A tale of three cities, or: The smart city as will and category error

The following short piece is my contribution to Imminent Commons, the catalogue accompanying the 2017 Seoul Biennale of Architecture and Urbanism. I hope you enjoy it.

Humanity is now, we are so often told, an urban species. Though there are real questions as to what the numbers actually mean, the statistics on planetary urbanization are so often bruited about that they have become something of a cliché. What’s more, popular discourse on the subject appears to have internalized the notion that the great cities of Earth aren’t merely significant for their concentration of habitation, but for the beneficial effects that habitation gives rise to. Disproportionately generators of economic vitality, technical innovation and cultural dynamism, our cities may even be able to function as lifeboats capable of sustaining us through the ecological reckoning that is now bearing down on our civilization.

If it is an urban age, though, it is also a networked one. Between the comprehensive instrumentation of the built environment, and the smartphones that so many of us now carry through every moment of the waking day — simultaneously sensor platform, aperture onto the global network, and remote control for the connected systems and services all around us — the colonization of everyday urban life by information processing is virtually complete.

And finally, we appear to have entered an age in which the more-or-less stable neoliberal consensus that held global sway for the past four decades has started to erode. Thus far, the most notable and distressing result of this erosion has been a turn toward authoritarian and xenophobic ethnonationalisms of one stripe or another, its traces evident in the Brexit referendum, the 2016 US presidential election, and a long list of autocracies in the ascendant, from Russia to Turkey to the Philippines. But more hopefully, the eclipse of neoliberal hegemony has opened up a space in which some dare to imagine an entirely new way of organizing the productive processes of life: a commons beyond state and market both, in which networked collaboration, distributed material and energetic production, and horizontal forms of governance give rise to striking new possibilities for a just, equitable and fructifying urbanism.

By leveraging the decentralizing tendencies that appear to be implicit in our networked technologies, and the configurations of power they in principle give rise to, we can even begin to imagine what a networked urban commons would look like, and how it might work, at global scale — as a desirable end in itself, an antidote to the anomie and widespread sense of powerlessness that underlie the turn toward xenophobic authoritarianism, and a means of restoring some semblance of ecological balance.

Those of us who are interested in bringing such a state of affairs into being, though, might find that our hopes are dashed at the outset by a lack of clarity about how the technologies involved actually work, naiveté about those parties who currently wield them most effectively, or confusion about what a true commons would require of us. At present, we can see networked technology being layered onto urban place along three basic trajectories: one based largely on the needs of multinational technology vendors; one with roots in the Silicon Valley startup and venture-capital complex; and one — the subtlest yet most promising of all — as yet indistinct. By examining each of them in turn, we can learn more about what is at stake in the advent of networked urbanism, and perhaps chart a course through the Scylla and Charybdis of unwise choices toward a more fruitful future for all.

§ Avatar I: Songdo

In his public appearances, the presidential candidate Moon Jae-in is fond of invoking a comprehensive vision of heavily technologized everyday life that involves “smart house, smart road, smart city” — indeed, an entire “Smart Korea.” There may be no place on Earth closer to concrete fulfillment of Moon’s objective than New Songdo City, a municipality of 90,000 souls built on some 53 square kilometers of tidal flats recovered from the Yellow Sea. In Songdo, both domestic spaces and the entire built fabric have been instrumented, allowing the city’s controllers to monitor and adjust traffic flow and energy utilization in real time.

As ambitious as this sounds, it’s an only slightly more elaborate version of a conception of networked urbanism that is common to municipal administrators and technology enthusiasts the world over. In its raw outlines, this conception seeks to harness the CCTV cameras and networked sensors installed throughout the urban milieu, as well as the torrential streams of data flowing off of our personal devices, to realize greater efficiency and enhance that ever-elusive property known as “quality of life.” By submitting these flows of data to advanced analytic techniques based on machine learning, all kinds of benefits can be obtained: the nominal “optimization” of material and energetic flows, the streamlined delivery of municipal services, even the preemption of undesirable conditions (whether traffic jams or criminal offenses).

