Killer Bee Invasion is a satirical series written by David A Banks and Britney Summit-Gil that explores the way news media outlets cover major events. (Read Part 1)
Poughkeepsie – A rift has opened up approximately 80 miles north of New York City, the Times has learned. According to reports from the Poughkeepsie Journal and eyewitnesses in the area, a disturbance described by some as a “shimmer” formed, followed by a deep black spot in the northern sky. It is from this black spot that the bees, which are estimated to be between 10 to 12 feet long, have emerged.
Previous reports claimed that the bees were “ten to twelve feet in height, including black, shining stingers around two feet long.” New observations by National Guard officers now indicate that the bees are ten to twelve feet in height from head to thorax, with their massive gleaming stingers adding an additional two feet to their overall length.
Lieutenant Colonel Stephen P. Grianno of the United States Air Force leads the squadron dispatched to the rift. “As of right now we are working with intelligence agencies and reaching out to exobiologists for help in ascertaining the threat these bee-like creatures pose to Americans,” he said over the phone.
He added, “Right now we are taking a wait and see approach.”
As of 4:00PM Saturday the death toll is estimated to be 200, but local officials suspect more deaths have occurred. One city official, who spoke on condition of anonymity because they were not authorized to speak publicly, stated that “many more, perhaps thousands” of people have been killed by the bee creatures.
The city official added, “I mean just look at the things. Who knows if they leave anything behind once they sting you.”
Exobiologists are concerned that humans may be unintentionally taunting the other-worldly visitors by wearing bright colors and standing in what Dr. Emmerson Schafenham calls a, “flower-like stance, with a slight swaying as if you are a delicate pistil growing out of a strong stem.” A pistil is the central structure of the flower that receives pollen.
“These bees may come from a place where flowers are mammal-like creatures that must be caught and injected, unlike the more passive process that terrestrial bees use to pollenate plants.” He alternatively suggested that stingers may be used as a means of communication or greeting in the bees’ native culture. “We know little about their social structure, and these stingers may have a variety of uses beyond killing.” Mr. Schafenham also added, “There’s no playbook for this.”
Other researchers are more confident in their assessment of the creatures, some going so far as to name and classify the creatures. University of Wisconsin biologist Dr. Carol Frasche and her team has already begun a naming convention: “We are suggesting a parallel phylogeny wherein anything that comes through the rift be appended with an alt- prefix to designate what we believe are their alternative universe origins.”
The scientific name for the giant honey bee is apis dorsata and so Ms. Frasche and her team have taken to naming the aliens alt-apis. They stop short, however, of being more specific. “We have not observed honey-producing behavior so we cannot classify them as dorsata which is reserved for honey-producing species of the genus.”
Alt-apis may quickly become the preferred nomenclature as behavioral scientists such as Dr. Karl Masctrich of the University of Chicago note that calling these creatures “giant killer bees” may be a self-fulfilling prophesy. “By approaching them as natural-born killers we may be ignoring their ability to communicate and even empathize.”
He went on to add, “We really need to understand alt-apis before we rush to judgement. What has transpired so far may be nothing more than a very bad first impression. We have to understand the hardships these creatures went through and why they felt the need to rip a hole in space-time and invade our planet.”
Lt. Colonel Grianno seems to agree, “I took an oath to protect this nation from enemies foreign and domestic but first we have to be sure they are an enemy. Right now all we can say for certain is that they seem angry.”
If you’ve been keeping up with the latest advancements in technology, you’ve probably heard the news that self-driving or autonomous cars are taking over the roads. While major companies like Uber, Google, Tesla, Nissan and more are jumping head first into developing cars capable of driving themselves, the public remains a bit hesitant.
The uncertainty that many people feel about autonomous vehicles isn’t unwarranted. From fear of losing jobs to safety concerns, many people are wondering if self-driving cars are really the right way to go.
With the invention of the car came the invention of the car accident. Soon after the Model T took over America’s roads, car-related fatalities soared to nearly 20,000 a year and have remained within a few thousand ever since. When drivers are distracted, accidents are bound to happen. Handing over the steering wheel to a computer, according to tech companies, may be a way to finally reduce the five-figure annual death tolls.
Not even those companies selling self-driving vehicles are arguing that driving deaths will be totally eliminated. Mistakes can happen with both humans and computers; it’s fair to wonder how autonomous cars will respond to unexpected scenarios.
The problem here is that when you get in your car and need to avoid an accident, you react to the situation at hand. If you were in completely self-driving car, the situation requires the car to make a decision. A decision requires forethought. This leads the ethical dilemma surrounding self-driving cars. Cars could soon choose between hitting a bystander, taking the brunt of the blow (potentially risking the lives of it’s passengers) or sacrificing the few in favor of saving the majority, also known as the Trolley Problem.
Autonomous cars also pose the question of who would be responsible for an accident? Will the owner of the vehicle be to blame if something goes wrong, or does the manufacturer take the fault? The answer to this question will differ, depending on the degree of automation.
The National Highway Traffic Safety Administration recently released a set of standards that each self-driving vehicle must adhere to. These rules and regulations differ depending on where the vehicle falls on the automated driving system scale, with Level 0 being a standard car where a human is entirely in control and Level 5 indicating that the vehicle is completely driverless, even in extreme conditions.
With minimal autonomous features like cruise control or power steering, most of our driving experiences stay around a Level 1 or a Level 2. At these levels, the driver is still in charge of the majority of the vehicle’s functions. However, the new self-driving vehicles being developed are at a Level 3 or a Level 4. Unfortunately, many people operate their Level 1 or 2 car like it is a Level 3 or 4 car. One needs only to turn to YouTube to find proof of people ignoring the road while behind the wheel.
Human drivers aren’t perfect, but neither are human programmers and engineers. Automating something as complex as driving will never be perfect. Thinking through the ethics and accountability scenarios for self-driving cars should keep pace with technological development. Are we really ready to put our safety in the same hands as companies who struggle to create cell phones, apps, and programs that don’t malfunction? With so much hesitation around self-driving vehicles, we may be better off if they don’t get rolled out at all. However, we know that won’t be the case.
Most people though, remain suspicious about the helpfulness of self-driving cars. “The handoff” from the computer to a human driver can be a dangerous few seconds. If you’re traveling down the highway at 55mph and your car alerts you, how quickly can you take the wheel in an emergency situation?
As you read that last sentence, did you think of a response? In that time you’ve lost precious seconds. If you do that while driving the problem compounds itself. While you may think it’s no big deal, remember it only takes 4.6 seconds at 55 miles an hour to travel the length of a football field. Your reaction would have been immediate in a regular car. While you think this could lead to the demise of the autonomous car, it will actually create a push for more advanced Level 5 cars.
As most of America warms to the idea of letting algorithms take the wheel, there remains a sizeable portion of Americans who have good reason to resist autonomous vehicles. People who drive for a living — from taxies to semi-trucks — are worried what this could mean for their jobs. With the introduction of self-driving trucks that can eliminate the restrictions surrounding human drivers, truck drivers fear that their jobs may be replaced.
Cab drivers and Uber drivers also worry they will find themselves out of a job if autonomous vehicles really begin taking off. Uber is already expanding their self-driving fleet to other cities. It’s only a matter of time before unemployment becomes the unfortunate reality for taxi and truck drivers.
The fact of the matter is, humans aren’t perfect. The irony is, some people think that an autonomous car, programmed by a human, will perform correctly 100% of the time. There will always be a margin of error. With the ethical dilemmas and job loss surrounding these vehicles, are they really the road to the future we want to travel?
Megan Ray Nichols is a freelance science writer. She’s a regular contributor to Datafloq and The Energy Collective. Megan also writes weekly on her personal blog Schooled By Science where she discusses the latest news in science and technology. Subscribe to her blog for the latest news and follow her on Twitter, @nicholsrmegan, to join the discussion.
