Note: in a time when we'll soon have for the first timea national vote in Switzeralnd about the Revenu de Base Inconditionnel ("Universal Basic Income") --next June, with a low chance of success this time, let's face it--, when people start to speak about the fact that they should get incomes to fuel global corporations with digital data and content of all sorts, when some new technologies could modify the current digital deal, this is a manifesto that is certainly more than interesting to consider. So as its criticism in this paper, as it appears truly complementary.
More generally, thinking the Future in different terms than liberalism is an absolute necessity. Especially in a context where, also as stated, "Automation and unemployment are the future, regardless of any human intervention".
IN THE NEXT FEW DECADES, your job is likely to be automated out of existence. If things keep going at this pace, it will be great news for capitalism. You’ll join the floating global surplus population, used as a threat and cudgel against those “lucky” enough to still be working in one of the few increasingly low-paying roles requiring human input. Existing racial and geographical disparities in standards of living will intensify as high-skill, high-wage, low-control jobs become more rarified and centralized, while the global financial class shrinks and consolidates its power. National borders will continue to be used to control the flow of populations and place migrant workers outside of the law. The environment will continue to be the object of vicious extraction and the dumping ground for the negative externalities of capitalist modes of production.
It doesn’t have to be this way, though. While neoliberal capitalism has been remarkably successful at laying claim to the future, it used to belong to the left — to the party of utopia. Nick Srnicek and Alex Williams’s Inventing the Future argues that the contemporary left must revive its historically central mission of imaginative engagement with futurity. It must refuse the all-too-easy trap of dismissing visions of technological and social progress as neoliberal fantasies. It must seize the contemporary moment of increasing technological sophistication to demand a post-scarcity future where people are no longer obliged to be workers; where production and distribution are democratically delegated to a largely automated infrastructure; where people are free to fish in the afternoon and criticize after dinner. It must combine a utopian imagination with the patient organizational work necessary to wrest the future from the clutches of hegemonic neoliberalism.
Strategies and Tactics
In making such claims, Srnicek and Williams are definitely preaching to the leftist choir, rather than trying to convert the masses. However, this choir is not just the audience for, but also the object of, their most vituperative criticism. Indeed, they spend a great deal of the book arguing that the contemporary left has abandoned strategy, universalism, abstraction, and the hard work of building workable, global alternatives to capitalism. Somewhat condescendingly, they group together the highly variegated field of contemporary leftist tactics and organizational forms under the rubric of “folk politics,” which they argue characterizes a commitment to local, horizontal, and immediate actions. The essentially affective, gestural, and experimental politics of movements such as Occupy, for them, are a retreat from the tradition of serious militant politics, to something like “politics-as-drug-experience.”
Whatever their problems with the psychodynamics of such actions, Srnicek and Williams argue convincingly that localism and small-scale, prefigurative politics are simply inadequate to challenging the ideological dominance of neoliberalism — they are out of step with the actualities of the global capitalist system. While they admire the contemporary left’s commitment to self-interrogation, and its micropolitical dedication to the “complete removal of all forms of oppression,” Srnicek and Williams are ultimately neo-Marxists, committed to the view that “[t]he reality of complex, globalised capitalism is that small interventions consisting of relatively non-scalable actions are highly unlikely to ever be able to reorganise our socioeconomic system.” The antidote to this slow localism, however, is decidedly not fast revolution.
Instead, Inventing the Future insists that the left must learn from the strategies that ushered in the currently ascendant neoliberal hegemony. Inventing the Future doesn’t spend a great deal of time luxuriating in pathos, preferring to learn from their enemies’ successes rather than lament their excesses. Indeed, the most empirically interesting chunk of their book is its careful chronicle of the gradual, stepwise movement of neoliberalism from the “fringe theory” of a small group of radicals to the dominant ideological consensus of contemporary capitalism. They trace the roots of the “neoliberal thought collective” to a diverse range of trends in pre–World War II economic thought, which came together in the establishment of a broad publishing and advocacy network in the 1950s, with the explicit strategic aim of winning the hearts and minds of economists, politicians, and journalists. Ultimately, this strategy paid off in the bloodless neoliberal revolutions during the international crises of Keynesianism that emerged in the 1980s.
What made these putsches successful was not just the neoliberal thought collective’s ability to represent political centrism, rational universalism, and scientific abstraction, but also its commitment to organizational hierarchy, internal secrecy, strategic planning, and the establishment of an infrastructure for ideological diffusion. Indeed, the former is in large part an effect of the latter: by the 1980s, neoliberals had already spent decades engaged in the “long-term redefinition of the possible,” ensuring that the institutional and ideological architecture of neoliberalism was already well in place when the economic crises opened the space for swift, expedient action.
Demands
Srnicek and Williams argue that the left must abandon its naïve-Marxist hopes that, somehow, crisis itself will provide the space for direct action to seize the hegemonic position. Instead, it must learn to play the long game as well. It must concentrate on building institutional frameworks and strategic vision, cultivating its own populist universalism to oppose the elite universalism of neoliberal capital. It must also abandon, in so doing, its fear of organizational closure, hierarchy, and rationality, learning instead to embrace them as critical tactical components of universal politics.
There’s nothing particularly new about Srnicek and Williams’s analysis here, however new the problems they identify with the collapse of the left into particularism and localism may be. For the most part, in their vituperations, they are acting as rather straightforward, if somewhat vernacular, followers of the Italian politician and Marxist theorist Antonio Gramsci. As was Gramsci’s, their political vision is one of slow, organizationally sophisticated, passive revolution against the ideological, political, and economic hegemony of capitalism. The gradual war against neoliberalism they envision involves critique and direct action, but will ultimately be won by the establishment of a post-work counterhegemony.
In putting forward their vision of this organization, they strive to articulate demands that would allow for the integration of a wide range of leftist orientations under one populist framework. Most explicitly, they call for the automation of production and the provision of a basic universal income that would provide each person the opportunity to decide how they want to spend their free time: in short, they are calling for the end of work, and for the ideological architecture that supports it. This demand is both utopian and practical; they more or less convincingly argue that a populist, anti-work, pro-automation platform might allow feminist, antiracist, anticapitalist, environmental, anarchist, and postcolonial struggles to become organized together and reinforce one another. Their demands are universal, but designed to reflect a rational universalism that “integrates difference rather than erasing it.” The universal struggle for the future is a struggle for and around “an empty placeholder that is impossible to fill definitively” or finally: the beginning, not the end, of a conversation.