This, anyway, is the theory of smart urbanism. In practice, however, a number of issues conspire to ensure that what gets delivered invariably turns out to be rather less than the sum of its parts. The first is that, in looking to a rising technology sector to achieve this ambition, municipal-scale actors leave themselves at the mercy of powerful vendors —
globally, multinationals like Siemens, IBM, Hitachi or Microsoft; in Korea the infrastructure, systems-integration and real estate development arms of the familiar chaebol. Because they generally lack the organic technical competence to determine what kinds of hardware and software might best serve their needs, city governments entering this market are perforce compelled to buy what these vendors have to sell, whether or not the problems those systems are designed to solve bear any particular resemblance to the issues perceived by their constituents. This was certainly the case in Songdo, where the expensive and elaborate Cisco “telepresence” hardware planned for each apartment unit in the city was rendered obsolete even before it was deployed, outmoded instantly by free smartphone- and tablet-based video chat applications like Kakao Talk and FaceTime.

The second problem follows on from this. By its very nature, the municipal procurement process involves one set of centralized, hierarchical actors (i.e. technology vendors) interacting with another (local bureaucracies). As a result, the multispectral awareness that might in principle be derived from large-scale analysis of data is generally retained for the exclusive use of municipal administrators, habitually and instinctively — and not, in other words, made available to the public who generated the data in the first place. What is offered to us wreathed in the ostensible glamor of technological futurity, then, is here revealed to be something that’s actually rather dowdy and retrograde: old-style technocratic management from the top down. Not by any stretch of the imagination something consonant with the will to collective self-determination, it cannot be reconciled with the commons without contortions that verge on intellectual dishonesty, however well-intentioned they may be.

And there is a final issue: daily life in Songdo, at least, appears to be rather soulless and dull. NPR quotes a young resident who describes it as a nonplace and a “prison,” and compares her escape into Seoul and all its nightlife at the end of the workweek to a jailbreak. This is admittedly a single data point, but it hardly makes a compelling argument for quality of life in the well-tuned city.

In its current form, then, the smart city as delivered by vendors is not merely ill-advised, nor merely unlikely to support the kind of vivid experiences we associate with big-city life, but actively detrimental to the achievement of an urbanism consistent with the values of the commons. A case in point can be found in the recent Korean experience of mass public demonstrations, which illustrate like relatively few other moments in history the power that an aggrieved citizenry claims for itself when it takes to the streets in protest of an order that has become intolerable. As it happens, the technologies bound together under the banner of the smart city have no way of accounting for this kind of active practice of democracy. Far from recognizing mass demonstrations as the signal of public sentiment they surely are, the smart city can only interpret such protests as a disruption to business as usual: first as an anomaly to be detected, then as an inefficiency to be contained, minimized, neutralized or eliminated.

§ Avatar II: San Francisco

It’s worth unpacking just what business as usual looks like to the architects of the smart city, what conceptions of the normal and the ordinary they may hold in mind when designing the algorithms responsible for detecting imminent departures from normalcy and triggering preemptive action.

And here we need to address the fact that even in software development, there is such a thing as fashion. Once something practiced by a self-consciously professional cohort given to horn-rim glasses, crisp short-sleeve shirts and pocket protectors — call it the Mission Control look — software engineering is, in its Northern Californian and Pacific Northwest fastnesses, dominated by a young, privileged and remarkably homogeneous technical elite. At present, you cannot walk down the streets of San Francisco — a city whose name was once synonymous with the radical, the queer, the experimental and the frankly marginal — without running headfirst into a mostly male scrum of software engineers in their mid-twenties, in their universal uniform of fitted hoodies and $400 sneakers, talking unit tests and code sprints. To a surprisingly great extent, it is their tastes, predilections, priorities and values that urban technology is increasingly designed around.

If the multinational vendor, in all its centralization, conservatism and ponderous lack of agility, represents one of the two predominant modes in which information technology is now applied to the life of cities, the other is typified by the proverbial Bay Area tech startup, with its addiction to venture capital and its imperative to “move fast and break things.” Thus the emphasis on convenience and immediate gratification we see in offerings like Airbnb, Tinder, TaskRabbit and above all Uber: services whose socially corrosive effects were self-evident virtually from the outset, though they are only recently becoming matters of widespread controversy.

