“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.

Last thursday/friday, I was in Brittany for an seminar called “Imagine 2015″, the annual gathering of companies from the Media and Network companies from there (France Telecom/Orange, Alcatel-Lucent, Thomson, Philips, etc.). The point of such event is to discuss the future of networks and what it means for these organizations in terms of foresight, change and (of course) possible new products/services. I was invited as an expert (a “witness” as they call it) to present various things related to my work (user experience research results, foresight issues that I find interesting and work practices related to the use of digital tools). Thanks for Jean-Noel and Christiane for the invitation.

Instead of giving a summary of the event, I am more interested here in the process and how people answers the questions we addressed. The starting points were (sort-of): “according to you what interesting thing will we see from now to 2015?” and since they are focused on networks: “what does network allow? what are the implications of networks?”

Given that I participate in other seminars in the same vein (some pretty focused on a clear goal, like Lyon 2013, some other more speculative such as Cinum), I always find relevant to observe what are the arguments employed by the experts (and the crowd) to answers foresight questions (”what do you think will happen from now to 20XX?”). I’ve tried to make a raw-and-not-exhaustive list here of what I observe as being used:

1. personal experience (expert) and of course naive personal experience (when people are not expert but rely on something they’ve lived)
2. statistics about people, environmental issues.
3. use of the long term/now perspective because as Paul Saffo points out in his Long Now talk, “We tend to over-estimate the speed of short-term adoption and under-estimate the diffusion of the technology”
4. bring history to the table: especially the greeks, the egyptian and the roman
5. the use of abstract metaphor coming from fields such as thermodynamics (entropy employed as a metaphor for chaos, disorder or dissipation of energy) or biology (the other day Thierry Gaudin talked about apoptotis: form of programmed cell death caused by a lack of information transfer).
6. the use of sociological or psychological models, concepts and sometimes controversial universals.
7. imagination, be it about novels from the past or sci-fi
8. to be continued

Why do I blog this? preparing a course about foresight and innovation, I am listing the “sources” for foresight analysis. The notion of data to draw scenarios for the future is something I am always been intrigued about. Feel free to add things to the list, which is definitely not exhaustive.

What I find interesting is to confront the types of arguments described in the literature and those employed in seminar/conferences, not really to evaluate which are more powerful to persuade others, rather to understand which emerge spontaneously.

Still gathering stuff about “failed futures” for a project, I ran across this interview of Matt Jones by Adaptive Path peeps that is very insightful. Some excerpts I found relevant for my project:

“RF: You’ve mentioned the danger of “lost futures,” based on the success of a given device. One model becomes wildly popular, and other, more interesting ways of looking at the problem get cast aside… or at least ignored when they could be doing the most good.

MJ: Exactly - the gravity well of the iPhone is going to be hard for anyone developing innovative UIs to escape for the next few years. In hardware, you’re subject to the determinism of sourcing components.

RF: Our friends the cognitive anthropologists have warned us about the implications of subscribing to the wrong cognitive artifacts…

MJ: So everyone for the last 2/3 years has been offered the same touchscreen components more or less by a few suppliers. And we all (more or less) have similar dimensions we can work within in a touch UI.

RF: So thinking in hardware becomes even more constrained?

MJ: To an extent. UIs will not be so diverse in the next few years… inside a BigDeviceCo you’re going to find it hard to justify the investment in the out-there stuff (as always). But there’s still innovation a plenty to come, its just that for the next few years it’ll be all 16:9 touchscreens, I guess. And then… hopefully someone will Wii on their parade and breakthrough with something as different as the iPhone was to the existing crop of smartphones. That’s my hope anyway. And I think it might be in the area of physical/gestural interfaces, matched with ambient/visualisation tech to give us more natural ‘Everyware‘.“

Why do I blog this? I am trying to collect material about what Jones calls “lost future” (in design+foresight), I quite like his stance here, not only about the example discussed (that 16:9 touchscreen device coming from Cupertino) but, rather, its possible consequence: how it eclipses other innovation. There are different consequences of failed futures, some are about traps like in this examples; others are about perpetuation of wrong ideas.