In demanding full automation of production and a universal basic income, Srnicek and Williams are not being millenarian, not calling for a complete rupture with the present, for a complete dismantling and reconfiguration of contemporary political economy. On the contrary, they argue that “it is imperative […] that [the left’s] vision of a new future be grounded upon actually existing tendencies.” Automation and unemployment are the future, regardless of any human intervention; the momentum may be too great to stop the train, but they argue that we can change tracks, can change the meaning of a future without work. In demanding something like fully automated luxury communism, Srnicek and Williams are ultimately asserting the rights of humanity as a whole to share in the spoils of capitalism.
Criticisms
Inventing the Future emerged to a relatively high level of fanfare from leftist social media. Given the publicity, it is unsurprising that other more “engagé” readers have already advanced trenchant and substantive critiques of the future imagined by Srnicek and Williams. More than a few of these critics have pointed out that, despite their repeated insistence that their post-work future is an ecologically sound one, Srnicek and Williams evince roughly zero self-reflection with respect either to the imbrication of microelectronics with brutally extractive regimes of production, or to their own decidedly antiquated, doctrinaire Marxist understanding of humanity’s relationship towards the nonhuman world. Similarly, the question of what the future might mean in the Anthropocene goes largely unexamined.
More damningly, however, others have pointed out that despite the acknowledged counterintuitiveness of their insistence that we must reclaim European universalism against the proliferation of leftist particularisms, their discussions of postcolonial struggle and critique are incredibly shallow. They are keen to insist that their universalism will embrace rather than flatten difference, that it will be somehow less brutal and oppressive than other forms of European univeralism, but do little of the hard argumentative work necessary to support these claims. While we see the start of an answer in their assertion that the rejection of universal access to discourses of science, progress, and rationality might actually function to cement certain subject-positions’ particularity, this — unfortunately — remains only an assertion. At best, they are being uncharitable to potential allies in refusing to take their arguments seriously; at worst, they are unreflexively replicating the form if not the content of patriarchal, racist, and neocolonial capitalist rationality.
For my part, while I find their aggressive and unapologetic presentation of their universalism somewhat off-putting, their project is somewhat harder to criticize than their book — especially as someone acutely aware of the need for more serious forms of organized thinking about the future if we’re trying to push beyond the horizons offered by the neoliberal consensus.
However, as an anthropologist of the computer and data sciences, it’s hard for me to ignore a curious and rather serious lacuna in their thinking about automaticity, algorithms, and computation. Beyond the automation of work itself, they are keen to argue that with contemporary advances in machine intelligence, the time has come to revisit the planned economy. However, in so doing, they curiously seem to ignore how this form of planning threatens to hive off economic activity from political intervention. Instead of fearing a repeat of the privations that poor planning produced in earlier decades, the left should be more concerned with the forms of control and dispossession successful planning produced. The past decade has seen a wealth of social-theoretical research into contemporary forms of algorithmic rationality and control, which has rather convincingly demonstrated the inescapable partiality of such systems and their tendency to be employed as decidedly undemocratic forms of technocratic management.
Srnicek and Williams, however, seem more or less unaware of, or perhaps uninterested in, such research. At the very least, they are extremely overoptimistic about the democratization and diffusion of expertise that would be required for informed mass control over an economy planned by machine intelligence. I agree with their assertion that “any future left must be as technically fluent as it is politically fluent.” However, their definition of technical fluency is exceptionally narrow, confined to an understanding of the affordances and internal dynamics of technical systems rather than a comprehensive analysis of their ramifications within other social structures and processes. I do not mean to suggest that the democratic application of machine learning and complex systems management is somehow a priori impossible, but rather that Srnicek and Williams do not even seem to see how such systems might pose a challenge to human control over the means of production.
In a very real sense, though, my criticisms should be viewed as a part of the very project proposed in the book. Inventing the Future is unapologetically a manifesto, and a much-overdue clarion call to a seriously disorganized metropolitan left to get its shit together, to start thinking — and arguing — seriously about what is to be done. Manifestos, like demands, need to be pointed enough to inspire, while being vague enough to promote dialogue, argument, dissent, and ultimately action. It’s a hard tightrope to walk, and Srnicek and Williams are not always successful. However, Inventing the Future points towards an altogether more coherent and mature project than does their #ACCELERATE MANIFESTO. It is hard to deny the persuasiveness with which the book puts forward the positive contents of a new and vigorous populism; in demanding full automation and universal basic income from the world system, they also demand the return of utopian thinking and serious organization from the left.
Note: j'aurai le plaisir d'être en entretien --en français-- ce vendredi 26.02 à 20h avec le journaliste Frédéric Pfyffer, de la Radio Télévision Suisse Romande, dans le cadre du programme Histoire Vivante qui traite cette semaine du sujet des "Big Data".
Cet entretien, qui a été enregistré en fin de semaine passée, nous verra évoquer la façon dont les artistes ou designers abordent aujourd'hui --mais aussi un peu hier-- cette question des données. En contrepoint ou complément peut-être des approches scientifiques. Pour ma part, aussi bien dans le contexte de ma pratique indépendante (fabric | ch où de nombreux projets réalisés ou en développement s'appuient sur des données) qu'académique (projet de recherche interdisciplinaire en cours autour des "nuages"... entre autres).
À noter encore qu'au terme de la semaine d'émissions thématiques sera diffusé sur la TSR (dimanche 28.02) le documentaire Citizenfour, qui relate toute l'aventure d'Edward Snowden et du journaliste Glenn Greenwald.
Une semaine d’Histoire Vivante consacrée à l’histoire de la recherche scientifique à la lumière de l’émergence de l’internet et des big data.
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Dimanche 28 février 2016, vous pouvez découvrir sur RTS Deux: CitizenFour, un documentaire de Laura Poitras (Allemagne-USA/2014):
"Citizenfour est le pseudonyme utilisé par Edward Snowden pour contacter la réalisatrice de ce documentaire lorsqu'il décide de révéler les méthodes de surveillance de la NSA. Accompagnée d'un journaliste d'investigation, elle le rejoint dans une chambre d'hôtel à Hong Kong. La suite est un huis-clos digne des meilleurs thrillers."
Note: can a computer "fake" a human? (hmmm, sounds a bit like Mr. Turing test isn't it?) Or at least be credible enough --because it sounds pretty clear in this video, at that time, that it cannot fake a human and that it is m ore about voice than "intelligence"-- so that the person on the other side of the phone doesn't hang up? This is a funny/uncanny experiment involving D. Sherman at Michigan State University, dating back 1974 and certainly one of the first public trial (or rather social experiment) of a text to speech/voice synthesizer.