It is now beyond dispute that Airbnb has undermined the market for affordable rental housing in city after city, just as Uber’s massive, outsourced fleet has drastically increased traffic in cities around the world, even as it drained custom and resources from public transit. What these services offer is nothing less than a shared reality platform for everyone wealthy enough, and sufficiently comfortable with technology, to use them fluently — a platform that privatizes benefits and sheds costs on the public so nakedly indeed that we no longer hear much talk of a putative “sharing economy.” Though these effects can be noted in every market where these services operate, they’re felt particularly acutely in the Bay Area, where life for those who most closely resemble software developers demographically and psychographically often does seem to consist of near-effortless algorithmically-streamlined ease, albeit at the cost of a slowly decaying public realm for everyone else.

It is telling, in this withdrawal from any pretense at convivial urbanity, that we don’t even discuss progress anymore, only “innovation.” In doing so, we preemptively surrender the terrain of the social imagination to the likes of Elon Musk, Jeff Bezos and Mark Zuckerberg, if not still more impoverished souls like Travis Kalanick or Peter Thiel. If the urban condition that results from their everted imaginings is not quite the brutal reality of first-generation smart cities like Masdar City, in the United Arab Emirates — where Pakistani, Bangladeshi and Filipino guest workers labor long, thanklessly and at great personal risk to keep the city turning over, and end their days in metal shipping containers arrayed behind razor wire under the broiling desert sun — neither does it have much to do with how cities have traditionally generated meaning and value for their inhabitants. Thus far, at least, everyday life in this capsular, app-mediated city appears to be defined by its exclusions.

§ Avatar III: Seoul

By contrast, the Greek architect and activist Stavros Stavrides, in his recent book on practices of spatial commoning, emphasizes the profoundly invitational aspect of any true commons, its quality of radical openness and porosity. If neither the multinational nor the startup way of doing networked cities quite works to produce such conditions on the ground, where can we go looking for a model that might do so?

Perhaps the greatest irony of all, in the present context, is that certain aspects of vernacular Korean urbanism already work quite well in this regard. Without fetishizing them, or sugarcoating their less felicitous aspects, Korean cities even now reliably generate an informality and canniness in the use of space that comes much closer to achieving the vision of a life in common than anything on offer from either wing of the tech industry. Not so much the newly-built, gated apartment complexes, of course, with their Ballardian full-service towerblocks rising in endless numbered ranks, but in older city cores throughout the country. Here the ajeossi play an impromptu game of baduk in a doorway, seated on torn cardboard box covers; there a sudden chicken-and-beer stand has popped up on an unused concrete forecourt; above, tucked into the fifth floor of an otherwise anonymous office building, is the jjimjilbang with beauty salon and restaurant and game parlor attached, pulsing with life and activity through 24 hours of the day. These things may not read that way to a globalized elite smitten with enticingly glossy corporate visions of the future, but to a certain kind of Western visitor, these feel like signals of the way life in the networked city could be: spontaneous, mobile, flexible, convivial, and above all open.

Could we design networked platforms and systems that generated this kind of urban experience, not merely for a few, but for everyone? The answer is almost certainly yes — but successfully doing so would require that we learn to wield networked technology quite differently than we do at present.

It would be necessary, first, to step back and ask what we are actually trying to achieve by deploying networked systems in the urban frame. We would have to test and iterate and test again, and discard for good that which is seen not to work. This, of course, runs almost directly counter to several aspects of the way we do things now: the headlong pace of technical innovation most obviously, but also its ahistoricity.

It would be necessary to press for specifics, whenever we are offered hype, buzzwords and promises. We would have to ask hard questions about how technologies actually function when used by real people in real environments, and not simply be seduced by lovingly-crafted renderings or animated flythroughs.