Much of the post-election analysis has focused on strategic fixes–what should have been done. But what can Trump’s win tell us about more fundamental theories of politics? In what way does the failure of an alliance based on labor, environmentalists and civil rights activists give us clues about our basic social power concepts?
Those three categories are fairly clear voting blocks (consider, for example, the very different constituencies that the AFL-CIO, Sierra Club, and Black Lives Matter represent), but they are also broad theory categories. Marxist theory predicts that working class voters will struggle to find a way to understand and represent their interests; environmentalists interrogate Western views of “dominion over nature”; and race theorists confront the structures of white supremacy. None of these theoretical projects occurred in a vacuum and there has been lots of good intersectional work across all three. But when it comes to praxis, history has lots of examples where these movements were pitted against each other or were incompatible from the start. Think of the 1930s labor strikes when black scabs were brought in to break all-white unions; the 1970s white activists who abandoned civil rights to start “Earth First”; and the 1980s loggers who found themselves pitted against the spotted owl.
We are, admittedly, painting these complicated and old social movements with a very broad brush but there are critical moments today when these basic incompatibilities have resulted in direct and immediate consequences. When Hillary Clinton said she would “put coal miners … out of work” it was not a misstep, it was an honest (if inadvertent) admission of our failure to articulate a fundamental political theory; to paint a coherent vision from the contradictory pallet of blue collar labor, green environmentalists and black and brown rights advocates.
An attempt to create exactly that vision is at the core of Teknokultura’s new special issue on “generative justice”. Generative justice is defined as “the circulation of unalienated value, under control of those who generate it”. The idea came out of a six year NSF grant that brought together community organizers with humanities, science and engineering scholars in locations ranging from rural west Africa to New York’s inner cities. As we looked over the best outcomes—a DIY condom vending machine, math lessons using fractals in cornrow braiding, solar ink production for local weavers—a common pattern began to emerge. In every case that counted as success—where the underserved communities we worked with were able to access or build something that improved their material conditions—there was a very direct connection between labor and its rewards, or, what Marx would have called “unalienated value.” But our successes (and our many failures) did not center on labor value alone: there was also a lot of value that non-human allies in nature were producing, and a third category that was more about “expression”: unalienated sexuality, free speech, spirituality and the like. Unlike Marx’s ideal in which value was extracted and centralized before redistribution, these forms of value remained in unalienated form and circulated in a commons. It was a kind of justice from the bottom-up: if those who generate value stay in control, they can share the fruits of their physical, ecological, and expressive activities in a kind of gift economy of reciprocity and commons-based production.
Many of these successes were innovations rather than inventions. Condom vending machines have existed for a long time, but with a bit of help from computer-aided design and rapid prototyping, we ended up with a DIY machine that can be made using tools and parts commonly available in West Africa. Rather than requiring mass production in a high tech factory, this would keep the financial value in the community of use, and also help sustain local artisanal groups and traditions. Back in the US we made a similar move using simulations of African American cornrow hairstyles for math and computing education. In contrast to the vending machine’s focus on keeping labor value local, circulating these “heritage algorithms” was about the expressive value of black cultural tradition, which made for less alienating STEM lessons in inner city classrooms. Some of those students have started to create 3D printed versions of their work (image above), and two of the hairstylists have offered to display them in their shops to see if this can bring in more customers, and our engineering students are working on a switch to recycled plastic. AI and robotics is generally about replacing workers and deskilling jobs, but a generative approach to STEM can use these technologies to amplify the abilities of artisanal labor, expand access to cultural expression and improve ecological sustainability.
How does all that apply to Trump’s election and destructive mismatch between labor, environment and civil rights? One of the Democrats’ greatest errors was promising that lost manufacturing jobs would be replaced by skilled labor in the tech sector or renewable energy in some soon-to-be-realized shiny future. None of the latinos laid off from Texas oil fields, white equipment installers without jobs in Indiana, or black auto workers replaced by the most recent wave of automation could see how this was going to get them a job next week. At best, it’s a promise that their children might get that education, but those sorts of promises have been broken more times than kept.
Generative justice, in contrast, gets at the fundamental issue at stake: unalienated labor means being in charge of the production process and seeing it directly benefit those around you. Building a political campaign with generative justice in mind actually has precedence. There are lots of real-world models for the sorts of value circulation that we call generative justice, but they are rarely gathered together under a coherent social analysis. Take for example the workers’ council movement in Czechoslovakiaprior to the Soviet invasion of 1968. There were councils in 120 enterprises, for a total of about 800,000 employees–almost 1/6th of the national workforce who had a say in how labor was paced, managed and even what products were produced. These organizations ran much like a modern capitalist corporations but management and executive positions were democratically selected by and amongst workers. Each enterprise was independent, but interrelated, often inviting workers to sit as external members on hiring committees.
Such an arrangement does not neatly fit into state-controlled communism or capitalism. It derives worker protections, product quality standards, and other social welfare concerns from contracts and agreements between democratic bodies, not from government bureaucracies. Workers’ councils, like all practices that illustrate the generative justice concept —open source software, indigenous gift economies, commons-based land management, and so on— are best understood as lying on an axis which runs orthogonal to the conventional right/left political spectrum of state-protected capitalist or communist politics.
The same holds for the other two categories, unalienated ecological value and unalienated expressive value. Once you catch the fundamental concept of generative justice then any scheme for extraction becomes suspect, whether private enterprise, state bureaucracy, or other institutional domination. Trump’s scheme to help oil companies alienate value from nature runs in parallel to his plans to help homophobic institutions like the American Family Association alienate citizens from their own spiritual, sexual and cultural identities. But the record for protecting labor, the environment and civil rights is no better for socialist bureaucracies than it is for market economies. And “mixed” economies like the People’s Republic of China are no recipe for justice either.
So what does work in driving social structures closer to the ideal of generative justice? One of the common themes that shows up in the Teknokultura special issue is the importance of grassroots organizations that combined a social agenda with activities of “making”. Unlike political movements that aim for changes through policy or legislation, these groups make democratic action a part of mixing labor and raw resources into finished artifacts. To be clear generative justice is not only about making things, but some of its best illustrations are found in cases where unalienated value circulation is a deliberate expression of both politics and physical production.
Take for example open source software, maker spaces and other DIY-oriented sharing collectives. As several articles in the issue note, there are plenty of great generative justice exemplars in that category, ranging from Liberating Ourselves Locally(a “people-of-color-led, gender-diverse, queer and trans inclusive hacker/maker space in East Oakland”) to vast international enterprises like MakerHealth that allows nurses and others to create their own health care innovations. But none of these collectives happened through some kind of Adam Smith style “invisible hand” of self-interested competition. Rather they are all examples of a kind of hybrid between old fashioned grassroots organizing and new technologies of sharing (code, blue prints etc. shared via creative commons, github, instructables and other platforms).
Imagine, then, a political platform based not on asking “how will American workers compete against those in Asia” or “how will we defeat the coal lobby” but rather “how will value be returned to all workers? How will the ecological value created by non-humans be returned to them, sustaining their soil, water, air and biodiversity? And how will the shy, ineluctable aspects of our being–spiritual or atheist, gay or straight, artist or logician–be similarly circulated to nurture communities of our choosing?” We hope readers will take a look at the special issue and join this conversation.
Ron Eglash received his B.S. in Cybernetics, his M.S. in Systems Engineering, and his PhD in History of Consciousness, all from the University of California. His work includes the book African Fractals, and the online Culturally Situated Design Tools suite. He is currently a Professor of Science and Technology Studies at Rensselaer.