Beyond the technical performance, it is the social experiment that is probably even more interesting. It's intertwined and odd nature. You can feel in the voice of the person on the other side of the phone (at the pizza factory --Domino's pizza--) that he really doesn't know how to take it and that the voice sounds like something not heard before. A few trials were necessary before somebody took it "seriously".
Every year, the researchers, students, and technology users who make up the community of the Michigan State University Artificial Language Laboratory celebrate the anniversary of the first use of a speech prosthesis in history: the use by a man with a communication disorder to order a pizza over the telephone using a voice synthesizer. This high-tech sociolinguistic experiment was conducted at the Lab on the evening of December 4, 1974. Donald Sherman, who has Moebius Syndrome and had never ordered a pizza over the phone before, used a system designed by John Eulenberg and J. J. Jackson incorporating a Votrax voice synthesizer, a product of the Federal Screw Works Co. of Troy, Michigan. The inventor of the Votrax voice synthesizer was Richard Gagnon from Birmingham, MI.
The event was covered at the time by the local East Lansing cable news reporter and by a reporter from the State News. About seven years later, in 1981, a BBC production team produced a documentary about the work of the Artificial Language Laboratory and included a scene of a man with cerebral palsy, Michael Williams, ordering a pizza with a newer version of the Lab's speech system. This second pizza order became a part of the documentary, which was broadcast throughout the U.S. as part of the "Nova" science series and internationally as part of the BBC's "Horizon" series.
In January, 1982, the Nova show on the Artificial Language Lab was shown for the first time. The Artificial Language Lab held a premiere party in the Communication Arts and Sciences Building for all the persons who appeared in the program plus all faculty members of the College of Communication Arts and Sciences and their families. The Domino's company generously provided free pizzas for all the guests.
The following December, Domino's again provided pizzas for a party, again held at the Communication Arts building, to commemorate the first ordering of a pizza eight years earlier. The Convocation was held thereafter every year through 1988, each year receiving pizzas through the generous gift of Domino's.
A Communication Enhancement Convocation was held in 1999, celebrating the 25th anniversary of the first pizza order.In addition to Dominos's contribution of pizzas, the Canada Dry Bottling Co. of Lansing provided drinks.The Convocations resumed in 2010 through 2012, when Dr. John Eulenberg advanced to Professor Emeritus status.
At each event, in addition to faculty and students, the convocation guests included local dignitaries from the MSU board of trustees and from the Michigan state legislature. Stevie Wonder, whose first talking computer and first singing computer were designed at the Artificial Language Lab, made telephone appearances and spoke with the youngsters using Artificial Language Lab technology through their
school district special education programs. MSU icons such as the football team, Sparty, and cheer leaders made appearances as well.
Now, through YouTube, we can relive this historical moment and take a thoughtful look back at 40 years of progress in the delivery of augmentative communication technology to persons with disabilities.
Songdo in South Korea: a ‘smart city’ whose roads and water, waste and electricity systems are dense with electronic sensors. Photograph: Hotaik Sung/Alamy.
A woman drives to the outskirts of the city and steps directly on to a train; her electric car then drives itself off to park and recharge. A man has a heart attack in the street; the emergency services send a drone equipped with a defibrillator to arrive crucial minutes before an ambulance can. A family of flying maintenance robots lives atop an apartment block – able to autonomously repair cracks or leaks and clear leaves from the gutters.
Such utopian, urban visions help drive the “smart city” rhetoric that has, for the past decade or so, been promulgated most energetically by big technology, engineering and consulting companies. The movement is predicated on ubiquitous wireless broadband and the embedding of computerised sensors into the urban fabric, so that bike racks and lamp posts, CCTV and traffic lights, as well as geeky home appliances such as internet fridges and remote-controlled heating systems, become part of the so-called “internet of things” (the global market for which is now estimated at $1.7tn). Better living through biochemistry gives way to a dream of better living through data. You can even take an MSc in Smart Cities at University College, London.
Yet there are dystopian critiques, too, of what this smart city vision might mean for the ordinary citizen. The phrase itself has sparked a rhetorical battle between techno-utopianists and postmodern flâneurs: should the city be an optimised panopticon, or a melting pot of cultures and ideas?
And what role will the citizen play? That of unpaid data-clerk, voluntarily contributing information to an urban database that is monetised by private companies? Is the city-dweller best visualised as a smoothly moving pixel, travelling to work, shops and home again, on a colourful 3D graphic display? Or is the citizen rightfully an unpredictable source of obstreperous demands and assertions of rights? “Why do smart cities offer only improvement?” asks the architect Rem Koolhaas. “Where is the possibility of transgression?”
Smart beginnings: a crowd watches as new, automated traffic lights are erected at Ludgate Circus, London, in 1931. Photograph: Fox Photos/Getty Images
The smart city concept arguably dates back at least as far as the invention of automated traffic lights, which were first deployed in 1922 in Houston, Texas. Leo Hollis, author of Cities Are Good For You, says the one unarguably positive achievement of smart city-style thinking in modern times is the train indicator boards on the London Underground. But in the last decade, thanks to the rise of ubiquitous internet connectivity and the miniaturisation of electronics in such now-common devices as RFID tags, the concept seems to have crystallised into an image of the city as a vast, efficient robot – a vision that originated, according to Adam Greenfield at LSE Cities, with giant technology companies such as IBM, Cisco and Software AG, all of whom hoped to profit from big municipal contracts.
“The notion of the smart city in its full contemporary form appears to have originated within these businesses,” Greenfield notes in his 2013 book Against the Smart City, “rather than with any party, group or individual recognised for their contributions to the theory or practice of urban planning.”
Whole new cities, such as Songdo in South Korea, have already been constructed according to this template. Its buildings have automatic climate control and computerised access; its roads and water, waste and electricity systems are dense with electronic sensors to enable the city’s brain to track and respond to the movement of residents. But such places retain an eerie and half-finished feel to visitors – which perhaps shouldn’t be surprising. According to Antony M Townsend, in his 2013 book Smart Cities, Songdo was originally conceived as “a weapon for fighting trade wars”; the idea was “to entice multinationals to set up Asian operations at Songdo … with lower taxes and less regulation”.
In India, meanwhile, prime minister Narendra Modi has promised to build no fewer than 100 smart cities – a competitive response, in part, to China’s inclusion of smart cities as a central tenet of its grand urban plan. Yet for the near-term at least, the sites of true “smart city creativity” arguably remain the planet’s established metropolises such as London, New York, Barcelona and San Francisco. Indeed, many people think London is the smartest city of them all just now — Duncan Wilson of Intel calls it a “living lab” for tech experiments.