It would be necessary to nurture more space outside the market in particular. If “the commons” is to mean anything at all, it can only refer to a milieu where neither the values of the state nor those of the market prevail, leaving room for mutuality, solidarity and positive-sum collaboration — the diametric opposite, in other words, of the condition that broadly obtains in the West now, where the market sets the ground conditions of everyday life, and the state is increasingly figured as something that exists solely to guarantee the operating conditions for private enterprise. It remains to be seen how this model might apply to a place like Korea, where the dynamics of the developmental state retain a powerful hold on the national psyche, but it would clearly be an uphill battle.

Finally, regardless of the particular set of political commitments we hope to see observed in the design of urban technologies, it would be necessary for us to consider with the greatest care what kind of subjectivity our use of these systems give rise to. We would have to ask who we become in their presence and through their use, and be prepared to redesign everything if we don’t much care for the answers.

The examples I’ve offered here ought to make it clear if what we seek to achieve is a life in common, the whole quest for technological “smart” is something akin to a category error, where it isn’t simply intellectually bankrupt. We know in any event that any city deserving of the name is always already smart, and that its intelligence resides in the people who live in it and give it life. The task that remains before us is to design technical systems that are respectful of that intelligence, and allow it to speak itself. In the final analysis, this task cannot be outsourced. It cannot be optimized. It cannot be automated. It will require of us profound investments of time, energy and care. But the reward would be considerable: a place, or a meshwork of places, where everyday life is spontaneous and convivial, where the conditions of equity, justice and ecological balance are finally realized, where our quest to be human in full might find at last a natural home and ground.

US book tour dates, Fall 2017 (rolling updates)

Here’s a list of some upcoming Radical Technologies events in selected East and West Coast cities during September and October. It’d be so lovely to see you at one (or more) of them.

You may want to check back to see if I’ve added a talk in your city, by the way, as this itinerary is very much a work in progress. Similarly, I’ll add links to event venues, times and other details as I get them. See you soon!

East Coast
September 12th
– Baltimore MD: Morgan State University, with Fred Scharmen.
– Baltimore MD: Red Emma’s.
September 13th
– Philadelphia PA: Wooden Shoe Books.
September 14th
– NYC NY: NYU Interactive Telecommunications Program.
– Brooklyn NY: Verso.
September 15th
– NYC NY: Columbia University, with Laura Kurgan.
September 16th
– NYC NY: McNally Jackson, with Aimee Meredith Cox.

West Coast
October 4th
– San Francisco CA: City Lights Books.
October 9th
– San Diego CA: UC San Diego, details TBC, with Babak Rahimi.

The extended Acknowledgments

With Radical Technologies finally out and — to my amazement and deep satisfaction — receiving the most extraordinarily generous notices, I think it’s a good moment to pause, take a breath, and take stock of how it is that I’ve rolled up on these shores.

In the course of a life, if you’re very lucky, you run into people who through their words and deeds launch you on a completely new and better trajectory than the one you arrived on. There’s actually quite a bit more than luck involved, of course; one of my favorite definitions of “privilege” glosses it as a state in which your personal networks tend to help you achieve your ambitions, rather than suppressing or undermining them. But there’s unquestionably room in all of this for the operations of chance.

Looking back now, I can see a few clear and obvious inflection points in the journey that resulted in me being able to write and publish Radical Technologies, and without exception they were moments at which a specific individual human being intervened in my life in a conscious attempt to change my fortunes for the better. And what strikes me with particular force is how contingent all of these encounters were. They so easily could have gone another way — any other way. And had that been the case, it is overwhelmingly likely that my life as I know it wouldn’t exist.

What follows, then, is my (no doubt flawed and incomplete) attempt to name and thank these human beings for making the decisions they did. I want them, and you, to know that wonderful things happened in the aftermath of those choices.