Last week The New Inquiry published an essay I wrote about science journalism podcasts syndicated on NPR. Shows like Radiolab, The TED Radio Hour, Hidden Brain, Invisibilia, Note to Self, and Freakonomics Radio, I argued, were more about wrapping pre-conceived notions in a veneer of data than changing minds or delivering new insights into long-standing problems. Worse yet, social and political issues that might be met with collective action are turned into wishy-washy “well isn’t that interesting” anecdotes:
Topics that might have once been subject to political debate or rhetorical argument–work demands, exposure to toxins, surveillance, the limits of love, even Marxian alienation–become apolitical subjects for scientific testing. But the results only lead to greater and greater complexity, prompting introspective thought rather than action.
If anyone acts at all on what they hear in NPR podcasts it is either as a means of self-help or, as I wrote in the essay, “in the register of the heroic … by well-resourced individuals who seek to make dramatic moves because most others cannot, supposedly, see the whole picture.” I would like to pick up where I left off and describe two particularly stark examples of self-help and heroics. I think the two, juxtaposed as they are, demonstrate exactly what kind of world liberal infotainment seeks to engender.
I had some good things to say about Freakonomics Radio in the essay. Because the show is mostly about economics (I say mostly because there was one pledge drive episode where, and I am not kidding, they did not talk about economics at all and instead interviewed a neuroscientist that studies fMRI scans of people as they listen to podcasts.) the episodes mostly focus on what happens “in between” individuals and how the aggregate of human behavior cannot always be found in individual cognition. They do, however, make a point of encouraging listeners to apply theories meant for corporations and governments, to their daily lives. People gush about how the application of abstract economic theories on their bathroom routines or training regimens has resulted in huge gains in productivity and happiness. It is the kind of relief that can only come after a steady diet of equivocality suddenly and selectively provides a path forward.
In one such episode (the same one with the fMRI scans of podcast listeners) they talk to a young man who dreamed of being on they Olympic rowing team, only to come up short. On his way home from the training camp, feeling dejected, he looked for a radio show that would take his mind off of thing and, sitting there in the top 10 podcasts on iTunes, was Freakonomics Radio. From the transcript:
It was a very small segment of the podcast. I think it was like five minutes where it talked about Marine, Army Rangers, I believe. And how to get leaders out of them, they didn’t say, “You’re a natural leader,” or something like that. They said, “You’re hard-working and your success is built off hard work and not talent or not how a natural leader you are.”
The host, Stephen Dubner replies: “It sounds like you were a hard worker, but if I’m reading you correctly it sounds like you’re saying even though you worked hard, a) you could work harder and b) you could work more strategically or engage in what we call deliberate practice.” Deliberate practice is a term out of (surprise) psychology that says talent for a given activity comes out of a lot of “maximal effort” that is “generally not enjoyable.” (Quotes from here.)
The mundane point here is that practice makes perfect and that practice is often difficult but ultimately rewarding. Of course our rower probably already knew that, but it is the declarative power of science that makes such advice unavoidable. I had a professor in graduate school that once told my class, “Witch craft and astrophysics might both be equally true but only one is more likely to help you get to the moon.” The point he was making is that different kind of knowledge are good for different things and I think we can apply that to the case above. It is fine and good to hear a coach or someone you trust say, “it just takes more practice” but science has a way of telling you there is a single path to one’s goal. No matter how good you are, you can’t break the laws of nature (as described to you by a scientist) to get what you want. The only people who break the laws of nature are scientists themselves, and then they get rewarded with the Nobel Prize.
Now who does feel empowered to act on anything that isn’t themselves after listening to NPR podcasts are the incredibly rich. In an episode of Radiolab produced by the makers of Note to Self (brought to you in part by Goldman Sachs) the listener learns about the development of a high-powered camera technology that can scan entire cities to track cars and monitor people. Note to Self host Manoush Zomorodi and her colleague Alex Goldmark interview the inventor of the technology who wants to take his plane mounted camera from the battlefields of Iraq to the United States to fight crime. This technology, the episode promises, can track cars in real time providing detailed evidence for all sorts of major and minor crimes.
That episode aired in June 2015 and concluded with the technology getting stymied by elected officials and citizens who had serious privacy concerns. After describing the technology in heroic terms (the inventor is said to have a “super power”) and giving examples of how it brought killers to justice, Goldmark complains, “The advantages are so concrete and the dangers are nebulous.” They fret and lament that such a powerful technology for good is held up by reactionaries with “nebulous” concerns about big brother. They end on a sad note, saying this technology is being used for traffic monitoring and analysis.
Over a year later, in September 2016 they do a follow-up episode where they feign confusion at how their coverage convinced an ex Enron executive-turned-“philanthropist” John Arnold (along with his wife, Laura through their foundation) to singlehandedly bankroll a pilot study in Baltimore. Because the Arnolds are willing to bankroll the system there is no need for a public hearing or vote. Instead, the police chief signs a contract and the system is up and running. In addition to the city-wide photographs there are also the pre-existing CCTV cameras that can sync up with the aerial photography. The episode ends without a single self-reflective moment where Krulwich, Abumrad, Goldmark, or Zomorodi consider perhaps how they portrayed that technology would have attracted the interest of law and order-loving aristocrats.
I hope these further examples outline the stakes that we’re working with here. More than just bad traffic jam entertainment, these shows are widely listened to and inspire people to change their lives and the lives of others. Most importantly, NPR podcasts are a symptom of a much larger failure of political imagination. The fact that these shows are so popular indicates that they are maintaining hegemonic ideas rather than creating new ones, but if we are to truly face the issues current events demand, we are going to need a fundamental shift in how we approach problems of politics and science.
In a widely-shared article on The Intercept, Sam Biddle made the point that, “Trump’s anti-civil liberty agenda, half-baked and vague as it is, would largely be an engineering project, one that would almost certainly rely on some help from the private sector.” The center of his article, that of the six major tech companies he requested comments from only Twitter gave him an unequivocal statement that they would not help build a Muslim database, was chilling even though most of the companies just never responded. The role of engineers and designers in carrying out political ends often relegated to business’s policies. That is, engineers themselves are seen as completely beholden to whatever their bosses decide their job should be. I want to look at this from a different angle: why are engineers so willing to defer responsibility for their actions and why are they so often in positions to do so?
Simply put, border security doesn’t happen without engineers willing to build the walls or design the drones that make up that border. If, as the oft repeated Bruno Latour quote goes, technology is society made durable, we should be paying attention to (and putting a lot more pressure on) who is choosing which parts of social life persist without direct, constant human intervention. Making sure that companies behave ethically is one strategy but we should also look at how engineers themselves are trained to deal with morally dubious projects. Many of the academics who study engineering pedagogy and the accreditation bodies that oversee engineering programs have come to the conclusion that not only are engineers not given the necessary skills to navigate social and political conundrums, they are primed to follow orders regardless of their moral outcome.
Consider first, the disturbing fact that engineers are vastly overrepresented in extremist groups of all stripes: from neo-nazis to jihadists, engineering is the most common educational background of right-wing extremists. Diego Gambetta and Steffen Hertog, the authors of a book on the subject found that relative to their prevalence in any given nation, engineers are vastly over-represented in violent right-wing extremist groups. Left-wing extremist groups that advocate or support violent means, on the other hand, have no engineers amongst their ranks and are instead made up of people with backgrounds in the social sciences and humanities.
Gambetta and Hertog’s reasoning for this phenomenon is based in political psychology: both engineers and right-wing extremists put considerable emphasis on hierarchy, order, clear boundaries between categories, and unchanging conditions. The personalities that choose right-wing extremism and engineering overlap considerably. Of course, every engineer is not a nazi, but we should never lose site of the numerical fact that engineers were over-represented in nearly every right-wing revolution of the past century: from 1970s Iran to 1920s Germany. It is unclear from their book whether their discovery is due to self-selection into engineering and fundamentalist groups or if engineering pedagogy primes people to accept right-wing extremism. In other words, the jury is still out as to whether this is a matter of correlation or causation, but there is some evidence to support the latter.