So what challenges face technologists hoping to weave cutting-edge networks and gadgets into centuries-old streets and deeply ingrained social habits and patterns of movement? This was the central theme of the recent “Re.Work Future Cities Summit” in London’s Docklands – for which two-day public tickets ran to an eye-watering £600.
The event was structured like a fast-cutting series of TED talks, with 15-minute investor-friendly presentations on everything from “emotional cartography” to biologically inspired buildings. Not one non-Apple-branded laptop could be spotted among the audience, and at least one attendee was seen confidently sporting the telltale fat cyan arm of Google Glass on his head.
“Instead of a smart phone, I want you all to have a smart drone in your pocket,” said one entertaining robotics researcher, before tossing up into the auditorium a camera-equipped drone that buzzed around like a fist-sized mosquito. Speakers enthused about the transport app Citymapper, and how the city of Zurich is both futuristic and remarkably civilised. People spoke about the “huge opportunity” represented by expanding city budgets for technological “solutions”.
Usman Haque’s project Thingful is billed as a ‘search engine for the internet of things’
Strikingly, though, many of the speakers took care to denigrate the idea of the smart city itself, as though it was a once-fashionable buzzphrase that had outlived its usefulness. This was done most entertainingly by Usman Haque, of the urban consultancy Umbrellium. The corporate smart-city rhetoric, he pointed out, was all about efficiency, optimisation, predictability, convenience and security. “You’ll be able to get to work on time; there’ll be a seamless shopping experience, safety through cameras, et cetera. Well, all these things make a city bearable, but they don’t make a city valuable.”
As the tech companies bid for contracts, Haque observed, the real target of their advertising is clear: “The people it really speaks to are the city managers who can say, ‘It wasn’t me who made the decision, it was the data.’”
Of course, these speakers who rejected the corporate, top-down idea of the smart city were themselves demonstrating their own technological initiatives to make the city, well, smarter. Haque’s project Thingful, for example, is billed as a search engine for the internet of things. It could be used in the morning by a cycle commuter: glancing at a personalised dashboard of local data, she could check local pollution levels and traffic, and whether there are bikes in the nearby cycle-hire rack.
“The smart city was the wrong idea pitched in the wrong way to the wrong people,” suggested Dan Hill, of urban innovators the Future Cities Catapult. “It never answered the question: ‘How is it tangibly, materially going to affect the way people live, work, and play?’” (His own work includes Cities Unlocked, an innovative smartphone audio interface that can help visually impaired people navigate the streets.) Hill is involved with Manchester’s current smart city initiative, which includes apparently unglamorous things like overhauling the Oxford Road corridor – a bit of “horrible urban fabric”. This “smart stuff”, Hill tells me, “is no longer just IT – or rather IT is too important to be called IT any more. It’s so important you can’t really ghettoise it in an IT city. A smart city might be a low-carbon city, or a city that’s easy to move around, or a city with jobs and housing. Manchester has recognised that.”
One take-home message of the conference seemed to be that whatever the smart city might be, it will be acceptable as long as it emerges from the ground up: what Hill calls “the bottom-up or citizen-led approach”. But of course, the things that enable that approach – a vast network of sensors amounting to millions of electronic ears, eyes and noses – also potentially enable the future city to be a vast arena of perfect and permanent surveillance by whomever has access to the data feeds.
Inside Rio de Janeiro’s centre of operations: ‘a high-precision control panel for the entire city’. Photograph: David Levene
One only has to look at the hi-tech nerve centre that IBM built for Rio de Janeiro to see this Nineteen Eighty-Four-style vision already alarmingly realised. It is festooned with screens like a Nasa Mission Control for the city. As Townsend writes: “What began as a tool to predict rain and manage flood response morphed into a high-precision control panel for the entire city.” He quotes Rio’s mayor, Eduardo Paes, as boasting: “The operations centre allows us to have people looking into every corner of the city, 24 hours a day, seven days a week.”
What’s more, if an entire city has an “operating system”, what happens when it goes wrong? The one thing that is certain about software is that it crashes. The smart city, according to Hollis, is really just a “perpetual beta city”. We can be sure that accidents will happen – driverless cars will crash; bugs will take down whole transport subsystems or the electricity grid; drones could hit passenger aircraft. How smart will the architects of the smart city look then?
A less intrusive way to make a city smarter might be to give those who govern it a way to try out their decisions in virtual reality before inflicting them on live humans. This is the idea behind city-simulation company Simudyne, whose projects include detailed computerised models for planning earthquake response or hospital evacuation. It’s like the strategy game SimCity – for real cities. And indeed Simudyne now draws a lot of its talent from the world of videogames. “When we started, we were just mathematicians,” explains Justin Lyon, Simudyne’s CEO. “People would look at our simulations and joke that they were inscrutable. So five or six years ago we developed a new system which allows you to make visualisations – pretty pictures.” The simulation can now be run as an immersive first-person gameworld, or as a top-down SimCity-style view, where “you can literally drop policy on to the playing area”.
Another serious use of “pretty pictures” is exemplified by the work of ScanLAB Projects, which uses Lidar and ground-penetrating radar to make 3D visualisations of real places. They can be used for art installations and entertainment: for example, mapping underground ancient Rome for the BBC. But the way an area has been used over time, both above and below ground, can also be presented as a layered historical palimpsest, which can serve the purposes of archaeological justice and memory – as with ScanLAB’s Living Death Camps project with Forensic Architecture, on two concentration-camp sites in the former Yugoslavia.
The former German pavilion at Staro Sajmište, Belgrade – produced from terrestrial laser scanning and ground-penetrating radar as part of the Living Death Camps project. Photograph: ScanLAB Projects
For Simudyne’s simulations, meanwhile, the visualisations work to “gamify” the underlying algorithms and data, so that anyone can play with the initial conditions and watch the consequences unfold. Will there one day be convergence between this kind of thing and the elaborately realistic modelled cities that are built for commercial videogames? “There’s absolutely convergence,” Lyon says. A state-of-the art urban virtual reality such as the recreation of Chicago in this year’s game Watch Dogs requires a budget that runs to scores of millions of dollars. But, Lyon foresees, “Ten years from now, what we see in Watch Dogs today will be very inexpensive.”
What if you could travel through a visually convincing city simulation wearing the VR headset, Oculus Rift? When Lyon first tried one, he says, “Everything changed for me.” Which prompts the uncomfortable thought that when such simulations are indistinguishable from the real thing (apart from the zero possibility of being mugged), some people might prefer to spend their days in them. The smartest city of the future could exist only in our heads, as we spend all our time plugged into a virtual metropolitan reality that is so much better than anything physically built, and fail to notice as the world around us crumbles.