Juliana Uruburu, Dwight Jackson, Dave Dunn, Tori Orr, Anne Galloway, Christina Wodtke, Jeffrey Zeldman, Andrew Otwell and Chris Heathcote: thank you for seeing what nobody else could, and for acting on what you thought you saw. You all have my profound and permanent gratitude. Adriana Young and Leo Hollis, of course, I’ve already thanked in the book itself. Maya Lin extended to me, at a critical moment, a gesture of big-sisterly kindness that she will have long ago forgotten, but which meant everything to me. And a few other people along the way, sadly no longer with us, who said or did things that changed the entire course of my existence. (Here I’m thinking primarily of Herbert Muschamp, who I miss all the time, and the great Red Burns at NYU’s Interactive Telecommunications Program, who took a gamble on letting me teach there when there was no obvious reason to do so. May their memory be a blessing.)

An index, 2017

I thought you might enjoy seeing the draft index I compiled for Radical Technologies, now available for pre-order on Amazon. If nothing else, it’ll give you an idea of the book’s main concerns, and maybe even a sense of its arguments.

Radical Technologies launches worldwide on May 30th, 2017.
 
#
15M movement (110, 169)
3arabizi (311)
3D printing (8, 85-86, 88, 93-96, 98, 100-104, 107-108, 110, 281, 295-296, 302, 312)
The 5 Point (Seattle dive bar) (84)
51% attack (139)

A
Accenture (198, 231)
accuracy (machine learning) (217)
acrylonitrile butadiene styrene plastic filament (ABS) (94-95)
Aetna (36)
aerogel (95)
AIDS Coalition to Unleash Power (ACT UP) (167)
Air America (CIA front organization) (228)
Airbnb (41, 156)
Alcoholics Anonymous (167)
Aldiss, Brian (291)
Alibaba (106, 286)
Alphabet (company) (275-279, 284)
AlphaGo (264-266, 278, 270)
Amazon (36-39, 46-47, 193, 195, 211, 275, 277-282, 284, 286, 314)
– acquisitions of (280-281)
– Alexa virtual assistant (39)
– Dash Button (36-37, 42, 46-48, 279)
– Echo (38, 279)
– Echo Dot (38)
– Flex (278)
– labor conditions at, blue-collar (47, 195)
– labor conditions at, white-collar (195n)
Amnesia, Anne (181)
Android operating system (18, 44, 275, 278)
Annapurna Labs (281)
“anticipatory surveillance” (242)
AntPool mining pool (139)
Apple (15, 18, 33, 36-39, 85, 197, 275, 277, 279, 283-285)
– App Store (18)
– iOS (18)
– iPad (277)
– iPhone (15, 64-65, 277)
– iTunes (277)
– Macintosh, first-generation (85)
– Siri virtual assistant (39)
– TV (277)
– Watch (33, 36, 197)
application programming interface (API) (26, 39, 60, 196, 248, 274)
application-specific integrated circuits (ASIC) (128, 138, 141)
AR-15 assault rifle (108)
Arlington National Cemetery (65)
Armadillo police vehicle (29)
artificial intelligence (259-271)
Asawa, Ruth (261)
Atelier Populaire (269)
augmented reality (AR) (63-84)
Auschwitz death camp (61, 65, 71)
automated teller machines (ATM) (1, 3, 7, 52, 135)
automation (8, 153, 183-207, 226, 236, 255-257, 260, 275, 280, 311)
– economic implications of (192-206)
– “four D’s of” (184, 202)
– motivations behind (186-191)
autonomous organizations (115, 147, 175, 302)
autonomous trucking (193, 255, 278)