Embedded not just in our existing gadgetry but in the very methods and processes that design and build new ones, are very specific ideological valences. This goes as far back as Newton’s Principia where the very foundations of calculus were laid out in such a way to be directly beneficial to engineers building warships. Engineering, as social scientists Dean Nieusma and Ethan Blue like to say, has always been a war-built discipline. From the sorts of organizations engineers are trained to work in (very hierarchical ones) to their professional ethics (the customer/employer/contractor is always right), they are taught unquestioning deference to authority and unremitting neutrality towards issues of political consequence.
Some who study engineering pedagogy and professional development make strong arguments for including peace and justice in college curriculums. Some have gone so far as to build an alternative “shadow code” for engineering departments willing to build social justice into their lessons. Education scholar Michael Lachney and I, in our contribution to this shadow code, have suggested that engineers become fluent in the differences between violence and property destruction.
Imagine if medical doctors, instead of taking the Hippocratic Oath that says, in part, “do no harm”, instead took an oath to never knowingly expose their employer to malpractice suits? No one, patients included, wants to be involved in malpractice but the change in allegiance should be clear: we want doctors to be first and foremost concerned with their patients’ well-being and their hosting institutions should be directed toward supporting that concern. Why should engineers be any different? Why are there no oaths to build things that cause harm to fellow humans? Why are there no licenses to be revoked if an engineer knowingly and consistently builds things that do great harm? These seem like common sense requests until you look at the major employers of engineering graduates: military contractors, resource extraction companies, and the governments that own those militaries and resources.
A new society needs a new kind of engineer. One who would recognize that designing a prison is not unlike designing a building with no foundation. Both are a kind of malpractice: building something that has been shown time and time again to produce bad outcomes. Engineers must understand their impact on society as well as they know Java or the tensile strength of concrete. That way, when they are told to build that wall or compile that database, they at least have a professional set of standards they can hold up as antithetical to their assigned project.
“The motor has killed the great city. The motor must save the great city.”
-Le Corbusier, 1924.
In the fast and shallow anxiety around driverless cars, there isn’t a lot of attention being paid to what driving in cities itself will become, and not just for drivers (of any kind of car) but also for pedestrians, governments, regulators and the law. This post is about the ‘relative geographies’ being produced by driverless cars, drones and big data technologies. Another way to think about this may be: what is the city when it is made for autonomous vehicles with artificial intelligence?
The question of planning cities in response to automobiles is not a new one. It was addressed through a number of architectural and urban planning visions in the 1920s-50s. Two of the most significant are Le Corbusier’s La Ville Radieuse (‘The Radiant City’), and the Plan Voisin/ Ville Contemporaine (Voisin was the car company that bankrolled this plan) for Paris. The former was never achieved, and the latter was more developed but also left incomplete. Corbusier’s Plan Voisin was founded on the belief that the centre of Paris was congested, dirty, and unable to support the deluge of motor cars of the early twentieth century. Plan Voisin/Ville Contemporaine would have involved uprooting and razing most of central Paris from Gare de l’est to Rue de Rivoli, and from Place de la Republique to Rue du Louvre. Le Corbusier’s solution, Ted Shelton writes here, “was to eliminate the infrastructure of the Parisian street and replace it with spaces designed around the car. In the Plan Voisin the traditional city must yield to the infrastructure of the automobile wherever the two were in conflict.” (in Automobile Utopias and Traditional Urban Infrastructure: Visions of the Coming Conflict, 1925–1940).
Other models for cities imagined around technology, particularly cars, are The Metropolis of Tomorrow (Hugh Ferris, 1929), Broadacre City (Frank Lloyd Wright, 1932), and Futurama (Norman Bel Geddes, 1939–40). Each of these proposals attempted to reconcile the “the ever-increasing speed and large-scale geometries of the automobile and the much finer grain and slower speeds of the traditional city street.” (Shelton, above, again). In detailing vertical and horizontal planes of movement of people and traffic, the spread of buildings, the fates of city centres, and travel between airports and cities, automobile technology sets the direction for optimistic, Utopian, urban planning and architecture.
Like the twentieth century automobile, the driverless car will re-order relationships to urban space and produce new kinds of places and urban cultures. The parking lot, rendered as cold, dangerous and creepy in cinema, is one such place. Commercial and personal use drones will need their own parking spaces, perhaps like the new Norman Foster droneport in Rwanda. The first pizza delivery by drone in New Zealand raises all kinds of practical questions about how exactly you’d get your pizza if you lived in an apartment building. Would the drone hover outside your window (what if you don’t have a balcony?) or leave it in a drone delivery depot? The devil is in the detail.
Liam Young’s forthcoming film, In the Robot Skies: A Drone Love Story, is a film shot by pre-programmed autonomous drones and tells the near-future story of two young lovers in a London Council Estate sequestered in their homes under ‘anti social behaviour orders’ who communicate by hijacking local CCTV camera drones that surveil their estate. Young says that just as the New York subway car of the 1980s birthed “a youth culture of wild style graffiti and hip hop”, the drone will create particular networks and cultures of surveillance activists and drone hackers. Not only is this a drone’s eye view of the city, but drones will be able to create film locations that weren’t accessible before.
Trailer for Liam Young’s In the Robot Skies
But while droneports and Council Estate drones may produce new flows of people and urban subcultures, big data technologies also continue to play a role in shaping and re-instating pre-existing physical geographies. Nowhere is this more poignant and difficult than at borders. Josh Begley’s new filmBest of Luck With the Wall, is 200,000 satellite images of the US Mexico border on Google Maps. In making the film, Begley says he wants to focus on the physical geography and the inhabitants of it: “The southern border is a space that has been almost entirely reduced to metaphor. It is not even a geography. Part of my intention with this film is to insist on that geography.” He does, but in doing so is also pointing upwards to the very satellites that made the film possible, the vast human, legal and machine apparatus that produces and maintains the US-Mexico border. So this border, and any border at this point, is both a physical geography, as well as something produced by technologies of border surveillance that deliver certain kinds of knowledge about what is valid, legal and legitimate in terms of movement across it; and what is not.
The surveillance apparatus of the US Mexico border is also comprised of people who work to make sense of data collected by machines. Joana Moll’s and Cedric Parizot’s The Virtual Watchers is a project that reveals another side of crowdsourced, open source intelligence. Moll says that Virtual Watchers is based on a project that was launched in 2008, and consists of an online platform called RedServants, a network of 200 cameras and sensors. The 203.633 volunteers on Red Servant watched camera feeds of the US Mexico border and identified “illegal” border crossings and other “illegal” events.
Norman Bel Geddes’ Futurama was where cars would create the “grain” against which the city would be built; now, with the gradual accretion of sensors, radar, lidar, optical recognition, fingerprint scanners, biometric turnstiles, key-card only access zones, license plate scanners, cameras, recorders, databases, dashboards, and maps, it is as if big data is the grain against which place itself is imagined. Smart city visions are based on visions of second-order cybernetic actualization. Orit Halpern’s work analyses the evolutionary arc of urban design imaginaries in smart cities like Songdo in South Korea, Masdar in Abu Dhabi, and Singapore. In these cities architecture and urban planning become armatures, or interfaces, for control through a kind of higher-order knowledge assumed to be embedded in data.