Paul Saffo’s talk at the Long Now Foundation (MP3 here) is a very good overview of foresight research heuristics/rules of thumbs/methods. Some notes:

• “Hunt of Bin Laden, experts agree, Al Qaeda leader is dead or alive” is a great forecast because it accurately captures the uncertainty of the moment. The biggest mistake is to be more certain than what the fact suggest, especially today, at this very uncertain moment in time (where indicators are going in different directions). As Peter Schwarz says: “The difference between a good forecast and reality is…a good forecast has to be believable and internally consistent”
• The job is not about predicting but rather mapping the “cone of uncertainty” on a subject. And, uncertainty means opportunity. It’s a cone shape for commonsensical reasons and because uncertainty expands as you project further into the future. The important thing is to find edges: Where might they happen? There you should look for wild-cards to define the boundaries and science-fiction can be a good candidate for that matter (as well as bad press about the future).
• Change is not linear and very slow and most big technological changes take 20 years to develop (”new technologies take 20 years to have an overnight success”). This means that you need good backsight, BUT because evolution is slow, you still have time even if you miss an early indicator.
• Look then for early indicators (”prodromes” or “prodroma”: an early symptom or leading indicator) as claimed by William Gibson’s observation that the “future is already here, it’s just not unevenly distributed”. Look for indicators and things that don’t fit.
• We tend to over-estimate the speed of short-term adoption and under-estimate the diffusion of the technology (”Never mistake a clear view for a short distance”). In addition, things aren’t accelerating and every society has always complained that things were getting faster, even in the 16th century (”every generation thinks things are accelerating”).
• Look at failures and cherish them (Preferably other people’s). Silicon Valley has been built on the ashes of failure. Look also for people who failed in a company and went starting their own.
• Prove yourself wrong: look for indicators that proves what you say BUT also weak signals that prove it wrong
• “Be indifferent. Don’t confuse the desired with the likely”
• Know when not to make a forecast
• The problem for forecasters is not of being wrong, it about persuading people to act on forecasts.

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.

Still a struggle to find time to blog my notes from the LIFT08 conference. Here are some notes from the session about foresight.

Scott Smith
As defined by his complany tagline, Scott talked about “seeing change differently” or how to help people to see change more clearly. He defined foresight as “keeping your mind and your eyes aware of the periphery as well as what is in the immediately linear future, as there is always something that could disrupt your path“. Following William Gibons’s quote that the “future is already here but it’s not evenly distributed”, Scott then described how the future is hidden in little places or pockets we are not always aware of and insisted on the important of qualitative data (over quantitative extrapolations). Hence the importance of ethnographical approaches. He insisted on a set of tips to adopt a qualitative foresight approach: (1) be aware of what’s going on around you, (2) scan, collect, organize, (3) look for patterns and deep currents, (4), understand the role of values, (5) have a view, but not an ideology (and be ready to step outside your boundaries), (6), stay grounded, (7), be prepared to leave behind the artifacts of your experience.

Francesco Cara
Francesco works at Nokia, he’s design strategist and basically described the sort of approach to innovation he favors. He started by insisting on the notion of ecosystem and complex systems drawn from Piaget that shaped his vision hereafter. Looking at the evolution of mobile communication, he showed how the ecosystem got more complex over time: from GSM phone units (closed by regulators, carriers, manufacturers) to WAP-based phone with more capabilities to exchange “with the outside” and finally a third stage with new services that tap into the Internet (maps, email…) and new entrants (Google, Apple).
To do so, he actually used visualization from a project conducted at our EPFL lab called “Mapping the Digital World, Visualizing the fundamental structure of the digital world in mobile devices . This last stage forms a sort of “cloud” of services that is so complex that our way to interact with it are totally different. But the problem is the one of the interface: how to interact with this complex ecosystem?

(Picture taken by Bruno Giussani)

Francesco showed the different approaches adopted by companies such as Blacberry (specialized: email), chaotic interface with various ways to use services (Sony Ericcson), desktop-based (Apple iPhone) or portal-based (Windows). He then advocated for “fresh” innovation. And why is this in a foresight session? Francesco’s point is that sometimes innovation does not lie in observing the past or looking for weak signals but rather to develop brand new approach and create new metaphor (that can of course be based on analogical reasoning, taken from other domains). His claim was not that the stuff presented by Scott is wrong but rather that innovation if a combination of both and it all boils down to the level of granularity in the data you need to inform design.