B
Bach, J.S. (261)
Back, Adam (121)
Baidu (243)
Baihe (286)
Balochistan (179)
Bank of America (120)
Bank of England (194)
baseband processors (15)
beacons (49, 51)
becoming-cyborg (80)
Beer, Stafford (155, 302)
Bennett, Jane (307)
Bergen-Belsen concentration camp (61)
BetterWorks (199)
Bezos, Jeff (193, 278)
bias (human prejudice) (188-189, 234)
bias (machine learning) (218)
big data (211, 221)
Bitcoin (115-117, 119-126, 128-129, 131-143, 145-151, 153, 155, 157, 159-163, 165-166, 179)
– as infrastructure for micropayments (133)
– mining of (126-128, 130-131, 135, 138-141, 145)
– putative anonymity of (137)
Bitcoin Magazine (148)
“black boxes” (244, 253)
Black Lives Matter movement (177, 236, 244)
blockchain (8, 115-181, 207, 209-210, 288, 290, 293, 295-296, 303, 307, 318)
Bois de Boulogne (2)
Borges, Jorge Luis (244)
Boston Dynamics see Google
Bowyer, Adrian (86, 303, 306)
Branch (startup) (246-247, 254)
Brandes, Jeff (256)
Brantingham,
– Jeffrey (231)
– Patricia (232)
– Paul (232)
Braungart, Michael (96)
British Broadcasting Corporation (BBC) (177)
Brown, Henry T. (103)
Brown, Joshua (223-224, 254)
Brown, Michael (231)
“buddy punching” (198)
bullshit jobs (203, 205)
Bui, Quoctrung (192-193)
bushido (266-267)
Bushido Project, the (266)
Business Microscope (197)
Buterin, Vitalik (147-150, 152, 154, 162-164, 167, 169, 172, 175, 177, 179, 303, 311)
Byzantium (69)

C
CAD-Coin (157)
Californian Ideology, the (283)
Carmack, John (82)
cartography (20)
cats (214)
cellular automata (86)
Champs-Élysées (Paris street) (1)
Chaum, David (121)
Checkpoint Charlie (70)
chess (263)
Chevrolet Camaro (216-218)
Chicago Police Department (230-231)
China (87, 102, 190, 194, 278-279, 286, 290, 306)
Chinese yuan (135)
Churchill, Winston (28)
circular economy (92, 96, 99, 288)
Ciutat Meridiana (Barcelona neighborhood) (109)
climax community (289)
closed-circuit television (CCTV) (49-50, 54, 241)
Cockney rhyming slang (311)
code library (274-275)
commons, the (171-173)
computer numerical control (CNC) milling (86, 93, 95, 97, 108, 110, 273)
Container Store, The (196)
cooperatives (171)
cooperative motility (80)
Copenhagen (31, 51)
Cornell Law School (151)
Cortana virtual assistant (39)
CostCo (45)
cozy catastrophe (291)
cradle-to-cradle industrial ecosystem see circular economy
The Craftsman (111)
Creative Commons (102-103)
CRISPR technique (298)
Crossmatch (startup) (198)
Crown Heights (Brooklyn neighborhood) (136)
cryptocurrency (8, 115-144, 145, 148-149, 153, 156, 164-165, 177-178, 248, 273, 279, 290, 293, 318)
cryptofinance (180)
cryptography (116, 118-119, 121-123, 129, 146-147, 176, 178-179)
“Custom Notifications” (Chicago Police Department program) (235)
cybernetic socialism (191)

D
DAO, The (distributed autonomous organization) (161-181)
data subject (251)
Davao City, Philippines (31, 43, 46)
Day, Jeffrey (63)
distributed denial-of-service attacks (45)
“The Dead” (short story) (261)
Deep Blue (263-265)
Deep Dream see Google
Deep Lab (314)
deep learning see machine learning
DeepMind see Google
de Certeau, Michel (311)
Deleuze, Gilles (148, 211)
dematerialization (11)
Demnig, Gunter (72)
de Monchaux, Nicholas (101)
Demos (246)
Deutsche Bank (278-279)
The Dialectic of Sex (191)
El Diario newspaper (109)
Dick, Philip K. (83, 244)
digital fabrication (85-114)
digital rights management software  (DRM) (292, 295)
DiscusFish/F2 Pool mining pools (139)
distributed applications (115, 147, 149, 163)
distributed autonomous organizations (161-181, 288, 302)
distributed consensus (126)
distributed ledgers (117, 137, 160, 293)
Department of Motor Vehicles (generically) (158)
Dodge Charger (216-217, 221)
döner (71)
“Double Bubble Trouble” (MIA song) (295)
drones (103, 188, 220, 277-278, 283, 295)
DropCam (281)
Dubner, Stephen J. (237)
dugnad (170)
Dunning-Kruger syndrome (260)
Dutch East India Company, the (165)