In Crapularity Hermeneutics, Florian Cramer speculates on the tension between car and city in a way that might have thrilled Le Corbusier and Lloyd Wright. He suggests that “all cars and highways could be redesigned and rebuilt in such a way as to make them failure-proof for computer vision and autopilots …. For example, by painting all cars in the same specific colors, and with computer-readable barcode identifiers on all four sides, designing their bodies within tightly predefined shape parameters to eliminate the risk of confusion with other objects, by redesigning all road signs with QR codes and OCR-readable characters, by including built-in redundancies to eliminate misreading risks for computer vision systems, by straightening motorways to make them perfectly linear and moving cities to fit them.” The design company BIG made a video for Audi, (Driver)Less is More, which seems to capture what Cramer talks about. In the BIG view, the driverless car inhabits a city made for itself (notice the absence of humans):
But before we arrive at that point where everything is re-adjusted for the driverless car, there is going to be considerable struggle for political rights and freedoms against the blindness of algorithms based on already-biased databases. For example, as Seda Gurses recently said, would we rediscover racial discrimination in apps like the way-finding app, Waze, or Redzone, that “help” stay out of “high crime neighbourhoods”? What kind of new places will be created, and discriminations perpetuated, by autonomous driving that identify people and neighbourhoods as criminal or threatening? As unacceptable as this is, it is these moments of the messy glory of human difference that must be fashioned into speedbumps, in-computable objects, on the road to Utopia.
Maya Indira Ganesh is a reader, writer, researcher and activist living in Berlin, Germany. She is working towards a PhD about ethics and technology at Leuphana University, and is Director of Research at Tactical Technology Collective. She has worked with feminist movements in India, and continues to at an international level through her work on Tactical Tech’s Gender & Tech project. She’s on Twitter as @mayameme; find more at Body of Work.
A couple of years ago I wrote about Friendsgiving, that very special holiday where cash-strapped millennials gather around a dietary-restriction-labeled potluck table and make social space for their politics and life experiences under late capitalism. All still very relevant, though I suspect this is the year where we should come up with a name for whatever happens after late capitalism. Some of you, of course, will be sharing a table with people not of your own choosing and so you might be forced into reckoning with people who make excuses for Nazis and disagree that trans people exist.
What follows are a couple of useful tactics that will help you hold your own and get through arguments that we shouldn’t have to keep having but here we are. These probably will not help you in a completely hostile room. These are better if you’re in a mixed crowd and you want to make sure that at the end of the political argument people don’t leave saying nothing more than “politics is so divisive!” People only criticize divisiveness when they aren’t sufficiently convinced by one side.
Above all, remember that political arguments are not about decisions based on different information, they are rooted deeply-held beliefs about how the world works that we are slowly socialized into. No single conversation will undo a social world. Campaigns (including these last two) know that most of their voters are “low information” voters who are not fluent in, or even persuaded by, long and involved explanations of policy. The mistake here is to assume that this is because most people are stupid and if you’re not basing your political positions on exhaustive research you don’t deserve to have tightly-held beliefs. This is a deeply condescending and unproductive position. Instead of delivering correctives like a walking, talking vox.com article, try to get to the bottom of what your debate opponents’ politics represent. If it is a general sense of declining American prosperity, agree with them! But then redirect the conversation away from race-baiting and lament any candidate’s ability to put forward a plan that would work for most people. Sometimes it helps to encourage someone to spin out their argument until it reaches an internally illogical conclusion like I did here. Depending on the situation, ask questions, challenge basic assumptions, or offer an alternative framing for the topic at hand. Which reminds me…
Understand Framing. No idea stands alone. Rather, concepts and ideas are interconnected and cannot be utilized without some unexpected or unwanted baggage. Framing is not just how ideas are presented, but what parts of an argument automatically feed into other arguments that the speaker is not intending to make. If you fall into an argument about how to make the country safer, for example, you are not talking about how most crimes tallied by the FBI’s Uniform Crime Reporting Statistics are at historic lows. (Same story with immigration.) Also, be sure to notice when you’ve started using someone else’s conceptual metaphor. If you talk about “trade wars” you have entered a conversation where trade is war. This means you’re trapped into talking about trade in terms of winners and losers who are determined through cut-throat violence. Try to reframe the conversation by talking about trade in a less combative way. Check out this handy list of conceptual metaphors to help you get familiar with conceptual metaphors.
Resist well-meaning people who want a reason “to hope that he succeeds in making the country great.” There is some sophisticated framing going on when someone parrots this line like a CNN talking head. The office doesn’t “make the man” and there are no checks and balances in place to make sure Trump is tempered by more level-headed people. The executive branch has never been more powerful and we have both parties to thank for that. Trump, for all his outsider status, has never made claims to devolving the power of the President. Don’t even argue about the Republican-held Congress and the soon-to-be 5-4 conservative Supreme Court. Instead, talk about all the ways Obama has strengthened the executive branch by embracing the Bush administration’s love of signing statements. Talk about how powerful the president has gotten in the last two decades and even if you like Trump he’s (hopefully?) not going to be president forever and someone will inherit the more-powerful position he’s helped create. There is nothing normal about this president and there are no counter-vailing forces within government powerful enough to correct the ship.
Reasonableness is so, so delicious. Everyone wants to be the reasonable one. Notice when the conversation turns toward what is reasonable, actionable, or realistic. This is a sign that someone is trying to do an end run around the very basis of your argument. They don’t want to engage in the substance of what you are saying and are more concerned with how reasonable and calm they appear to others. Britney Summit-Gil has more:
And if everyone at every interaction in their life is performing a self with the purpose of affecting another person, this holds true for left, right, and center. But for moderates, for white people, for the “reasonables,” there is little cost. Of all of the people I’ve seen calling for us to be reasonable, they are those least likely to be affected by a Trump administration. I have yet to see an immigrant, a person of color, a gay or trans person make this kind of call, though I am sure there are exceptions. But based on what I have seen, disenfranchised and targeted populations are calling for resistance, not unity.
Put the onus on Trump supporters to explain why we should ignore Nazi’s loud support for him, and “just give the guy a chance.” This is probably where the most aggressive confrontation must take place. Keep Trumpists on the defense by explaining why they think Nazi’s would be excited about this administration and what the administration plans to do to materially curb the power and prominence of these organizations (not just distance themselves from their most vocal avatars). Most likely you’ll be met with an argument about how these organizations are being given excess attention by the media and this is not representative of the Trump administration. Here you could agree that this isn’t totally unprecedented given that Reagan enjoyed endorsements from white supremacists, and a healthy handful of Republican primary candidates were supported by and shared a stage with a pastor that openly called for the execution of gay people. You could even bring up the fact that many white supremacist organizations celebrated Obama’s victory, albeit for very different reasons. After making that point, criticize Trump as not doing enough to overcome the problem that he’s nonetheless faced with. Above anything though, keep the focus on what Trump must do to deal with the seeming threat of Nazis regardless of whether that thread is manufactured by the media or not.
Stay away from talking about Trump in ableist terms. You might even surprise a few people by briefly, seemingly defending Trump. Stop anyone who is (still!) talking about Trump’s hand size or how “totally crazy” he is and instead keep focus on what he has said, done, and apparently believes. This is all that matters.
Two very different kinds of thoughts were running through my mind on the way to Leipzig to the BMW factory and on the way back. On the way there, I was thinking about how and why factories are relevant to the study of artificial intelligence in autonomous vehicles, the subject of my PhD; and on the way back I was thinking about the work ofHarun Farocki, the German artist and documentary filmmaker who left behind an astonishing body of work, including many films about work and labour. These two very different thought-streams are the subjects of this post about the visit to the factory. They don’t meet at neat intersections, but I think (hope) one helps “locate” the other.
BMW is a German car company that is working on ‘highly automated driving‘ (although the Leipzig factory we visited isn’t making those cars at present). I’m doing a PhD that will – someday – suggest how to think about what ethics means in artificial intelligence contexts, and will do so by following the emergence of the driverless car in Europe and North America. One part of what I’m doing considers a dominant frame that has emerged around ethics in the driverless car context: ethics-as-accountability. In the search for the accountable algorithm in driverless cars of the future, I went to the BMW factory to see where the car of the future will come from. Who, or what, must be added to the chain of accountability when the driverless car makes a bad decision? Who, or what, comes before and around the software engineer who programs the faulty algorithm?
