Found in an interview of Hugh Raffles about his recent work. He starts off with its anxiety towards theoretical branding and moves to his own ethnographic practice:
“I'm always wary of branding and work pretty hard to not be brandable, quotable, transposable, or in any way modular. I want to encourage people to think about questions in expansive and maybe subtle ways. Taking a key word and inserting it as a stand-in for something often means not having to think through a question or phenomenon more carefully. I guess I’m especially worried about what the impulse to branding--and the rewards for branding--do to graduate students. People start to think there's a currency to a particular type of work and they start referencing it because they think it's a shorthand way to demonstrate a fluency and an up-to-dateness. (…) These types of trends tend to have a limited shelf life too, so right now everyone feels they have to jump into this swimming-pool or else they’ll be missing the fun. But I worry about the students who are enjoying splashing around right now and can’t get a job in 5-7 years’ time because the fad has passed and we’re all doing Inter-Galactic Inorganic Ethnography (that’s IGIE). It may not sound like it but this is actually friendly criticism from a fellow traveler who is excited to see the range of work expanding but just concerned by the emergence of new orthodoxies. I worry that the fashionable is a poor sign under which to do intellectual work. (…) It’s important to not be preoccupied with making mistakes and to be willing to take intellectual risks. It’s also important not to feel that you have to declare some theoretical allegiance or belong to a movement. Of course, you can and should build upon prior intellectual work without being trapped in it and it’s important to have a strong genealogical sense of your own and others work. Obviously, though, these questions are different for students and faculty. There are different institutional contexts and constraints at play. Students have to be very savvy about navigating the discipline while retaining their intellectual independence, particularly in such a tight and shifting market. I’m certainly not utopian about it but I’d like us to be better at creating environments in which people can take risks. The graduate education structure of grant-giving, dissertation-writing, etc., tends to enforce a defensive mode of scholarship, and faculty, too, are rarely given the breathing-space and opportunity to explore radically new directions in their work (…) I’m guessing my project will turn out to be more ethnographic than much of the recent work and less concerned to explicitly generate ‘theory"‘“
Why do I blog this? Some interesting thoughts here about “the discipline” and how to make it… more “spontaneous” perhaps and less tied to labels and theoretical labels, while at the same time focusing on descriptions.
We are concerns for the many perspectives that present a misconstrued perspective on Design Fiction. We felt the need to add a few notes to rectify some of the most common confusion about Design Fiction. A must read: On Design Fiction: Close, But No Cigar.
We are running a little background experiment to turn our “new idioms” observations into digestible and inspiring images that anybody can flipped through when chatting or working on projects. Follow #newidiomsfromthefringes on Instagram.
Nicolas was part of a panel about future imaginaries in Nantes during the Scopitone festival. Organized by Bastien Kerspern (Design Friction), Nicolas shared a presentation describing how we produce design fiction at the Laboratory, and discussed the implications of futures research with Mawena Yehouessi and Irini Papadimitriou (Future Everything).
After Helsinki in 2014, Taipei in 2016 and Mexico last year, Lille (north of France) is going to be the World Design Capital. Nicolas has been asked to be part of the curatorial committee of a big exhibit about design and fictions that will happen around April. More about that soon.
Fabien was part of a panel discussion at PrimerEU in Madrid and reported back from the conference. Like last year in Helsinki, it is the contributions of the younger designers on stage and in the audience with fresh approaches that really make Primer Europe unique and original. We also enjoyed how Jorge Camacho, who recently opened Diagonal Studio, explained in practical detailed his most recent “ethnographic futures” project. Jimmy Loizeau proved again how much of of good man he is with a long “personal” talk about his previous projects with James Auger and more recent work with refugee communities.
Nick spoke at the Emerging Practices Conference in Shanghai about the impact of Machine Intelligence on Culture. He also ran an introduction to Design Fiction session and teamed up with local Creative Associate Simone Rebaudengo to perform some cultural voyeurism through the city.
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“The contents of your shopping basket may change. Almost 30% of our food currently comes from the EU, and it is likely that some foods, such as fresh vegetables and fruit, will become more scarce and more expensive in the event of no deal.”
Today, Brexit would have happened if what eventually happened had not happened. The fears of a soft or a hard Brexit have been extended with a very abstract understanding of what might happen next.
