their invention. On the other hands, social scientists often more convinced by the prominence of human causalities are more skeptical and think that new techniques are only tools to modify the course of time based on their own objectives.

The author then addresses how techniques and their usage evolve over time, for which he describes 3 phases in his “diffusion model” using a raft of interesting examples that I won’t describe here:

1. Phase 1: The “time of prophecy and fantasy” (enthusiastic or terrifying) where revolutions are predicted and technique is “inserted socially” (right after invention and R&D). It’s mostly the time of positivists and the moment where imaginary symbols are constituted. The less objective fact you have, the more imaginary you get, so irrational thoughts are important here. Prophecies (or social actors who promote them) attempt to create a connection between 3 elements: the new technical object, human desire and expectations/fear of the time being. This leads to imaginary representations that you can find in the discourse of companies promoting the innovation, surveys or advertising/media messages. For Scardigli, there are of course constant imaginary issues: power on constraints (liberty of slavery), knowledge, fear of death, social justice, social bounds, economical wealth and global solidarity. There is therefore a discourse around the hopes and fears linked to these issues which are recurring in history. What happen is that fantasy, scientific knowledge and actions are intertwined and even the weakest signal is turned into an excessive hope or fear. Prophecies become necessities and then self-justificated.
2. Phase 2: The “delusion phase” that suggest how the expected technological revolution does not lead to a social revolution. Positivists’ prominence is obscured by skeptical voices who raise the gap between forecasts and realizations/effects. They also reveal how “techniques” themselves are not sufficient to change “society”. To some extent, observers realize that science only make progress… in science. It’s of course the time where “users/people” enter the scene and begin employing the technique. These small actors transform, invent new uses, hack or tweak the innovation. This appropriation and reinvention of daily life leads to a third phase.
3. Phase 3: “the side-effect phase”: 30 or 40 years after, the real diffusion of the technique is effective and some social and more long term consequences appear but often different from the one expected at first (new social form, new forms of cultures or human activities). He cites an example of a sort of bulletin-board system in the 80s in French that was expected to revive surburbian communities. What happened is that technology vanished (the state program was stopped) but it allowed people to gather, meet and create “mediating” organizations that survived. In the end, the collective imaginary of progress from the 1st phase is articulated with the strategy of actors who promote the innovation. Social change appear as a side-effect of the technical innovation, not because of it. The introduction of the innovation acts as a “analyser” revealing problems, social dynamic, aspirations, needs and above all as an alibi for new forms of sociality. And at the end of the road, it’s end-users themselves who give sense to techniques by integrating to their daily life/culture.

Also Scardigli raises the importance of the socio-cultural context of innovation, who often fail without it. He exemplify this with a description of “mediating” persons who are social actors who can promote technologies and make people understand how it will be of interest for their purposes/life. In addition, there is of course a compromise between the Ideal of the project and the economic/user realism. If what happen in the 3rd phase is different than what was expected in the first one, it’s because big actors (States, companies) are struggling with each others with different visions BUT also because small actors (users!) modify, change, tweak or slow down the unfolding of these innovation.

Finally, in his conclusion, he discusses some lessons about progress and innovation:

• Human beings build their own history, sometimes by designing new techniques but often with other means (e.g. organizational). And it’s not these techniques that will change or social and daily life.
• These innovation effort are always carried out over and over, as a sort of Sisyphean curse because new techniques have to articulate both Science (who likes to “discover”) and social demand for a better world. Unfortunately, harmonious encounters between both is very rare and needs and innovation are scarcely matching. Technical inventions are always the fruit of a culture and inventors, engineers or users all share the will to have a better world so they try, like Sisyphe.
• Social appropriation is always slower than technical innovation. 5-10 years are needed to go from the fantasy phase to find a niche of users. 10 or 20 years are then needed so that the innovation is entirely appropriated in daily life.

Reading this piece on ZDnet that I flagged few months ago, I stumbled across interesting figures:

• In 2007, Minitel traffic and services generated 100 Millions Euros (shared between the french provider France Telecom and third parties) through to 4000 “services” (sort of the equivalent of websites). In 1996, there were 25 000 services that generated 1 billion euros of revenues.
• 220 millions of connections in 2007, approximately 20 millions per months.
• Traffic dropped by 90% between 1996 and 2006 and by 35% between 2006 and 2007.
• There are still 1 million Minitel terminals that are active but people still access Minitel services through their PCs (2 millions do, through emulators). In 1996, there were 6.5 millions.
• Minitel terminals are still sold and - even better - manufactured by recycling old ones.
• Most of the usage are: looking up addresses/phone numbers by the mythic “3611″, reverse phone directory, astrology and bets. But “minitel rose” (sex chats) have vanished.
• Professional services are very important mostly for logistics marketplace.
• 25% of the revenues comes from financial services (following stock exchanges, investments etc.)