I discovered something else more vividly and strangely digital than the car – the automation of the factory itself. In fact, the autonomous, intelligent car receded into the background and what emerged was a demonstration of scaled up, cybernetic thinking resulting in a factory that is shaped by logistics, which as Zehle and Rossiter put it is the ‘organisational paradigm’ of cybernetics:
The primary task of the global logistics industry is to manage the movement of bodies and brains, finance and things in the interests of communication, transport and economic efficiencies. There is an important prehistory to the so-called logistics revolution to be found in cybernetics and the Fordist era following World War II. Logistics is an extension of the ‘organizational paradigm’ of cybernetics […] Common to neoliberal economics, cybernetics and logistics is the calculation of risk. And in order to manage the domain of risk, a system capable of reflexive analysis and governance is required. This is the task of logistics.
The factory has become an infrastructural node, rather than the primary theatre of action; as part of a multi-nodal software program that determines the movements of people and things, rather than a point in a linear assembly line. To mix metaphors, logistics is the brainchild of cybernetics, serving as a kind of mental model to with which to think about the processes of production in the face of rising costs, rising demands and complex risk paradigms. So, conversations about “smart factories” are not about robots taking away jobs, which is a limiting approach to the topic; it perhaps more that people’s jobs in the smart factory become integrated into and are determined by software programs that determine where people, money, raw materials, ships, and eventually power itself, are to go. In what may sound a little dramatic, things like cars have (to) become software in order to be produced.
The ‘logistical turn’ has gained prominence as computer programs have come to be their the main design environment and control mechanism in manufacturing. Ned Rossiter, explains why logistical technologies are important: that “logistical technologies that measure productivity and calculate value” intersect with financial capital and supply chains, to result in a governance regime of standardization.
The factory features prominently in the origin story of the theories we love, cite, and lean on. The machine of Capital, the industrial machine, commodity fetishism, the culture industries: these are ideas that come to us, primarily, from observations of workers and conditions in factories. Factories and makingconveysignificant symbolic power. As Merkel famously retorted to the then-Prime Minister of Britain, Tony Blair, on what Germany’s secret sauce is: “Mr. Blair, we still make things.” But what does it mean to make things in conditions enabled by the internet, particularly unwaged work and new forms of labourwrapped up as ‘play’ and leisure? Trebor Scholz,editsDigital Labour: The Internet as Playground and Factory which offers a deep read into the many dimensions of what digital labour means. He says in the introduction: “there are new forms of labour but old forms of exploitation.” In an earlier time, it was perhaps less complicated to isolate where the exploitation comes from; in a time of ubiquitous computing, you have to pick away more carefully to reveal where it is.
In 1895, the Lumiére brothers made one of the world’s first films, Workers Leaving The Factory, in which workers are shown exiting the brothers’ photographic products factory in Lyon, France The film is a jumpy 45 seconds long on a 17m long film reel, a reminder of a time when it was apparent that people were technology, the first movie-making machines being hand-cranked projectors.
One hundred years later, German filmmaker Harun Farocki, asked: where were the workers going? “To a meeting? To the barricades? Or simply home?” and made a documentary researching the history of that film. Twenty years on and still intrigued by this film, Farocki and his co-curator, Antje Ehmann, presented Labour in a Single Shot, an exhibition of more than 200 single-shot 1-2 minute films about labour created through workshops in 15 cities around the world. The films are charming, whimsical, and are about varied and diverse kinds of labour: dog grooming, child care, industrial manufacturing, leather curing, surgery, taco delivery, water delivery, teaching, building inspection, security, tailoring, piano tuning, shoemaking, data centre management, and so on.
Labour is as much about capturing different kinds of labour as it is about filmmaking. All cameras are fixed giving a single perspective, the kind of thing we’re more likely to equate with CCTV visuality. In one film from Rio de Janeiro, we see a woman minding a little girl in a pink dress playing in a sandpit in a park in a garden. The child goes down a slide and obviously falls because we hear her wailing and the nanny runs out of the frame. We hear the child’s loud cries, and the nanny attempting to soothe her, all the while, the camera remains fixed. A few seconds later we see a child in her nappy, now muddy with sand, storming back into the frame and crying, the nanny scurrying behind her with the pink dress. What happened off camera?
Labour is a series about work that goes unrecognised as work, work that is both material and immaterial, mobile and fixed, routine and irregular, and the various contexts of sociality, camaraderie and the self in work. We see what it means to pay people for doing mundane and boring things like stacking clothes in a factory, or difficult things like scaling buildings, or moving the carcass of a dead cow, or things that are difficult to value, like teaching music. The mind seeks to draw equivalence between these activities and it is sobering and challenging to see where and how ideas of equivalence between different kinds of work break down. Always deeply politically invested, Farocki and Ehmann, want the viewer to be charmed and discomfited in equal measure, it would seem.
Back in Leipzig, a senior manager tells us, “Industry 4.0 is about smart logistics.” This isn’t just a piece of business jargon however; the manager said he did not like the idea of “smartness” and “4.0” but seemed to suggest it was baked into the design and operations of the factory; smartness was a sort of inevitability, it seemed. We heard many managers, at different times, talking about “the future” saying they were “ready” and “prepared to face it”. I wondered if this had something to do with the realities of autonomous vehicles that would come in “the future”? They just smiled in response.
The factory’s former chief engineer, and now- BMW board member, Peter Clausen says “communication was the implicit assumption underlying the design of this building…”; and eventually, “there is a central nervous system thinking in the flow of the building….” He hired the late Zaha Hadid to build a factory re-imagined as a place that would respond, seamlessly, to distant nodes of control and regulation. Thus, the words “flow”, “future”, “distribution” are mentioned often in talking about the architecture of the plant in relation to the production of cars. These and other ecology metaphors familiar to cybernetic thinking kept cropping up.
While we were walking around the shop floor, a manager told a story about BMW’s electric car, the i3, as we milled around its engine proudly on display. He said that in building the electric car they didn’t just replace the traditional combustion engine with an electric one; they actually invented a whole new car around an electric battery. They made “working from the outside-in” sound more intuitive than the oft-heard reverse, “from the inside out”. What this anecdote suggests, I believe, is that they wanted to, or had to, change how they saw production itself, to move away from the idea and practice of production as something linear. In a snarky comment to distinguish themselves from Google, someone said referring to the software company, “they’re a software company – they think about communication and then build a car around it.”
Here it seems that communication is embedded far deeper. The factory was designed in response to people’s communication flows. They measured the number of steps taken for one team to reach another, and the ways in which teams talk to each other through the production life cycle, and the different workflows of who talks to who, and when they need to talk to each other. One of the senior-most managers at BMW delighted in revealing that he receives less email than the visiting academics; he said he gets up and walks over to people to talk to them, thus reducing his email footprint: “email is asynchronous communication; talking to people is synchronous.”
Flow extends to how the shop floor merges with office space. Cars assembled in one part of the factory called the Body Shop travel along raised gantries right through the factory on their way to being painted and fitted out in the Paint Shop. You can be checking email, or talking to a coworker at the water-cooler, and have an unpainted shell of a i3 glide past overhead. The sides of the transfer gantries are lit in purple; we snickered about this as a tribute to the recently departed Prince. You could be forgiven for feeling like you’re on the filmset for a bad sci-fi film set from the 1930s. Or a music video from the 1980s.
People flow; there is an attempt to adjust traditional hierarchies into something nominally flatter in certain respects, and possibly shaped by mainstream notions of equality in German society (there are some deeply troubling notions of who a German is, however)The plant is built with one entry and one exit, so everyone -managers and workers and all levels of staff – enters and leaves through the same door. Everyone eats at the same cafeteria. Human Resources and Corporate Communications departments sit on the ground floor, by the cafeteria and the entry, and everyone has to walk past them.