As part of our regular internal Design Fiction exercises, we took something conflictual like Brexit and we placed it firmly in the context of a mundane archetype. Something everyone might experience in the future.
We bring a potential future to the present, not as a prediction but to create a shared understanding of a decision and to evaluate possible implications. The image above is how we translated the BBC headline into that type of mundane situation.
We are super excited and thrilled that the term “Design Fiction” is being heard beyond the relatively small community of designers who have been practicing it over the last decade or so. More organizations and teams are now coming to us looking for a fresh and different approach to addressing their needs, concerns, fears, failures and ambitions that the old PowerPoint and Post-it Design Processes simply cannot handle.
This is encouraging for us as we believe the practice of Design Fiction has enormous potential.
We are also concerned — concerned for the many perspectives that present a misconstrued perspective on Design Fiction.
Note #1: Design Fiction is about understanding implications of decision making. Design Fiction is like a design-based A/B test.
— Have an idea or a range of possible ideas?
Run it through the Design Fiction process to understand how these ideas might play themselves out. Design Fiction allows you to engage the implications of your ideas deeply by creating some possible/probable outcomes. In those engagements you are actually creating artifacts that exist in those possible/probable futures. The artifacts you create are things from the future. When you do Design Fiction, you are like some kind of time traveling anthropologist bringing back things you’ve found. When you create these artifacts, you are engaging the context of its existence — why does this exist? what kind of world surrounds it? who are the people and what are their goals and ambitions?
In this kind of Design Fiction process, the discussions with your team and other stakeholders are bound to yield new ideas. The primary activity though, is to work with your team and stakeholders to understand the implications of decision making. Implications come first. New ideas follow.
Yes, we know that organizations often want to be told the solution to their problems and Design Fiction can certainly help here, as just described. Design Fiction is about studying possible implications — not all of them ‘preferred’, but they are always pragmatic and aligned with reality — not reality distorted.
— How do we do this?
Through the Design Fiction process we create design-based tangible artifacts that represent those implications. Sometimes we refer to these artifacts as props, as if they were the objects from that future, brought back to today to be considered, discussed, mulled over, debated and reflected upon.
With Design Fiction so may get your ‘new possibilities’, but you will get something more valuable: a richer understanding of the results of your ideas, good, bad, normal. This ultimately better prepares you for what happens when your idea is in the world. It allows you to de-risk based on the unexpected outcomes (which always happen).
Design Fiction does something no other design process does — it analyzes the outcomes of decision making today, so you have a clearer perspective and understanding of your possible/probable futures.
Note #2: The Design Fiction process produces tangible future artifacts. It does not produce written stories about a future state. This is a common and understandable misconception, probably based on the fact that the word “Fiction” is in the name.
Design Fiction is not a literary style, nor a purely dystopian visual style, despite its roots in Science Fiction and more specifically the important work of Near Future Laboratory Ambassador, His Eminence, Bruce Sterling, one of the founding fathers of the cyberpunk genre and aesthetic.
If you end up with a draft of a short story or a few paragraphs of a typical UX interaction scenario, or a storyboard, or a little film of someone swiping on a screen to show how your App idea would work — you have not done Design Fiction.
What you’ve done is write a short story, which can only possibly be read as a short story. You haven’t created a designed artifact that is the result — an implication — of a set of decisions, current conditions and other inputs, and wrote something down about it.
What you should ideally produce is something a casual observer may mistake for a contemporary artefact, but which only reveals itself as a fiction on closer inspection. It should be very much “as if..” this thing really existed. It should feel real, normal, not some fantasy. Nor should it be construed as a representation of the future — like a short story, or an illustration of some kind of interaction. (My favorite example of an artifact based on a recent workshop? A pizza menu — from the near future. An actual menu that describes a future state of food tastes, ingredients, means of payment, etc.)
Note #3: Creating an artifact forces you to get into the details of your future world in a way that writing a story does not. When writing, it is easy to skip over uncomfortable details in favor of the “big picture”. Design Fiction makes you sweat the details. For example, if you create a Quick Start Guide for a Self Driving Car there are myriad topics that would need to be addressed to describe how to activate, switch into Uber mode, upgrade firmware, etcetera.
— What should you do then if Design Fiction is more than writing stories?
You should be creating artifacts from that world and going through the work of actually making them — not writing about them.