E
Easterbrook, Steve (195)
Edo (69)
Elemental Technologies (281)
Elephant and Castle Shopping Centre (110)
Eisenman, Peter (70)
Embassy of the United States, Beijing (51)
Eno, Brian (238)
Equal Credit Opportunity Rights (248)
Ethereum/Ether (148-150, 152-154, 162-163, 168, 175-177, 179)
Ethical Filament Foundation (99)
Ethiopia (194)
Euro (currency) (100, 131, 136)
“eventual consistency” (134)
Existenzminimum (111)
Expedia (134)
EZPass (59)

F
fablabs (95, 100, 109-110)
faceblindness (67)
Facebook (69, 220-221, 227, 229, 232, 252, 275-279, 281, 284)
– Aquila autonomous aircraft (278)
– Free Basics (278)
– Instagram (278)
– opacity of Trending News algorithm (212, 252-253)
Fadell, Tony (276)
false positive (truth value) (217, 235, 249)
Family Assistance Plan (FAP) (204)
Fan Hui (268)
feature engineering (218)
Federal Trade Commission (248)
FedEx (278)
Filabot (98)
Fillod, Odile (107)
Financial Times (177)
FindFace software (240-242)
Firestone, Shulamith (191)
Fitbit Charge wearable device (197)
Five Hundred and Seven Mechanical Movements (103)
Flaxman, Seth (250-251)
foamed aluminum (95)
Ford Mustang (216-217)
Forrester, Jay (56)
Fortune Magazine (257)
Foucault, Michel (35, 70, 160)
Freakonomics (237)
Frey, Carl Benedikt (194)
Fully Automated Luxury Communism (90, 111, 190, 289)

G
gallium arsenide (47)
Galloway, Anne (82)
gambiarra (291)
Garrett, Matthew (43)
General Data Protection Regulation (249)
General Public License (103)
Genesis Block (125, 139)
genetic algorithms (239, 253)
gender
– of pedestrians, as determined by algorithm (239)
– as performance (239-240)
– of virtual assistants (39)
geofencing (27)
Gershenfeld, Neil (95)
Ghost Gunner (108)
Giger, H.R. (219)
GitHub code repository (242, 274, 281)
“glassholes” (84, 276)
Global Village Construction Set (103)
go (game) (263-266)
Goodhart’s Law (247)
Goodman, Bryce (250-251)
Google (18, 24, 37-40, 46, 66, 69, 73-74, 76-78, 80, 84, 193, 212, 218-220, 247, 254, 264, 275, 276, 278, 281, 284)
– Boston Dynamics robotics division (276)
– Chrome browser (275)
– Daydream virtual reality headset (275)
– Deep Dream (80, 219)
– DeepMind artificial intelligence division (264-265, 270, 276, 281)
– driverless cars (193, 220)
– Glass augmented reality headset (66, 73-74, 76-78, 80, 275)
– Home interface device (38-40)
– Image Search (218)
– Mail (275)
– Maps (24)
– Nest home automation division (275-276)
– Nest thermostat (275-276)
– Play (18)
– Plus social network (276)
– search results (212)
– Sidewalk Labs division (276)
Gladwell, Malcolm (237)
Glaser, Will (220)
Global Positioning System (4, 16, 21, 26, 51, 67)
Graeber, David (205)
Guangdong (179)
The Guardian (276)
Guattari, Félix (148)
Gu Li (265)

H
Hagakure (267)
Haldane, Andy (194)
Halo (game) (39)
Hannah-Arendt-Strasse (Berlin street) (70)
haptics (16)
Harman, Graham (48)
hash value (123-124, 128-130)
Hashcash (121)
hashing algorithm (123)
head-up displays (66-67)
Hearn, Mike (179)
“Heat List” (Chicago Police Department program) (230-231, 233, 235-236, 244)
heroin (228)
heterotopias (70)
high-density polyethylene plastic filament (HDPE) (99)
Hitachi Corporation (197)
Hollerith machines (61)
hooks, bell (311)
HR analytics (199)
Hungarian pengő (120, 122)