The jewel in the factory’s crown is Clausen’s “finger concept”.. Traditional ideas of the assembly line are, well, linear. Imagine, instead, a single line bending to form a triangle before what was the ends of the line become the middle and the middle breaks apart to form the new ends of the line. This is, almost literally, what this factory does; what it means is that production can integrate new elements or processes without getting disrupted. For example, automation in cars means that new automating machines need to be introduced into the line. How do you enlarge the backbone of production without moving anything up or down the line? There is no way you can shut down a plant like this for more than ten days to change production processes. The answer: the factory has to expand and contract on demand. Thus the “finger” is an architectural design feature in which the physical layout of the plant can keep being extended by building new sections to integrate new machines, storage areas, supply chain entry points, and so on. Organic metaphors of ‘growth’, ‘marriage’, ‘body’, and ‘evolution’ are key to the description of such responsive architectural design.
But this is not about the triumph of welding social science into industrial design, nor about spatial design theory in corporate brochure copy. It is about the relentlessness of cybernetic thinking that promises comfortable, soft orderliness almost as a sort of counter-point to the very disruption it stimulates, with its flows, nodes, and self-organising, feeding-back loops, constantly seeking order in systems that may be complex, glitch-ridden, or creaky. The disruption and innovation, seen in light of rising costs and demands, are oddly, about standardization itself; the old factory again. Decision-making is not inspired, but faster. Algorithmic regulation resulting in the financialisation of labour, and the demands on physical infrastructure, and its people, to become like components of that system, smooth and flowing, to become data.
In 1990, after the fall of the Berlin wall, Farocki made How To Live In the FRG, a series of mock ‘training seminars’ for workers, from strippers to nurses, to adjust to a new life in a neoliberal world of a “relentless scripting” of interaction where human and commodity are “machined” to assume “maximum dependability”. For example, in the scenes with the stripper, you are shown a woman’s midriff and hips against a dimly red light-lit stage, very typically ‘stripper’; and a male voice off-camera. This un-embodied voice instructs the abbreviated woman on how to move her hips suggestively, how to slip out of her panties, and how to look more seductive. It is pedantic, funny, and awkward.
There is something that happens in the smart factory, that isn’t quite different from the not-smart factory: the worker is known through her relations to the finished product, and things in between get obscured. Erich Hörl reflects on how ubiquitous computing results in the “becoming-ecological” of media and creates displacement of workers, saying that work then was a “privileged action that focused on results and finality and obscured relations, mediations, and objects. Without direct dialogue, humans and the world or nature were placed in relation to the object, but only indirectly via the hierarchical structures of the community”. I read the smart factory as a continuation of the old one, in this sense. In the smart factory, the loops and flows of information supersede everything else, making the fact of mediation, the design, objects, and the people disappear; the flow is the thing.
The Farocki films I was thinking about on the train back from Leipzig keep digging at those obscured relations, mediations and objects, urging power out into view, quietly, sometimes grimly comical, and always with purpose. The scene with the stripper, like others in FRG, is rich in the minutiae of what work entails. In an issue of the journal e-flux dedicated to Farocki after his passing, the editors say:
With Harun’s precise scrutiny, an intimate world of techno-social micro-machinations comes to life. When an automated gate closes and latches, Harun is there. When looking into the LCD screens replacing rear view mirrors in cars, he is there. He is there when we address a colleague at work with a certain title.
Maya Indira Ganesh is a reader, writer, researcher and activist living in Berlin, Germany. She is working towards a PhD about ethics and technology at Leuphana University, and is Director of Research at Tactical Technology Collective. She has worked with feminist movements in India, and continues to at an international level through her work on Tactical Tech’s Gender & Tech project. She’s on Twitter as @mayameme; find more at Body of Work.
I recently updated my mac’s operating system. The new OS, named Sierra, has a few new features that I was excited to try but the biggest one was the ability to use Siri to search my files and launch applications. Sierra was bringing me one step closer to the human-computer interaction fantasy that was set up for me at an early age when I watched Picard, La Forge, and Data solve a complicated problem with the ship’s computer. In those scenes they’d ask fairly complicated questions, ask follow-up questions with pronouns and prepositions that referenced the first question, and finish their 24th century Googling session with some plain language query like “anything else?” Judging by the demo I had seen on the Apple website it seemed like I could have just that conversation. I clicked the waveform icon, saw the window pop up indicating that my very own ship’s computer was listening and… nothing.
The problem wasn’t with Siri, it was with me. I had frozen. It was as if a rainbow spinning beach ball was stuck in my mouth. I was unable to complete a simple sentence. I closed the window and tried again:
Show me files that I created on… Damnit
Sorry I did not get that.
Show me files from… That I made on Friday.
Here are some of the files you created on Friday.
In all honesty, I should have seen this coming. I frequently use Siri to set reminders or to put things in my calendar but I always use my digital assistant in secret: the moment between getting in the car and starting the engine, alone at my desk, or (sorry) while I am using the bathroom. It works almost every time but when something goes wrong, it is my commands not Siri’s execution, that is left wanting. I pause because I forget the name of the place I need directions to or I stumble when it comes to saying exactly what reminder I want to set. There are several Siri-dictated reminders sitting in my phone right now that don’t want me to forget to “bring it back with you before you go” or “to write email in the morning.” I clam up when I know my devices are listening.
It gets worse when other humans are listening to my awkward commands. The thought of talking to an algorithm in the presence of fellow humans is about as enticing to me as reciting a poem I wrote in high school or explaining a joke that just fell flat. Here I was thinking it was the technology that had to catch up to my cyborg dreams but now it seems that the flesh is the half not willing.
As it turns out I am not alone in my stage fright. Last June the marketing research firm Creative Strategies released a short report (though none of the raw data or a comprehensive methods section) that noted 98% of iPhone owners use Siri but only 3% ever talk to it in public. Most Siri usage seems to happen in the car which they surmise is related to hands-free laws, not “a free choice by consumers to embrace this technology.”
The authors of the report are surprised and seem to have no explanation for their two big findings: that 1) the speaking-to-phones-in-the-car effect is more pronounced in iPhone users than Android users even though Apple Maps is terrible and Google’s maps are the gold standard and, 2) Americans are “uncomfortable” using virtual assistants in public even though “consumers are accustomed to talking loudly on phones in public.”
None of this seems particularly surprising given my own experiences. Cars definitely require more hands-free usage but they are also where I (and most Americans) spend the most time alone. Privacy seems like an equally if not larger precipitating factor, which would mean that maps are not the only thing being used in the car. Additionally, most of Americans’ time in the car is spent commuting to work, and so maps are unnecessary. It is far more likely that we’re asking our phones to play that new album or place a call to mom to see how she’s doing.
Equating human-to-human conversation over the phone with giving orders to a virtual assistant is a digital dualist mistake. Americans are certainly good at yelling at each in public, but that skill may not transfer to digital assistants. Interacting solely with a piece of software is something altogether different, although still social because algorithms are made by people and our interactions are situated within and among other humans.
Moreover, engineers assume a one-on-one relationship with devices with little regard for how a device is used in a group or how others see us use our gadgets. We can know this by just looking at how these services are demonstrated at their launch and subsequently marketed. Commands are clearly stated sentences from a single person into one device. Even devices like Amazon’s Alexa, which are meant to serve the whole home, cannot intercede in a conversation between two or more people. It is always one-on-one.
Many tech critics, unfortunately, tend to reinforce this assumption in their writing by describing psychological effects and rarely sociological observations. Analysis focuses on the extension of individuals’ cognitive abilities or laments eyes focused on screens. Rarely are we treated to a discussion of the role of devices as social actors in a relationship with multiple humans. Part of this is strictly economics: if a device is meant to be shared you cannot sell one to every single person. More insidiously though, the asocial approach to technology reflects a shallow understanding of humans’ communicative practices.