If you’re exploring a future of self-driving cars and the implications for urban policy, create a physical map for a city as might be given out to the local public, or tourists. What would be in the map and why? Have debates with stakeholders about the challenges that would be faced, the failures that might occur, the brand names of services, new kinds of signage, etcetera. Now you’re doing Design Fiction.
Note #4: Creating artifacts happens early.
Design Fiction is called Design Fiction because it adheres to the principle of making-things-with-which-to-think. If you do this at the end, you’ve missed the point of Design Fiction. You have missed the opportunity to discuss, discover with your team and stakeholders the implications of decision making.
Note #5: Design Fiction does not bias towards “perfect” or preferred outcomes — not because we wouldn’t like these, but because we’re pragmatic.
We are skeptical optimists. We have been doing this long enough to know that such things are always mired in the intractably complicated ways in which earnestly naive ideas (particularly from Silicon Valley) are disconnected from the way they are received and reacted to in the real world.
Most design processes fail to indicate the risks and challenges of decision making today. They are all “Blue Team” exercises that can only imagine the perfect outcomes. The world does not work this way. Decisions today never lead to ideal outcomes. Design Fiction allows you to run through multiple perspectives, multiple outcomes (Good. Neutral. Bad. Ugly.) It’s your “Red Team” exercise that goes along with the hopeful, optimistic outcome that explore a rich, wide, fulsome set of outcomes represented in tangible artifacts — Instagram Stories, YouTube Unboxing Videos, Customer Testimonial Videos (good ones, bad ones), a lower-thirds chyron crawl describing some epic fail of your idea as shown on Fox News, A Quick Start Guide that forces you to figure out how your “idea” would actually work so you can discover that even you can’t (yet) describe how it would actually work. These truly tangible futures help decision makers assess not only their “ideal” outcomes (which we always hope for and, if you’re honest, rarely get perfectly) but the neutral and completely failed outcomes.
When discussing and writing about the future of cities with autonomous vehicles, it is easy to skip over complex details in favor of the “big headlines”.
Any decision-maker serious about evaluating the key opportunities of an idea, investigating challenges and possible complications, must consider the details through-and-through. This is what Design Fiction is good at. It is good at understanding the implications of today’s decisions. It reveals the ways futures could come to life and shows what that looks like in the form of material objects — the tangible artifacts from the future. For example, the creation of a Quick Start Guide for a Self Driving Car reveals a myriad of topics that would need to be addressed to describe how to activate, switch into Uber mode, upgrade firmware, etcetera.
This is the reason why the Department of Mobility at the Canton of Geneva commissioned us to investigate their “what if” scenarios around automated driving. Using our loose Design Fiction process, we selected an artifact that could reveal the implications for urban policy. We wanted a popular artifact, intelligible by a large audience. We created a foldable map of Geneva and brought it back from the future to be given out to the local public or tourists. The point of doing Design Fiction is to create the artifact and going through the work of actually making them — not writing about them. Practically, we loaded OpenStreetMap layers into a Geographic Information System (QGIS) to organize and project the road segment data into a possible future. We iterated several times after discussing the results and using Illustrator to polish the details (e.g. remove road segments, highlight potential consequences) and imagine new legends (e.g. urban canyons, levels of automated traffic).
The foldable map format also gives opportunities to add content alongside the actual street plan. We expanded the world-building inserting descriptions of career opportunities, an upcoming Swiss federal vote on the topic and how the system of fleets of autonomous vehicles actually works with its pick-up and drop-off areas. This content hides provocations and simple hooks to generate discussions. The overall result shows how self-driving cars may have an influence on traffic, urban infrastructures and mobility in general.
The intention for the Department of Mobility at the Canton of Geneva was to generate debates about the challenges that would be faced, the failures that might occur, the services that might emerge, the new kinds of signage and rules, etcetera. The map was used in the context of a local event about the future of the city, along with a series of talks and workshops on various topics public institutions have to deal with (places for kids, agricultural facilities, urbanism against climate change, etc.). In this context, it acted as a tangible future for a group of people with conflicting opinions to exchange point of views. We found out that the discussion revolves around two main topics : the way urban traffic may be reconfigured and redefine what is acceptable on certain streets (e.g. pedestrian movements, presence of non-autonomous vehicles), and the energy infrastructure needed for this technology to happen.