In the meantime, when you hear that cities are being modelled down to individual people – or what in the model are called “agents” – you might still feel a jolt of the uncanny, and insist that free-will makes your actions in the city unpredictable. To which Lyon replies: “They’re absolutely right as individuals, but collectively they’re wrong. While I can’t predict what you are going to do tomorrow, I can have, with some degree of confidence, a sense of what the crowd is going to do, what a group of people is going to do. Plus, if you’re pulling in data all the time, you use that to inform the data of the virtual humans.
“Let’s say there are 30 million people in London: you can have a simulation of all 30 million people that very closely mirrors but is not an exact replica of London. You have the 30 million agents, and then let’s have a business-as-usual normal commute, let’s have a snowstorm, let’s shut down a couple of train lines, or have a terrorist incident, an earthquake, and so on.” Lyons says you will get a highly accurate sense of how people, en masse, will respond to these scenarios. “While I’m not interested in a specific individual, I’m interested in the emergent behaviour of the crowd.”
City-simulation company Simudyne creates computerised models ‘with pretty pictures’ to aid disaster-response planning
But what about more nefarious bodies who are interested in specific individuals? As citizens stumble into a future where they will be walking around a city dense with sensors, cameras and drones tracking their every movement – even whether they are smiling (as has already been tested at the Cheltenham Jazz Festival) or feeling gloomy – there is a ticking time-bomb of arguments about surveillance and privacy that will dwarf any previous conversations about Facebook or even, perhaps, government intelligence agencies scanning our email. Unavoidable advertising spam everywhere you go, as in Minority Report, is just the most obvious potential annoyance. (There have already been “smart billboards” that recognised Minis driving past and said hello to them.) The smart city might be a place like Rio on steroids, where you can never disappear.
“If you have a mobile phone, and the right sensors are deployed across the city, people have demonstrated the ability to track those individual phones,” Lyon points out. “And there’s nothing that would prevent you from visualising that movement in a SimCity-like landscape, like in Watch Dogs where you see an avatar moving through the city and you can call up their social-media profile. If you’re trying to search a very large dataset about how someone’s moving, it’s very hard to get your head around it, but as soon as you fire up a game-style visualisation, it’s very easy to see, ‘Oh, that’s where they live, that’s where they work, that’s where their mistress must be, that’s where they go to drink a lot.’”
This is potentially an issue with open-data initiatives such as those currently under way in Bristol and Manchester, which is making publicly available the data it holds about city parking, procurement and planning, public toilets and the fire service. The democratic motivation of this strand of smart-city thinking seems unimpugnable: the creation of municipal datasets is funded by taxes on citizens, so citizens ought to have the right to use them. When presented in the right way – “curated”, if you will, by the city itself, with a sense of local character – such information can help to bring “place back into the digital world”, says Mike Rawlinson of consultancy City ID, which is working with Bristol on such plans.
But how safe is open data? It has already been demonstrated, for instance, that the openly accessible data of London’s cycle-hire scheme can be used to track individual cyclists. “There is the potential to see it all as Big Brother,” Rawlinson says. “If you’re releasing data and people are reusing it, under what purpose and authorship are they doing so?” There needs, Hill says, to be a “reframed social contract”.
The interface of Simudyne’s City Hospital EvacSim
Sometimes, at least, there are good reasons to track particular individuals. Simudyne’s hospital-evacuation model, for example, needs to be tied in to real data. “Those little people that you see [on screen], those are real people, that’s linking to the patient database,” Lyon explains – because, for example, “we need to be able to track this poor child that’s been burned.” But tracking everyone is a different matter: “There could well be a backlash of people wanting literally to go off-grid,” Rawlinson says. Disgruntled smart citizens, unite: you have nothing to lose but your phones.
In truth, competing visions of the smart city are proxies for competing visions of society, and in particular about who holds power in society. “In the end, the smart city will destroy democracy,” Hollis warns. “Like Google, they’ll have enough data not to have to ask you what you want.”
You sometimes see in the smart city’s prophets a kind of casual assumption that politics as we know it is over. One enthusiastic presenter at the Future Cities Summit went so far as to say, with a shrug: “Internet eats everything, and internet will eat government.” In another presentation, about a new kind of “autocatalytic paint” for street furniture that “eats” noxious pollutants such as nitrous oxide, an engineer in a video clip complained: “No one really owns pollution as a problem.” Except that national and local governments do already own pollution as a problem, and have the power to tax and regulate it. Replacing them with smart paint ain’t necessarily the smartest thing to do.
And while some tech-boosters celebrate the power of companies such as Über – the smartphone-based unlicensed-taxi service now banned in Spain and New Delhi, and being sued in several US states – to “disrupt” existing transport infrastructure, Hill asks reasonably: “That Californian ideology that underlies that user experience, should it really be copy-pasted all over the world? Let’s not throw away the idea of universal service that Transport for London adheres to.”
Perhaps the smartest of smart city projects needn’t depend exclusively – or even at all – on sensors and computers. At Future Cities, Julia Alexander of Siemens nominated as one of the “smartest” cities in the world the once-notorious Medellin in Colombia, site of innumerable gang murders a few decades ago. Its problem favelas were reintegrated into the city not with smartphones but with publicly funded sports facilities and a cable car connecting them to the city. “All of a sudden,” Alexander said, “you’ve got communities interacting” in a way they never had before. Last year, Medellin – now the oft-cited poster child for “social urbanism” – was named the most innovative city in the world by the Urban Land Institute.
One sceptical observer of many presentations at the Future Cities Summit, Jonathan Rez of the University of New South Wales, suggests that “a smarter way” to build cities “might be for architects and urban planners to have psychologists and ethnographers on the team.” That would certainly be one way to acquire a better understanding of what technologists call the “end user” – in this case, the citizen. After all, as one of the tribunes asks the crowd in Shakespeare’s Coriolanus: “What is the city but the people?”
"Computing has always been personal. By this I mean that if you weren't intensely involved in it, sometimes with every fiber in your body, you weren't doing computers, you were just a user."
Note: while I'm rather against too much security (therefore, not "Imposing security") and probably reticent to the fact that we, as human beings, are "delegating" too far our daily routines and actions to algorithms (which we wrote), this article stresses the importance of code in our everyday life as well as the fact that it goes down to the language which is used to code a program. Interesting to know that some coding languages are more likely to produce mistakes and errors.
Three computer bugs this year exposed passwords, e-mails, financial data, and other kinds of sensitive information connected to potentially billions of people. The flaws cropped up in different places—the software running on Web servers, iPhones, the Windows operating system—but they all had the same root cause: careless mistakes by programmers.