Why do I blog this? intrigued by an object of the past that still have offer some resistance to progress. The fact that people still use minitel services through the Web is very interesting: the thing work, people have their habits and keep using the media they used for a long time.

Also it’s important to note that if things/invention are slow to take off, they are also slow to die!. If there’s an S-curve till a mature market for any invention, the curve is reversed the other way as well. The following paper in the NYT times the other day address this issue concerning mainframe computer which were expected to disappear ten years ago:

“What are the common traits of survivor technologies? First, it seems, there is a core technology requirement: there must be some enduring advantage in the old technology that is not entirely supplanted by the new. But beyond that, it is the business decisions that matter most: investing to retool the traditional technology, adopting a new business model and nurturing a support network of loyal customers, industry partners and skilled workers. The unfulfilled predictions of demise, experts say, tend to overestimate the importance of pure technical innovation and underestimate the role of business judgment.“

Not really a pattern, but I ran across two articles about design process this morning. The first one (found here) is about the design of a new ride (Toy Story Mania) at Disney theme parks:

“BUILDING elaborate models is among the first formal steps in creating a Disney attraction. Engineers, paying attention to scale and sight lines, want to find out how a planned addition would affect the existing park. Models are built on large tables equipped with wheels. The company keeps room-size models of entire parks, and engineers will eventually wheel the new model into that area to see how it looks.
(…)
To give birth to Toy Story Mania, Mr. Rafferty and Mr. Coltrin went to work turning drawings of the ride into foam models, toiling in the same 1950s-era building in suburban Los Angeles where Walt Disney himself once tinkered. Tweaks started to happen. The team added turrets to the top of the ride for a more dramatic flair. (…) Upstairs, designers entered blueprints for the ride into a computer program. This would allow them to start building and refining the entire project
(…)
“It is much easier and less expensive to do this before the concrete has been poured,” he added. “As rides become more complicated, your ability to tweak in the field gets harder and much more expensive.”

Across the street, in a cold, unmarked garage, Ms. Allen helped to conduct “play tests” on rudimentary versions of the ride. More than 400 people of all ages — all had signed strict nondisclosure agreements — sat on a plywood vehicle set up in front of a projection screen and played various versions of the games. Disney workers studied their reactions and interviewed them afterward.

And this interview of Bjarne P. Tveskov, the classic LEGO Space Designer addresses interesting topics related to design:

“BBG: Where did the ideas for the models come from? Did someone from LEGO say “Bjarne, we need a big space ship for the Blacktron line” or did you come up with the ship so they decided to produce it?

Bjarne: Well, normally there was a brief to create a new space ship or vehicle or base at a specific price point. Maybe the model were to replace an existing set or maybe there would be some other requirements. But there would always be a fixed “brick-budget” one had to stay within. That was often the hardest part; If the model was over budget, one had to simplify and sometimes strip all the little cool extras of the models. Each brick has an internal price, and there was a whole department that did nothing but calculate the prices of all the prototype models we designed. Often 20-30 different models would be built, and only one would be selected for production. Then the models went through a committee of super-experienced model-designers to make sure stability and buildability was optimal.

I remember that one of the toughest ones to slim down to the right price was the Blacktron Alienator (6876). It had to be rebuilt and re- calculated several times before the brick-count was low enough. But it’s still also one my favorite sets out of the 20+ LEGO Space models I designed back in the day from 1986 to 1990.“

Why do I blog this? two interesting accounts of design process in less known fields, some curious elements to be thought of. For example, the description of the test approach in the theme park scenario would be a curious topic to discuss with urban planners. Are there some transferable approaches? Would a public transport company benefit from this?