Bill Cockayne
Bill started off by making a strong point that what he talks about is not “futurism” but “foresight” and the role it plays in the innovation process. What he means is rather how to inform the building of something that is 1-2 product life cycle away. Depending on the products (car: 10 years+, nokia: closer), what happen is generally 1st product cycle (made now), 2nd product cycles (strategized now) and what happen for the 3rd product cycles?

Bill focuses on where you kind of start the whole process. He explained how the ideas he presents has been developed as Stanford. For instant, they adopted the ambiguity curve as a way to decribe the process. It’s used by Prof. Leifer at Stanford and it’s inspired by work from MIT+Buckminster Fuller. The ambiguity curve is not explicitly referenced but it shows how the situation evolves. At the beginning, you have ideas (beginning of a problem) with a vast ambiguity (”but we have to live in it”). All the way to shipping a product you retain ambiguity but there are different stages:

The thing is that people are having a problem to figure out where to fit in this process, to be aware of one’s strength or how to maximize them. What is design, what is foresight? How to connect d+f? The problem between r+d= people from research why what they give to developers is shipped and people from development never visit the researcher’s office because they have work to do today. And there are same issues with foresight and design. However, there are no breaks between r and f or between r and d, eventually you have to ship products! There are 3(+1) stages: (0), wallow (what Scott described: looking for the future, not ready to start the projects, be aware and intuitive, scan/look/analyze data), (1) foresight (prepare and sense), (2) research (form and analyze) and (3) design (integrate, develop)

What is important here is the notion of roles, which was developed afterwards. I strongly recommend here to have a look at at the impressive work done by Michele Perras, who recreated the images form Bill’s slides. For example the one that shows the different types of roles (see also Bill’s discussion of the role on her blog which nicely covers the topic in greater details):

(Re-created by Michele Perras)

Bill then described what roles can fit with what part of the process and along the ambiguity curve. He also presented what sort of process takes place: informal/formal/corporate.

His last advice was to know yourself, and what role you can play:
1) if you wanna be an expert, please remain an expert; stay at school kids, focusing on what you’re good at
2) t-person: learn another language, something complementary (take a design degree if you’re en business expert), vast need for this people
3) break your breadth, take a new expertise
4) come talk to people like scott, francesco, bill and read widely

Why is that important? why did he talk about roles and not tools to predict the future? Because change is constant, which means that new opportunities appear constantly and “we love opportunities because that’s where innovation comes from” and knowing where you excel at will help you to know who you are and make you more comfortable in the change environment and help you tell other people where you’re good at.

Some notes from Michele Bowman’s podcast entitled “The Role of Ethnofutures and Environmental Scanning”:

“2 things to keep in mind:
“Any truly useful idea about the futures should first seem to be ridiculous.”: The idea that airplanes would carry people, the fall of the berlin wall, paying bottled water

“not all change is created equal”: The general consensus in the business world is that change happens really, in fact this is not the case at all. There are all sorts of degress of change:
- environmental change, demographic change: takes decade to be felt
- evolutionary change: rising of women in the workforce… incremental… almost predictable timeframe
- faster furious change: the cost of sequencing the genetic alphabet that dropped

Environmental scanning is the understanding the dynamic of change, where and when, how fast? how slow? a collection, interpretation about trends and emerging issues And it needs to be external: “I don’t know who discovered water but it wasn’t a fish” because challenges will come form external environment

Roles of scanning
- as a decision-making capacity
- organizational learning, increasing the sensitivity to change“

Why do I blog this? curiosity towards different methods about foresight research, lots of resonance with the LIFT08 session about this theme.

Being an organizer of the LIFT conference is also tricky and often lead you to avoid attending the conferences. That said, I managed to watch Bruce Sterling’s introductory keynote.

Bruce addressed what was important in 2007 that may shape 2008. In a sense, looking out in the rear mirror to see the near future. Which led him to state “What’s the punchiest thing one can say about the past year? That’s the way it was, now get out!”. The first point of this keynote was that a big part of the good things that happen to us on this planet occur BECAUSE people make it out of bed in the morning (”The main reason people prosper if because they get out of bed, showing up is 90% of the job!”).