How we are seen talking by third parties, especially when the conversational partner is unknown, is very important. It is the stuff of reputations and flash judgements. One of the myriad scenarios that run through my head when I imagine using Siri in public is that someone might think I am talking to a human the way I talk to Siri, which is to say, talking to them like an asshole. I do not tell Siri please and thank you, nor do I use deferential phrases like “could you” or “would you mind.” I talk to Siri the way I talk to a cable company’s phone tree.
I have not done an exhaustive study of this subfield of HCI, nor am I practitioner myself but a quick look at some of the emerging textbooks and research in what is being called “conversational interfaces” is immediately telling. Michael McTear’s modestly titled The Dawn of the Conversational Interface [PDF] opens with an introduction describing the 2013 movie Her. He does not use this references as a cautionary tale, but as a simple demonstration of what conversational interfaces may soon become. Her is aspirational in a way that makes you hope that McTear stopped watching the movie before the third act. Unmentioned is the romantic relationship this male character has with this feminine AI who is, one must assume, both his secretary and lover. (More on those considerations here.)
McTear’s writing is one example of a fairly common relationship between fictional depictions of technology and very real attempts at making that technology come to life. Engineers and scientists regularly appeal to the fears and hopes depicted in film as a way of building a mythos around their research program. Cyber security research promises to prevent the devastation depicted in action movies, public funding for road infrastructure will deliver us into a Jetsons-like techno utopia (see previous link), and Siri will eventually fall in love with you.
If there is any prescription to be had here it is the work of Philip Agre, Phoebe Sengers, and others who advocate for the integration of critical theory into computer science and similar fields. Agre’s argument that computer scientists would do better work if they were critical of the basic assumptions of their field, is immediately relevant here. Is boss/assistant really the best relationship we could have with our devices? Is this nothing more than a softening of the master/slave terminology [PDF] that still lingers in mechanical engineering and computer science? Are we still beholden to the idea of the robotnik: The Czech word for slave that, through the translation of Karel Capek’s play R.U.R gave us the English word robot.
Perhaps, deep down, we are reticent to bark orders at our phones because we sense the echoes of arbitrary power in the construction of our machine-readable verbal commands. That the embarrassment we feel is a sort of discomfort with being a master, not just looking or sounding awkward. That makes the commands in private seem even worst if I am honest. At least open and notorious commands are exactly what they appear to be. Acting the master in private is a desire for veiled power which, to my mind, seems more sinister.
If Microsoft’s ill-fated Tay was a bellwether of the racist invective endemic to the internet then the cheery submissiveness of our digital assistants are something even darker. Certainly what we say and do to software is (for now) nowhere near as important as what we say and do to our fellow humans but we should think deeply about what we are indulging in when we talk to computers. Whether these practices and relationships are a net positive for a society that could use fewer power differentials. Just because we have talking computers doesn’t mean we’re any closer to the utopic visions we see on TV.
We should have seen this coming. The end of the world as we know it was announced today, unceremoniously with a blog post. Scripps Institution of Oceanography is reporting that we’ve definitely surpassed the 400 parts-per-million threshold for atmospheric CO2. It is at this concentration that a cascade effect is triggered and acidic seas rise to new heights, extinction rates increase, and food systems are permanently disrupted. More on all of that here.
What I want to focus on briefly is how we grapple with this enormous problem. It has been said before but it is worth saying again today: spurring people to act on climate change is difficult because the consequences are distributed and any solutions are really only best guesses to what is an enormously complicated question. Not only is it impossible to instantly halt all fossil fuel usage, it is difficult to even agree on how to scale it down. This is not a wishy-washy centrist political problem: should nations that have been plundered by colonial rule be forced into slowing down their own domestic nation-building projects? Should Europe and North America take on a greater share of the responsibility to account for historical advantages?
I am not expert in these matters, I only bring up this complication because it runs counter to the clear-cut narrative that U.S. environmentalism usually puts forward: that carbon neutral or even carbon negative futures are possible and it is only a matter of weak wills and greed that keep the smokestacks churning. Climate Change is often seen as a problem to be solved with equal parts technology and regulation but I would contend that an equal if not bigger issue is how we talk about climate change.
Lead on a global treaty to halt climate change. End destructive energy extraction: fracking, tar sands, offshore drilling, oil trains, mountaintop removal, and uranium mines. Protect our public lands, water supplies, biological diversity, parks, and pollinators. Label GMOs, and put a moratorium on GMOs and pesticides until they are proven safe. Protect the rights of future generations.
In theory, the policy positions outlined on a campaign’s web site are not there to make an argument so much as they are there to help you decide if your values line up with that of the person running for office. In truth though—and this should be especially true for a third party candidate that needs to convince people to vote on a long-shot—every time you have a voter’s attention you should be trying to convince them to change their mind and vote for you or give them more fodder for an internal dialog of why they’ve made the right choice to vote for you. Stein’s platform is emblematic of a larger problem of environmental social movements as of late: there is no shortage of organizational energy but there is still no clear way forward.
Climate change inaction is essentially a problem of public engagement because there are very bright people with very clear agendas but nothing really seems to be taking hold as forcefully as the situation demands. And no wonder: what does it even mean to “halt climate change” at this point? What is an electorate signing up for when they choose a government that commits to protecting biological diversity? I know someone knows—there’s probably even precedent for it—but I’m a fairly educated person on this topic and if I were faced with having to answer that question in order to gain entry to the last boat leaving North Miami Beach during the supermoon, I would probably end up clinging to a classy sectional sofa somewhere 100 miles north of Cuba.
The actual answer to the questions I pose above are besides the point. Thinking of climate change as a problem of argumentation means that there is something fundamentally wrong with how we talk about confronting the issue. After reaching this auspicious milestone, it seems likely that it those who are convinced climate change is real will be talking about it. It is also likely that a lot of that talk will center around how thick-headed people are for not believing in climate change, becoming a single issue voter about it, or doing enough to reduce their own carbon footprints. I do not think that sort of talk is helpful anymore, if it ever was.
To answer my glib titular question: there has to be a renewed commitment to meeting people where they are at. Granted, where people are at, is bad: not nearly enough people in the U.S. believe in climate change (recent poll pegs it at 30%) but perhaps the problem is that we need people to “believe in” impending global catastrophe. Resolute and determined commitment to facing a danger is only one of many reactions and unfortunately willful ignorance is another. Instead of calling anyone that doesn’t believe in climate change an idiot, there needs to be a wide range of rhetorical strategies. The general shift towards talking about climate issues in economic terms is probably a good start. (Martin O’Malley’s often-repeated phrase “Climate change is the best job opportunity we’ve seen in 100 years” is probably a bit much though.)
I definitely would rather live in a world where climate change was treated as the pending disaster that it is, but instead I live in one where it is largely ignored or outright denied. I suspect it is time to stop expecting people to be persuaded by evidence, even when it has literally arrived at their front door in the form of regularly reoccurring floods or droughts. Climate change is not a problem primarily defined by not enough people knowing the science. It is a political problem that requires persuasion by multiple means. The oil company villains and the “if every single person just…” rhetoric seems to have reached as many people as it is going to reach and we have to change tactics. That is, of course, if we stay committed to the idea that there is still time to wait to persuade people at all. If that is not the case then perhaps environmentalists must consider going in the opposite direction and, rather than appealing to existing governmental bodies, step up the rate at which they take it upon themselves to forcefully close uranium mines and fracking. I don’t know if there’s a third option.
We live in a cyborg society. Technology has infiltrated the most fundamental aspects of our lives: social organization, the body, even our self-concepts. This blog chronicles our new, augmented reality.