In this project, we imagined the near future as a territory. Maps provide a popular support to tell us how humans, technology and nature co-evolve. They make you travel to a future without actually going there. They bring a future into the hands of an audience with an objective to better understand the implications of today’s socio-technological developments might have on everybody’s life. Finally, our experiment of mixing today’s datasets with future narratives opens the doors of a new practice that uses techniques in Data Science not to predict what comes next but to speculate on the implications of the work of Data Scientists (e.g. automation, augmented intelligence).
An art project I ran across at the Lyon Art Biennale back in 2011.
The Post-Digital seminar at ENS in Paris organized this rather interesting conference in few weeks : Sans ordinateur / Without computer : Anthopocène et imaginaires numériques / Anthropocene and Digital Imaginaries. The call of paper can be found here and here are some excerpts that I find relevant to my own research:
Based on the hypothesis of a collapse of the IT infrastructure, and so, of a post-digital collapse, this symposium aims at suspending the occupation of the world. Given the omnipresence of computers, we want to provoke reflection to imagine what comes after. (…) Under- standing the roots of the mobilization of the world, of which the digital is a part, may mean not reproducing the causes of that which we want to escape in so-called “solutions” to the contemporary ecological crisis. This imaginary, the ambivalent source of the anthropocene, should be described. Our hypothesis is that it is at the crossroads of our science, mythical narratives and images of the world and technology (…) The interventions will aim at analysing the material and ideological impact of digital technologies on our environment and assess their future sustainability. They will also be able to question the use of digital in apocalyptic or innovation stories.
Why do I blog this? Addressing the role, the design and the use of digital technologies in the context of the current environmental crisis is a new interest in my research. Probably not that new considering that I started working on repair practices and the hybridization of low tech and high tech.
Seen in Italy last week-end, the eco-trend is here. That being said, I’m fascinated by the 100% bamboo thing, made me think of all those artists and designers interested in creating wood-based computers.
The business of dishonest automation and how the engineers, data scientists and designers behind it can fix it
“The pilots fought continuously until the end of the flight“, said Capt. Nurcahyo Utomo, the head of the investigation of Lion Air Flight 610 that crashed on October 29, 2018, killing the 189 people aboard. The analysis of the black boxes had revealed that the Boeing 737’s nose was repeatedly forced down, apparently by an automatic system receiving incorrect sensor readings. During 10 minutes preceding the tragedy, the pilots tried 24 times to manually pull up the nose of the plane. They struggled against a malfunctioning anti-stall system that they did not know how to disengage for that specific version of the plane.
That type of dramatic scene of humans struggling with a stubborn automated system belongs to pop culture. In the famous scene of the 1968 science-fiction film “2001: A Space Odyssey”, the astronaut Dave asks HAL (Heuristically programmed ALgorithmic computer) to open a pod bay door on the spacecraft, to which HAL responds repeatedly, “I’m sorry, Dave, I’m afraid I can’t do that“.
1. The commodification of automation
Thankfully, the contemporary applications of digital automation are partial and do not take the shape of an “artificial general intelligence” like HAL. However, the computational tasks that once were exclusively applied to automate human jobs in critical environments like a cockpit have reached people’s everyday lives (e.g. automated way-finding, smart thermostat) and the techniques often deployed for more frivolous but yet very lucrative objectives (e.g. targeted advertisements, prioritizing the next video to watch on YouTube).
“What concerns me is that many engineers, data scientists, designers and decision-makers bring digital frictions into people’s everyday life because they do not employ approaches to foresee the limits and implications of their work”
The automated systems that once relied on programmed instructions based on their author’s understanding of the world now also model their behavior from the patterns found in datasets of sensors and human activities. As the application of these Machine Learning techniques becomes widespread, digital automation is becoming a commodity with systems that perform at Internet scale one task with no deep understanding of human context. These systems are trained to complete that “one” job, but there are evidences that their behavior, like HAL or a Boeing 737 anti-stall system, can turn against their user’s intentions when things do not go as expected.