He then described how 2008 might be boring (”It’s a crap year!”) caused by economic downturn, global warming memes. And in the tech world, the situation looks even worse to him: what is exciting when Microsoft wants to eat Yahoo (”Is MS really about innovation when Bill Gates leaves MS to go cure malaria?”).

So what may shape 2008? Is it possible to produce focuses insights about it? To Bruce Sterling, a powerful driver can be something that came unexpected, out of nowhere and largely covered in the press. Before jumping into it, the gave a disclaimer “You will probably not like it but you’ll get why it’s important to other people”: Mrs Carla Sarkozy.

The first point he started with is to consider why talking about this in a tech conference like LIFT. To him, it’s because they met at a french tech summit about the current problems encountered by the music industry and P2P policies. So to some extent it’s an “internet policy romance” where Carla Sarkozy (the “Madame Du Barry of the Digital Renaissance”) can be considered as a black swan. If you’re not familiar with Nassim Nicholas Taleb’s work, a black swan is a “a large-impact, hard-to-predict, and rare event beyond the realm of normal expectations“, a ‘wild-card’ event that cannot be predicted with accuracy (in the foresight jargon). An history like this, as he said, “writes itself” and rules the world… showing that there are certain histories (”believe it or not”) who dominates.

Using this metaphor, he then presented the two driving forces related to this black swan: ambition (”carla is ambitious”) and publicity (”carla and nicolas are notorious, they can’t turn the press off, they feed the press”) with a matrix like this:

The next part of the talk was a depiction of what each square of this matrix would imply and are their what probabilities. The high ambition/high publicity square between the classic weirdest/useful scenario ( “Future tends to be weird, … but glamour has its use.”). The scenarios (and this topic) he presented may seem awkward BUT: what was interesting here was this sort of template/matrix to explore the future, a similar technique as the one we employed last year at the LIFT07 workshop about the city of the future. And of course, another black swan for the 21st century was definitely the Internet, as he pointed out.

The end of the talk were rather advices/behavior to adopt towards the future. For instance: “Let me tell you something you can take certainly in 2008, it’s to find the very character of our time. You can smell the future, you can embody it”, “you cannot predict the future but you can describe it” or take futurism as the goldilock hypothesis as the future is either “too hot, too cold, just right”.

Thus, he basically tied together foresight research techniques, black swans theory, goldilock hypothesis, Carla Bruni-Sarkozy and the Internet to discuss a sort of attitude towards the future. Some discussions with people+blogpost reading showed that lots of people thought he was “ranting against” this weird french couple. This was not a rant by any means, rather an exemplification of the foresight method and how unexpected events as well as driving forces can be employed to described scenarios. He wanted to state that if we do not have the proper analytical tools, we won’t understand it. It requires to get the the driving forces: “Like an american who learns the rules of soccer, you probably still won’t like it very much, but you will understand why it matters to people, you’ll be able to put into a useful perceptive and get on with you own life.“

In this NYT piece called “The Risk of Innovation: Will Anyone Embrace It?“, G. Pascal Zachary deals with interesting issues regarding innovation. Some excerpts:

“Even today, when adding video to a phone is a trivial cost, consumers may rebel. Video-conferencing often remains an activity forced on people by their employers. Resistance to technology is an omnipresent risk for every innovator. Even a device as fabulously freeing as the personal computer struck some people as an abomination
(…)
Adaptable humans usually trade one technology for another, rather than reject any and all. To be accepted, innovations must deliver benefits — enough benefits to make change worthwhile.
(…)
FOR technological innovators, the cash register can ring either way. They may achieve a smash-hit breakthrough, or simply make a slight improvement in a technology that humans already feel comfortable with. Most innovators no longer even try to predict human reactions to their creations. Henry Kressel, a partner at Warburg Pincus and a co-author of “Competing for the Future: How Digital Innovations Are Changing the World,” says, “You throw technologies into the market and see what sticks.” The hope is that passionate “early adopters” will blaze a path toward mass acceptance of a new technology. Yet the truth is that no one can tell in advance which innovations people will adapt to and which will become the next example of the Picturephone.“

Why do I blog this? some general-and-controversial thoughts about tech/usage foresight.

I already mentioned how “Foundations of Futures Studies: Human Science for a New Era: History, Purposes, Knowledge (Human Science for a New Era, 1)” by Wendell Bell was a relevant reference about future studies/foresight.