Each of these bugs—the “Heartbleed” bug in a program called OpenSSL, the “goto fail” bug in Apple’s operating systems, and a so-called “zero-day exploit” discovered in Microsoft’s Internet Explorer—was created years ago by programmers writing in C, a language known for its power, its expressiveness, and the ease with which it leads programmers to make all manner of errors. Using C to write critical Internet software is like using a spring-loaded razor to open boxes—it’s really cool until you slice your fingers.
Alas, as dangerous as it is, we won’t eliminate C anytime soon—programs written in C and the related language C++ make up a large portion of the software that powers the Internet. New projects are being started in these languages all the time by programmers who think they need C’s speed and think they’re good enough to avoid C’s traps and pitfalls.
But even if we can’t get rid of that language, we can force those who use it to do a better job. We would borrow a concept used every day in the physical world.
Obvious in retrospect
Of the three flaws, Heartbleed was by far the most significant. It is a bug in a program that implements a protocol called Secure Sockets Layer/Transport Layer Security (SSL/TLS), which is the fundamental encryption method used to protect the vast majority of the financial, medical, and personal information sent over the Internet. The original SSL protocol made Internet commerce possible back in the 1990s. OpenSSL is an open-source implementation of SSL/TLS that’s been around nearly as long. The program has steadily grown and been extended over the years.
Today’s cryptographic protocols are thought to be so strong that there is, in practice, no way to break them. But Heartbleed made SSL’s encryption irrelevant. Using Heartbleed, an attacker anywhere on the Internet could reach into the heart of a Web server’s memory and rip out a little piece of private data. The name doesn’t come from this metaphor but from the fact that Heartbleed is a flaw in the “heartbeat” protocol Web browsers can use to tell Web servers that they are still connected. Essentially, the attacker could ping Web servers in a way that not only confirmed the connection but also got them to spill some of their contents. It’s like being able to check into a hotel that occasionally forgets to empty its rooms’ trash cans between guests. Sometimes these contain highly valuable information.
Heartbleed resulted from a combination of factors, including a mistake made by a volunteer working on the OpenSSL program when he implemented the heartbeat protocol. Although any of the mistakes could have happened if OpenSSL had been written in a modern programming language like Java or C#, they were more likely to happen because OpenSSL was written in C.
Many developers design their own reliability tests and then run the tests themselves. Even in large companies, code that seems to work properly is frequently not tested for lurking flaws.
Apple’s flaw came about because some programmer inadvertently duplicated a line of code that, appropriately, read “goto fail.” The result was that under some conditions, iPhones and Macs would silently ignore errors that might occur when trying to ascertain the legitimacy of a website. With knowledge of this bug, an attacker could set up a wireless access point that might intercept Internet communications between iPhone users and their banks, silently steal usernames and passwords, and then reëncrypt the communications and send them on their merry way. This is called a “man-in-the-middle” attack, and it’s the very sort of thing that SSL/TLS was designed to prevent.
Remarkably, “goto fail” happened because of a feature in the C programming language that was known to be problematic before C was even invented! The “goto” statement makes a computer program jump from one place to another. Although such statements are common inside the computer’s machine code, computer scientists have tried for more than 40 years to avoid using “goto” statements in programs that they write in so-called “high-level language.” Java (designed in the early 1990s) doesn’t have a “goto” statement, but C (designed in the early 1970s) does. Although the Apple programmer responsible for the “goto fail” problem could have made a similar mistake without using the “goto” statement, it would have been much less probable.
We know less about the third bug because the underlying source code, part of Microsoft’s Internet Explorer, hasn’t been released. What we do know is that it was a “use after free” error: the program tells the operating system that it is finished using a piece of memory, and then it goes ahead and uses that memory again. According to the security firm FireEye, which tracked down the bug after hackers started using it against high-value targets, the flaw had been in Internet Explorer since August 2001 and affected more than half of those who got on the Web through traditional PCs. The bug was so significant that the Department of Homeland Security took the unusual step of telling people to temporarily stop running Internet Explorer. (Microsoft released a patch for the bug on May 1.)
Automated inspectors
There will always be problems in anything designed or built by humans, of course. That’s why we have policies in the physical world to minimize the chance for errors to occur and procedures designed to catch the mistakes that slip through.
Home builders must follow building codes, which regulate which construction materials can be used and govern certain aspects of the building’s layout—for example, hallways must reach a minimum width, and fire exits are required. Building inspectors visit the site throughout construction to review the work and make sure that it meets the codes. Inspectors will make contractors open up walls if they’ve installed them before getting the work inside inspected.
The world of software development is completely different. It’s common for developers to choose the language they write in and the tools they use. Many developers design their own reliability tests and then run the tests themselves! Big companies can afford separate quality–assurance teams, but many small firms go without. Even in large companies, code that seems to work properly is frequently not tested for lurking security flaws, because manual testing by other humans is incredibly expensive—sometimes more expensive than writing the original software, given that testing can reveal problems the developers then have to fix. Such flaws are sometimes called “technical debt,” since they are engineering costs borrowed against the future in the interest of shipping code now.
The solution is to establish software building codes and enforce those codes with an army of unpaid inspectors.
Crucially, those unpaid inspectors should not be people, or at least not only people. Some advocates of open-source software subscribe to the “many eyes” theory of software development: that if a piece of code is looked at by enough people, the security vulnerabilities will be found. Unfortunately, Heartbleed shows the fallacy in this argument: though OpenSSL is one of the most widely used open-source security programs, it took paid security engineers at Google and the Finnish IT security firm Codenomicon to find the bug—and they didn’t find it until two years after many eyes on the Internet first got access to the code.
Instead, this army of software building inspectors should be software development tools—the programs that developers use to create programs. These tools can needle, prod, and cajole programmers to do the right thing.
This has happened before. For example, back in 1988 the primary infection vector for the world’s first Internet worm was another program written in C. It used a function called “gets()” that was common at the time but is inherently insecure. After the worm was unleashed, the engineers who maintained the core libraries of the Unix operating system (which is now used by Linux and Mac OS) modified the gets() function to make it print the message “Warning: this program uses gets(), which is unsafe.” Soon afterward, developers everywhere removed gets() from their programs.
The same sort of approach can be used to prevent future bugs. Today many software development tools can analyze programs and warn of stylistic sloppiness (such as the use of a “goto” statement), memory bugs (such as the “use after free” flaw), or code that doesn’t follow established good-programming standards. Often, though, such warnings are disabled by default because many of them can be merely annoying: they require that code be rewritten and cleaned up with no corresponding improvement in security. Other bug–finding tools aren’t even included in standard development tool sets but must instead be separately downloaded, installed, and run. As a result, many developers don’t even know about them, let alone use them.