There is a great interview of Steve Portigal in influx. Some excerpts I found relevant:

“A great design strategist (…) someone who has had a few different professional identities and gets excited by the spaces where disciplines, schools of thought, and methods overlap. They are curious and easily intrigued: they like to observe what’s going on around them and they’re good at listening to people. And they know how to use all this data to synthesize new patterns and communicate them clearly to a range of audiences. Charlie Stross, in the sci-fi book “Accelerando”, describes the profession of a “meme broker” and the intense amount of content they have to assimilate every day in order to do this. Bruce Sterling calls this activity “scanning“ looking at all the sources one can and constantly asking what does this mean for my clients. Being able to work through all those data sources and pull out the implications is crucial for design strategy.
(…)
The best research brings to life the imperfect and messy stories of real people and presents generative frameworks that lead the way forward for new designs, products, services, features, communications, or whatever is needed.“

Why do I blog this? some good insights here that rings a bell with personal thoughts, especially concerning the messiness of reality and the need to uncover quirks, peculiars situations, extreme users as well as exceptions.

Fabien dug out an interesting paper by Bruno Latour about the implications of digital traces entitled “Beware your imagination leaves digital traces. The article, published in Times Higher Literary Supplement (6th April 2007) addresses the increasing traceability and how it will open up new inquiries by social sciences

“It is as if the inner workings of private worlds have been pried open because their inputs and outputs have become thoroughly traceable. (…) Before digitalisation, social psychologists used very vague words such as “rumours”, “influences”, “fads”, “fashions” or even “contexts” to describe the complex ecology of our minds. But today it just happens that a character from a game can be followed through the IP numbers of the computers from which they are clicked or from the stream of news in which they are commented upon, all the way from the designers who draw them to the blogs where their adventures are exchanged.
(…)
The ancient divide between the social on the one hand and the psychological on the other was largely an artefact of an asymmetry between the traceability of various types of carriers (…) today the data bank of Amazon.com has simultaneous access to my most subtle preferences as well as to my Visa card. As soon as I purchase on the web, I erase the difference between the social, the economic and the psychological, just because of the range of traces I leave behind.
(…)
The consequences for the social sciences will be enormous: they can finally have access to masses of data that are of the same order of magnitude as that of their older sisters, the natural sciences. But my view is that “social” has probably become as obsolete as “natural”: what is common to both is a sort of new epidemiology that was anticipated, a century ago, by the sociologist Gabriel Tarde and that has now, at last, the empirical means of its scientific ambition.“

Why do I blog this? I quite like the holistic perspective Latour describes here and how tools lead to a situation in which researchers need to go beyond reductionism. And pointing out Tarde is also relevant.

Been reading this paper from Paul Dourish tonight in the train: “Seeing Like an Interface” (a paper he presented at OzCHI 2007). The author concluded about “the burgeoning interest in a reflective approach to HCI” that would be concerned by the “critical dimensions of design”. He basically describes technologies such as computers as “an effective site” at which to engage in critical engagements about the cultural values and assumptions. What does that mean for the everyday researcher/practitioner? Here are some hints described in the paper:

“Reflective HCI suggests an approach to interaction design in which cultural assumptions and values play as important a role as traditional usability metrics both as measures of success and as elements of the design process.
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The discipline of HCI has evolved considerably over several decades, but so too have computer systems themselves. What I want to draw attention to here is not simply the fact that computers have become faster, smaller, and more powerful as technological artifacts, but that they have emerged as cultural objects in a radically different way than they did before. They are elements of the landscape of daily life in many different forms. Digital devices are embedded in our cultural and social imagination in very different ways than they were when HCI was emerging. To the extent that our discipline thinks not simply about user interface design but about interactions between humans and computers, these transformations suggest that we need to look more broadly for theoretical perspectives that help us understand how computation manifests itself as a cultural object“

Why do I blog this? surely some elements to be connected with what Anthony Dunne described in Hertzian tales about “critical design” (although the two visions are not the same). On a more general level, I find interesting to see when different disciplines (such as human-computer interaction or design) come-up with close concepts.

What is then interesting for the layman (for example when I am working with game designers on gestural interfaces usage for the Nintendo Wii) is to see how these ideas can be turned into (pragmatic) actions. In other words, what would “reflective HCI” brings to the table when I am surrounded by level designers, scenario planners, the production manager and the lead coder? Well, it’s certainly different from showing graphics about usability issues (that bloody tester missed the door 14 times on that level!) but it does bring questions, insights, discussions that sometimes allow to reconsider problems and results from tests/observations/ethnographic accounts of playtests.