One of the book chapter deals with the assumptions of future studies:

“

1. Time is continuous, linear, unidirectional and irreversible (…) the continuum of time defines the past, present and future.
2. Not everything that will exist has existed or does exist. Thus the future may contain things that never existed before.
3. Futures thinking is essential for human action.
4. In making our way in the world, both individually and collectively, the most useful knowledge is “knowledge of the future”. In making plans, exploring alternatives, choosing goals, and deciding how they ought to to act, humans have a need to know the future and how past and present causes will produce future effects.
5. The future is non-evidential and cannot be observed; therefore there are no facts about the future. Nonetheless (…) it is possible to have ‘conjectural’ knowledge.
6. The future is not totally predetermined. It is more or less open.
7. To a greater or lesser degree future outcomes can be influenced by individual and collective action.
8. The interdependence in the world invites a holistic perspective and a transdisciplinary approach both in the organization of knowledge for decision making and in social action.
9. Some futures are better than others

“

Why do I blog this? these assumptions give an interesting frame as they give rationales and directions for future studies. As the author mentions, it’s a selection of them that he exemplifies in his book in more actionable ways.

Just found this article about “the future of futurology” in The World in 2008 of The Economist. It starts of by describing how the word “futurologist” has disappeared from the business and academic world, so has the so-called “futurology” discipline (although “there are still some hold-outs prophesying at the planetary level“). The new thing is rather about scenario-building and storytelling, which is not a surprise.

What is interesting is the underlying reason proposed by the author:

“We can see now that the golden age of blockbuster futurology in the 1960s and 1970s was caused, not by the onset of profound technological and social change, but by the absence of it. The great determining technologies—electricity, the telephone, the internal combustion engine, even manned flight—were the products of a previous century, and their applications were well understood. The geopolitical fundamentals were stable, too, thanks to the cold war. Futurologists extrapolated the most obvious possibilities, with computers and nuclear weapons as their wild cards. The big difference today is that we assume our determining forces to be ones that 99% of us do not understand at all: genetic engineering, nanotechnology, climate change, clashing cultures and seemingly limitless computing power. When the popular sense of direction is baffled, there is no conventional wisdom for futurologists to appropriate or contradict.“

The author also points out to some advices:

1. the next rule lays in thinking short term (“Microtrends”… “nanotrends”)
2. “ say you don’t know. Uncertainty looks smarter than ever before“
3. “for the budding futurist: get embedded in a particular industry, preferably something to do with computing or national security or global warming. All are fast-growing industries fascinated by uncertainty and with little use for generalists. Global warming, in particular, is making general-purpose futurology all but futile. When the best scientists in the field say openly that they can only guess at the long-term effects, how can a futurologist do better?“
4. “talk less, listen more. Thanks to the internet, every intelligent person can amass the sort of information that used to need travel, networking, research assistants, access to power“

Why do I blog this? quite interesting food for thought here, and I agree with the rules.

I sometimes use the Metcalfe Law in my work to describe how communication systems (mobile phones application, location-based services, etc.) have a value only if there is a critical mass of users. Being the only local boob with a fax machine does not allow you to go beyond showing off, it’s actually like having one shoe. First formulated by Robert Metcalfe wrt to Ethernet, Metcalfe’s law states that the value of a telecommunications network is proportional to the square of the number of users of the system(N2).

It’s then interesting to dig that stuff and see why very serious folks in IEEE Spectrum are pondering that argument. They actually critique how this “law” has been turned into a mantra during the Internet Boom (and now with the Web2.0 frenziness) and mostly focus on the correctness of its definition that sits in between linear and exponential growth:

“If Metcalfe’s mathematics were right, how can the law be wrong? Metcalfe was correct that the value of a network grows faster than its size in linear terms; the question is, how much faster? If there are n members on a network, Metcalfe said the value grows quadratically as the number of members grows.

We propose, instead, that the value of a network of size n grows in proportion to n log(n).“

(Taken from here)

But more importantly:

“The fundamental flaw underlying both Metcalfe’s and Reed’s laws is in the assignment of equal value to all connections or all groups. (…) In general, connections are not all used with the same intensity. In fact, in large networks, such as the Internet, with millions and millions of potential connections between individuals, most are not used at all. So assigning equal value to all of them is not justified“

Why do I blog this? it’s interesting to understand how such law can be criticized. I actually do think the cluster metaphor is still valid but one should be cautious about how to employ it (and take the limits they describe into account). Should there be a commonsensical use of that law and a more mathematical one (the latter…. to make quantitative forecast… which I am not into)?