To make the Internet safer, the most stringent checking will need to be enabled by default. This will cause programmers to write better code from the beginning. And because program analysis tools work better with modern languages like C# and Java and less well with programs written in C, programmers should avoid starting new projects in C or C++—just as it is unwise to start construction projects using old-fashioned building materials and techniques.
Programmers are only human, and everybody makes mistakes. Software companies need to accept this fact and make bugs easier to prevent.
Simson L. Garfinkel is a contributing editor to MIT Technology Review and a professor of computer science at the Naval Postgraduate School.
The third workshop we ran in the frame ofI&ICwith our guest researcherMatthew Plummer-Fernandez (Goldsmiths University) and the 2nd & 3rd year students (Ba) inMedia & Interaction Design (ECAL) ended last Friday (| rblg note: on the 21st of Nov.) with interesting results. The workshop focused on small situated computing technologies that could collect, aggregate and/or “manipulate” data in automated ways (bots) and which would certainly need to heavily rely on cloud technologies due to their low storage and computing capacities. So to say “networked data objects” that will soon become very common, thanks to cheap new small computing devices (i.e. Raspberry Pis for diy applications) or sensors (i.e. Arduino, etc.) The title of the workshop was “Botcave”, which objective was explained by Matthewin a previous post.
The choice of this context of work was defined accordingly to our overall research objective, even though we knew that it wouldn’t address directly the “cloud computing” apparatus — something we learned to be a difficult approachduring the second workshop –, but that it would nonetheless question its interfaces and the way we experience the whole service. Especially the evolution of this apparatus through new types of everyday interactions and data generation.
Matthew Plummer-Fernandez (#Algopop) during the final presentation at the end of the research workshop.
Through this workshop, Matthew and the students definitely raised the following points and questions:
1° Small situated technologies that will soon spread everywhere will become heavy users of cloud based computing and data storage, as they have low storage and computing capacities. While they might just use and manipulate existing data (like some of the workshop projects — i.e. #Good vs. #Evil or Moody Printer) they will altogether and mainly also contribute to produce extra large additional quantities of them (i.e. Robinson Miner). Yet, the amount of meaningful data to be “pushed” and “treated” in the cloud remains a big question mark, as there will be (too) huge amounts of such data –Lucien will probably post something later about this subject: “fog computing“–, this might end up with the need for interdisciplinary teams to rethink cloud architectures.
2° Stored data are becoming “alive” or significant only when “manipulated”. It can be done by “analog users” of course, but in general it is now rather operated by rules and algorithms of different sorts (in the frame of this workshop: automated bots). Are these rules “situated” as well and possibly context aware (context intelligent) –i.e.Robinson Miner? Or are they somehow more abstract and located anywhere in the cloud? Both?
3° These “Networked Data Objects” (and soon “Network Data Everything”) will contribute to “babelize” users interactions and interfaces in all directions, paving the way for new types of combinations and experiences (creolization processes) — i.e. The Beast, The Like Hotline, Simon Coins, The Wifi Cracker could be considered as starting phases of such processes–. Cloud interfaces and computing will then become everyday “things” and when at “house”, new domestic objects with which we’ll have totally different interactions (this last point must still be discussed though as domesticity might not exist anymore according to Space Caviar).
Moody Printer – (Alexia Léchot, Benjamin Botros)
Moody Printer remains a basic conceptual proposal at this stage, where a hacked printer, connected to a Raspberry Pi that stays hidden (it would be located inside the printer), has access to weather information. Similarly to human beings, its “mood” can be affected by such inputs following some basic rules (good – bad, hot – cold, sunny – cloudy -rainy, etc.) The automated process then search for Google images according to its defined “mood” (direct link between “mood”, weather conditions and exhaustive list of words) and then autonomously start to print them.
A different kind of printer combined with weather monitoring.
The Beast – (Nicolas Nahornyj)
Top: Nicolas Nahornyj is presenting his project to the assembly. Bottom: the laptop and “the beast”.
The Beast is a device that asks to be fed with money at random times… It is your new laptop companion. To calm it down for a while, you must insert a coin in the slot provided for that purpose. If you don’t comply, not only will it continue to ask for money in a more frequent basis, but it will also randomly pick up an image that lie around on your hard drive, post it on a popular social network (i.e. Facebook, Pinterest, etc.) and then erase this image on your local disk. Slowly, The Beast will remove all images from your hard drive and post them online…
A different kind of slot machine combined with private files stealing.
Robinson – (Anne-Sophie Bazard, Jonas Lacôte, Pierre-Xavier Puissant)
Top: Pierre-Xavier Puissant is looking at the autonomous “minecrafting” of his bot. Bottom: the proposed bot container that take on the idea of cubic construction. It could be placed in your garden, in one of your room, then in your fridge, etc.
Robinsonautomates the procedural construction of MineCraft environments. To do so, the bot uses local weather information that is monitored by a weather sensor located inside the cubic box, attached to a Raspberry Pi located within the box as well. This sensor is looking for changes in temperature, humidity, etc. that then serve to change the building blocks and rules of constructions inside MineCraft (put your cube inside your fridge and it will start to build icy blocks, put it in a wet environment and it will construct with grass, etc.)
A different kind of thermometer combined with a construction game.
Note: Matthew Plummer-Fernandez also produced two (auto)MineCraft bots during the week of workshop. The first one is building environment according to fluctuations in the course of different market indexes while the second one is trying to build “shapes” to escape this first envirnment. These two bots are downloadable from theGithub repository that was realized during the workshop.
#Good vs. #Evil – (Maxime Castelli)
Top: a transformed car racing game. Bottom: a race is going on between two Twitter hashtags, materialized by two cars.
#Good vs. #Evil is a quite straightforward project. It is also a hack of an existing two racing cars game. Yet in this case, the bot is counting iterations of two hashtags on Twitter: #Good and #Evil. At each new iteration of one or the other word, the device gives an electric input to its associated car. The result is a slow and perpetual race car between “good” and “evil” through their online hashtags iterations.
A different kind of data visualization combined with racing cars.
The “Like” Hotline – (Mylène Dreyer, Caroline Buttet, Guillaume Cerdeira)
Top: Caroline Buttet and Mylène Dreyer are explaining their project. The screen of the laptop, which is a Facebook account is beamed on the left outer part of the image. Bottom: Caroline Buttet is using a hacked phone to “like” pages.
The “Like” Hotline is proposing to hack a regular phone and install a hotline bot on it. Connected to its online Facebook account that follows a few personalities and the posts they are making, the bot ask questions to the interlocutor which can then be answered by using the keypad on the phone. After navigating through a few choices, the bot hotline help you like a post on the social network.