2. The clumsy edges
Recent visual ethnographies at Near Future Laboratory like #TUXSAX and Curious Rituals uncovered some implications of that commodification of automation. In a completely different scale of dramatic consequences that brought down Lion Air Flight 610, these observations highlight how some digital solutions leave people with a feeling of being “locked in” with no “escape” key to disengage from a stubborn behavior. A wide majority of these digital frictions provoke harmless micro-frustrations in people’s everyday lives. They manifest themselves through poorly calibrated systems and a design that disregards edge cases. For instance, it is common to experience a voice assistant unable to understand a certain accent or pronunciation or a navigation system that misleads a driver due to location inaccuracies, obsolete road data or incorrect traffic information.
These clumsy automations can be mitigated but will not disappear because it became impossible to design contingency plans for all unexpected limitations or consequences. However, other types of stubborn autonomous behaviours are intentionally designed as the core of business models that trades human control for convenience.
3. The business of dishonest automation
Many techniques to automate everyday tasks allow organizations to reduce costs and increase revenues. Some members of the tech industry employ these new technological capabilities to lock customers or workers into behaviors for which they have no legitimate need or desire. Those systems are typically designed to resist from their user’s demands AND are hard to disengage. Let me give you a couple of examples of what I call “dishonest automations”:
3.1. Data obesity
Automatic cloud backup systems have become a default feature of operating systems. They externalize the storage of personal photos, emails, contacts and other bits of digital life. Their business model encourages customers to endlessly accumulate more content without a clear alternative that promotes a proper hygiene with their data (i.e. nobody has yet come up with “Marie Kondo for Dropbox ™”). Regardless of the promises of the providers, it becomes harder for people to declutter their digital lives from a cloud storage service.
3.2. Systemic obsolescence
Today’s apps automatic updates often increase the demand of resources and processing power for cosmetic improvements almost in a deliberate attempt to make a hardware obsolete and the software harder to operate. After years of impunity, there is now a bigger conscience against systemic obsolescence because it is wasteful and exploits customers.
3.3. Digital attention
As content grows exponentially on the Internet, (social) media companies rely increasingly on automation to filter and direct information to each one of their users. For instance, YouTube automates billions of videos to play next for 1.5 billion users. These algorithms aim at promoting content for higher engagement and tend to guide people against their interest.
In the light of these examples of clumsy and dishonest automation, what concerns me is that many engineers, data scientists, designers and decision-makers bring these frictions into people’s everyday life because they do not employ approaches to foresee the limits and implications of their work. Apart from the engineering of efficient solutions, automation requires professionals to think about the foundations and consequences of their practice that transcend any Key Performance Indicator of their organization.
4. The design for humane automation
The design of automation is not about removing the presence of humans. It is about the design of humane, respectful and trustful systems that automate some aspects of human activities. When working with data scientists, designers and engineers in that domain, we envision systems beyond the scope of the “user” and the “task” to automate. I encourage teams to a) learn from the past b) critique the present and c) debate the future. Let me explain:
4.1. Learn from the past
When it comes to automation, the acquisition of knowledge in academia and in the industry are not separate pursuits. Over the last 50 years, there has been an extensive body of work produced in research institutions on the implications of automating manual tasks and decision-making. The key findings have helped save money in critical environments and prevent numerous deadly errors (e.g. in cockpits).
Today, that knowledge is not translated into everyday tasks. For instance, many engineers or data scientists do not master concepts like automation bias (i.e. the propensity for humans to favor suggestions from automated decision-making systems) or automation complacency (i.e. decreased human attention to monitor automated results) theorized by research communities in Science and Technology Studies or Human-Computer Interaction. Sadly, only a few organizations promote platforms that gather academics, artists, engineers, data scientists and designers. Industries in the process of digitization would greatly profit from this type cross-pollination of professionals who learn from considerations that already emerged outside of their discipline.
4.2. Critique the present
I believe that the professionals involved in the business of automating human activities should be persistent critical reviewers of the solutions deployed by their peers. They should become stalkers of how people deal today with the clumsy, the dishonest, the annoying, the absurd and any other awkward emerges of digital technologies in their modern lives.
When properly documented, these observations offer a complementary form of inspiration to the multitude of “naive optimism” and glamorous utopian visions of the tech industry. They provide material for professionals to question arguably biased goals of automation. Moreover, they set the stage to define attainable objectives in their organization (e.g. what does smart/intelligent mean?, how to measure efficiency?, what must become legible?).