Julian posted on the near future laboratory website the translation from an interview we gave to Digicult, an italian magazine about digital culture.

The interview deals with the near future laboratory’s existence (” an opportunity in a design and research practice that operates between traditional long-term academic research studies and short-term commercial product development“), rationale (”a positive reaction to the difficulties of engaging in creative, insightful, fun and innovative work with fewer of the constraints we have found in academia and in the normal commercial world“) and some current projects.

Why do I blog this? tracking the near future laboratory conversations!

In a WSJ article, Jason Fry how he feels like George Jetson with all the technologies that we have around (cell phone, TiVo, etc). He interestingly describes what was interesting in that TV series:

“Then there was another influence, one that makes space opera sound like real opera. That, of course, was “The Jetsons” — the Hanna- Barbera show featuring flying cars, robot maids, and Space Needle apartment buildings filled with Rube Goldberg labor-saving devices. I doubt the creators of “The Jetsons” ever imagined how they’d
influence kids growing up in the 1970s.
(…)
Why such an influence for a show that was basically “The Flintstones” in aerial houses? (…) The only reason “The Jetsons” is a touchstone for the future instead of just childhood nostalgia is that it was “about” the future –
which was bound to arrive because, well, that’s what the future does. (…) “The Jetsons,” on the other hand, is pretty close to a sure thing, conversationally. (…) The other thing about the future is it tends to arrive slowly — so slowly that often we don’t notice how thoroughly things are changing.“

And then relates to today’s situation:

“I may not have a ticket to a moonbase quite yet, but if you could send me back to the 70s to tell
my nine-year-old self what’s coming, he’d be thrilled. To him, for all intents and purposes I am George Jetson.

What technological milestones have taken place during your lifetime? What do you take for granted that your nine-year-old self would have never believed possible? And what do you think the future holds? “

Why do I blog this? pure interest in (past) representation of the future and how it unfolded afterwards. Cultural artifacts like TV series are part of that ecosystem. And it’s crazy how today the word “jetsons” is employed in discourse about the future (newspaper articles, futurists conference, designers’ discussion and even academic papers).

This notion of a “touchstone” for the future is important, the normative representation of “what could be” at that time is the benchmark towards which one evaluate what we have today (”where’s my 3D video phone that I could use in my flying car?”).

An interview of foresight research Wendel Bell by himself offers interesting elemeents (although the idea of a robotic interviewer is a bit lame). It was actually published in 2005 in the Journal of Futures Studies 10(2) (November 2005): pp. 113-124.

Some excerpts:

“Prediction—or whatever euphemism a futurist may use, such as projection, forecast, foresight, prophecy, or prospective—necessarily enters into what a futurist does. In fact, it is one of the defining features of futures studies. In contemplating the future, we imagine alternative possible futures and we try to assess which futures would be most probable under a variety of conditions, including alternative actions that people might take. We try to answer the “what if” question. For example, what could or would happen if people did this, or that,
or something else? But—and this is important—we seldom predict a single future.
(…)
I am not suggesting that futurists have all the right solutions. But they have been asking the right questions. For example: What can we humans do to create societies that will be sustainable into the far future? What are the conditions under which all people everywhere can have sufficient water and food, modern sanitation, good health, freedom, personal security, and community support?
(…)
Some answers come from the futurist program of investigating the facts of the past and the present and, based on them, making speculative and imaginative, but presumptively true, assertions about possible and probable futures. Answers come, too, from judging these futures by some scale of values, and assessing their relative desirability. They come also from communication among people about these assessments of the desirability of alternative futures and letting people’s voices be heard by decision-makers. Answers come, as I said before, from gaining foresight into the true consequences of our actions. They come, also, from understanding that all people ought to be included in our community of concern, realizing that our own beliefs may be wrong, and showing tolerance toward the beliefs of others“

Why do I blog this? even though the notion of “futurist/m” seems a bit passé and awkward (long-range design, future research, foresight research sounds better), there are some pertinent things here, a good introduction for his book.