A different kind of hotline combined with a social network.
Simoncoin – (Romain Cazier)
Top: Romain Cazier introducing its “coin” project. Bottom: the device combines an old “Simon” memory game with the production of digital coins.
Simoncoin was unfortunately not finished at the end of the week of workshop but was thought out in force details that would be too long to explain in this short presentation. Yet the main idea was to use the game logic of Simon to generate coins. In a parallel to the Bitcoins that are harder and harder to mill, Simon Coins are also more and more difficult to generate due to the game logic.
Another different kind of money combined with a memory game.
The Wifi Cracker – (Bastien Girshig, Martin Hertig)
Top: Bastien Girshig and Martin Hertig (left of Matthew Plummer-Fernandez) presenting. Middle and Bottom: the wifi password cracker slowly diplays the letters of the wifi password.
The Wifi Cracker is an object that you can independently leave in a space. It furtively looks a little bit like a clock, but it won’t display the time. Instead, it will look for available wifi networks in the area and start try to find their protected password (Bastien and Martin found a ready made process for that). The bot will test all possible combinations and it will take time. Once the device will have found the working password, it will use its round display to transmit the password. Letter by letter and slowly as well.
A different kind of cookoo clock combined with a password cracker.
Acknowledgments:
Lots of thanks to Matthew Plummer-Fernandez for its involvement and great workshop direction; Lucien Langton for its involvment, technical digging into Raspberry Pis, pictures and documentation; Nicolas Nova and Charles Chalas (from HEAD) so as Christophe Guignard, Christian Babski and Alain Bellet for taking part or helping during the final presentation. A special thanks to the students from ECAL involved in the project and the energy they’ve put into it: Anne-Sophie Bazard, Benjamin Botros, Maxime Castelli, Romain Cazier, Guillaume Cerdeira, Mylène Dreyer, Bastien Girshig, Jonas Lacôte, Alexia Léchot, Nicolas Nahornyj, Pierre-Xavier Puissant.
From left to right: Bastien Girshig, Martin Hertig (The Wifi Cracker project), Nicolas Nova, Matthew Plummer-Fernandez (#Algopop), a “mystery girl”, Christian Babski (in the background), Patrick Keller, Sebastian Vargas, Pierre Xavier-Puissant (Robinson Miner), Alain Bellet and Lucien Langton (taking the pictures…) during the final presentation on Friday.
Note: will the term "architect" be definitely overtaken by computer scientists? (rather the term "urbanist" in fact in this precise case, but still...). Will our environments be fully controlled by protocols, data sensing, bots and algorithms? Possibly... but who will design them? It makes me think that at one point, the music industry didn't think that their business would change so dramatically. We all know what happened but the good news is: we still need musicians!
So, I probably believe that architects and the schools that form them should look carefully to what is about to happen (the now already famous -- but still to come -- "Internet of Everything"). New actors (in the building industry) are pushing hard for their place in this "still to come" field that include the construction, monitoring and control of cities, territories, buildings, houses, ... (IBM, Cisco, Google, Apple, etc.). Their hidden lines of code will become much more significant for the life of urban citizens (because of their increasing impact on "the way life goes") than any "new" 3d shape you can possibly imagine. Shape is over, code is coming in a street near you!
As if self-driving cars, balloon-carried internet, or the eradication of death weren't ambitious enough projects, Google CEO Larry Page has apparently been working behind the scenes to set up even bolder tasks for his company. The Information reports that Page started up a Google 2.0 project inside the company a year ago to look at the big challenges facing humanity and the ways Google can overcome them. Among the grand-scale plans discussed were Page's desire to build a more efficient airport as well as a model city. To progress these ideas to fruition, the Google chief has also apparently proposed a second research and development lab, called Google Y, to focus on even longer-term programs that the current Google X, which looks to support future technology and is headed up by his close ally Sergey Brin.
Note: it looks like many products we are using today were envisioned a long time ago (peak of expectations vs plateau)... back in the early years of personal computing (80ies). It funnily almost look like a lost utopian-future. Now that we are moving from personal computing to (personal) cloud computing (where personal must be framed into brackets, but should necessarily be a goal), we can possibly see how far personal computing was a utopian move rooted into the protest and experimental ideologies of the late 60ies and 70ies. So was the Internet in the mid 90ies. And now, what?
Apple's focus on design has long been one of the key factors that set its computers apart. Some of its earliest and most iconic designs, however, didn't actually come from inside of Apple, but from outside designers at Frog. In particular, credit goes to Frog's founder, Hartmut Esslinger, who was responsible for the "Snow White" design language that had Apple computers of the ’80s colored all white and covered in long stripes and rounded corners meant to make the machines appear smaller.
In fact, Esslinger goes so far as to say in his recent book, Keep it Simple, that he was the one who taught Steve Jobs to put design first. First published late last year, the book recounts Esslinger's famous collaboration with Jobs, and it includes amazing photos of some of the many, many prototypes to come out of it. They're incredibly wide ranging, from familiar-looking computers to bizarre tablets to an early phone and even a watch, of sorts.
This is far from the first time that Esslinger has shared early concepts from Apple, but these show not only a variety of styles for computers but also a variety of forms for them. Some of the mockups still look sleek and stylish today, but few resemble the reality of the tablets, laptops, and phones that Apple would actually come to make two decades later, after Jobs' return. You can see more than a dozen of these early concepts below, and even more are on display in Esslinger's book.
Computers dethrone humans in European stock trading - via reuters
European equity investors are placing more orders via computers than through human traders for the first time as new market rules drive more money managers to go high-tech and low cost. The widespread regulatory changes has made electronic trading spread across the industry.
Last year, European investors put 51 percent of their orders through computers directly connected to the stock exchange or by using algorithms, a study by consultants TABB showed. The TABB study revealed that of 58 fund managers controlling 14.6 trillion euros in assets, a majority intended to funnel much more of their business through electronic “low touch” channels, which can cut trade costs by two-thirds. Pioneer Investments, which trades 500 billion euros ($695 billion) worth of assets every year and has cut the number of brokers it uses from 300 to around 100. Thats a lot of money in the non-hands of algorithms.
This blog is the survey website of fabric | ch - studio for architecture, interaction and research.
We curate and reblog articles, researches, writings, exhibitions and projects that we notice and find interesting during our everyday practice and readings.
Most articles concern the intertwined fields of architecture, territory, art, interaction design, thinking and science. From time to time, we also publish documentation about our own work and research, immersed among these related resources and inspirations.
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