4.3. Debate the future
In today’s Internet, the design of even the most simple application or connected object has become a complex endeavour. They are built on balkanized Operating Systems, stacks of numerous protocols, versions, frameworks, and other packages of reusable code. The mitigation of digital frictions goes beyond the scope of a “Quality Assurance” team that guarantees the sanity of an application. They are also about documenting implications on the context the technologies live, unintended consequences and ‘what if’ scenarios.
Typically, Design Fiction is an approach to spark a conversation and anticipate the larger questions regarding the automation of human activities. For instance, we produced Quick Start Guide of Amazon Helios: Pilot, a fictional autonomous vehicle. In that project, we identified the key systems that implicate the human aspects of a self-driving car and we brought to life such experiences in a very tangible, compelling fashion for designers, engineers, and anyone else involved in the development of automated systems. Through its collective production, the Quick Start Guide became a totem through which anybody could discuss the consequences, raise design considerations and shape decision-making.
5. The business of trust
Like many technological evolution, the automation of everyday life does not come without the frictions of trading control for convenience. However, the consequences are bigger than mitigating edge cases. They reflect human, organization or society choices. The choice of deploying systems that mislead about their intentions in conflict with people and society’s interests.
In his seminal work on Ubiquitous Computing in the 90s, Mark Weiser strongly influenced the current “third wave” in computing, when technology recedes into the background of people’s lives. Many professionals in the tech industry (including me) embraced his description of Calm technology that “informs but doesn’t demand our focus or attention.” However, what Weiser and many others (including me) did not anticipate is an industry of dishonest automation or solutions that turn against their user’s intentions when things do not go as planned. Nor did we truly anticipate the scale in which automation can bite back the organizations that deploy them with backslashes from their customers, society as well as policymakers.
These implications suggest an alternative paradigm that transcend the purely technological and commercial for any organization involved in the business of digital automation. For instance, a paradigm that promotes respectful (over efficient), legible (over calm) and honest (over smart) technologies. Those are the types of values that emerge when professionals (e.g. engineers, data scientists, designers, decision-makers, executives) wander outside their practice, apply critical thinking to uncover dishonest behaviors, and use fictions to take decisions that consider implications beyond the scope of the “user” and the “task” to automate.
I believe that the organizations in the business of automation that maintain the status-quo and do not evolve into a business of trust might eventually need to deal with a corroded reputation and its effects on their internal values, the moral of employees, the revenues and ultimately the stakeholders trust.
Do these selfies taken by two people who don’t know each other give us a glimpse of the future? Will the ever-increasing use of technological devices reconfigure our bodies? Will it affect our posture even in the most banal situations?
Those are some of the questions we asked in Mobile Ordinary Gestures, a booklet that describes a typology of gestures and postures adopted when using smartphones. Without claiming completeness, this selection represents a pictorial archive documenting people intriguing interactions with mobile technology.
Similar to Curious Rituals, we use this type of visual ethnography as signals of change of the present from which to extrapolate when designing futures. The documentation of this current body language can also inform the adaptation of current interfaces, or the creation of products that can support, help or benefit from the gestures and rituals we found.
Paperback by Nicolas Nova (Near Future Laboratory) in collaboration with Constance Delamadeleine (Future Neue) Publisher: The Near Future Laboratory Published: October 1, 2016 Language: English Pages: 68
We created eight tiny “Design Fictions” (two of them will appear as Instagram Stories — so keep an eye out..they may be the best ones) that will appear in their feed.
Why did we create these? Aside from the unique opportunity to work with the Design Museum, it gave us an opportunity to do what we enjoy the most: creating meaningful design fictions that reflect upon the challenges of life in today’s weird worlds. Those reflections are meant to be engaging enough that designers of all kinds, which does not include “technologists” nor “business managers” — will consider that their ideas for tomorrow may actually be really shitty, and they should go back to their workstations and workshops and try harder to make products, services, experiences that stand a better change of making a more habitable near future.
We look at design fiction as a form of extrospection — looking from today to see possible near futures based on present state. What might the world look like tomorrow if the assumptions about what’s “new” projected into the future? What are the procedures and methods by which we can project into the near future a new product idea or service strategy — and learn about where the idea might work really well, or how the service strategy could go horribly wrong?
Design Fiction is one of the ways we work with our partners and clients to learn from the future and apply those learnings and insights to make better decisions.