I
iaido (266)
iaijutsu (266)
IBM (263)
ideology of ease (42)
infrapolitics (311)
ING (bank) (262)
input neurons (215)
Instagram see Facebook
Institute of Advanced Architecture Catalunya (IAAC) (109)
intellectual property (IP) (104, 106, 281, 284)
intent recognition (227)
The Intercept (252)
International Harvester Scout (158)
International Labor Organization (ILO) (133)
International Mobile Equipment Identity number (IMEI) (4, 137)
International Monetary Fund (IMF) (122)
internet of things (31-62, 155-156, 209, 277, 285, 312)
– at the scale of the body (33-36)
– at the scale of the city (48-59)
– at the scale of the room (36-48)
– business models for (46)
– security vulnerabilities of (42-45)
Inventing the Future (88, 203)

J
Johnson, Eddie (235)
Jollibee fast-food chain (43)
Joyce, James (261)
jugaad (291)

K
Kabakov, Alexander (241)
Kaczynski, Theodore (310)
Kafka, Franz (160, 244)
Kanjoya (startup) (198)
Kasparov, Garry (263)
Kay, Alan (305)
Keikyu Corporation (198)
Kelly, Kevin (34)
Keynes, John Maynard (184)
Kickstarter (155)
Kuniavsky, Mike (31)
Kurgan, Laura (53)
kyriarchy (111)

L
Landless Workers’ Movement (Brazil) (169)
Lee Sedol (264-265, 268, 270)
lethal autonomous robotics (226)
Levitt, Steven D. (237)
Liberator 3D-printed pistol (108)
lidar (23)
Liss, Jo (268)
Lofland, Lyn (79)
logical positivism (52)
Los Angeles Police Department (LAPD) (229)
Lovecraft, H.P. (269)

M
Machii, Isao (266-267)
machine learning (8, 16, 60, 185, 192, 194, 209-257, 308)
maker spaces (93)
MakerBot (85, 88, 101, 104-105, 107)
mapping (22-25, 275, 278)
Mann, Steve (77-78)
Marx, Karl (70, 305)
MasterCard (120)
Mason, Paul (88)
Mauthausen concentration camp (61)
McDonald’s restaurant chain (194-195)
McDonough, William (96)
McNamara, Robert (57)
Merkle roots (123)
Metropolitan Police Service (London) (231)
Microsoft (38-39, 262, 275)
minimal techno (music genre) (221)
Minority Report (227, 230)
MIT Technology Review (243)
Mitte (Berlin neighborhood) (71-72)
Monobloc chair (106)
Monroe, Rodney (230)
Morris, David (256-257)
Moore’s Law (88, 93)
Mountain View, California (284)
M-Pesa digital currency (117)
Music Genome Project (220)
Musk, Elon (222)

N
National Institute of Justice (233)
National Public Radio (41, 192)
National September 11th Memorial (65)
National Technical University of Athens (173)
NAVSTAR Global Positioning System (21)
NBC Universal (220)
neural networks (214-216, 219, 264, 266)
Nevada (192)
New York City (51, 56-58, 136, 238)
The New York Times (177)
Next Rembrandt project (262-263, 265)
near-field communication standard (NFC) (17, 117)
Niantic Labs (65)
Niemeyer, Oscar (261)
Nieuwenhuys, Constant (190)
Niigata, Japan (301-302)
niqab (295)
Nixon Administration (204)
nonvolatile memory (15)
North Dakota (192)
Norwegian black metal (music genre) (221)
Nuit Debout protests (3)

O
Occupy movement (167, 169)
Oculus Rift virtual reality headset (82)
O’Neil, Cathy (249)
open source hardware (102)
OpenTable (39-40, 46)
Osborne, Michael A. (195)
Ostrom, Elinor (171)
output neuron (215)
overtransparency (240-241, 243)

P
Pai, Sidhant (98)
Pandora music service (220)
Panmunjom Truce Village (65)
Pareto optimality (55, 59)
Paris (1–6, 292)
Pasquale, Frank (244, 253)
path dependence (232, 299)
PayPal (120, 136, 220)
PCWorld (45)
People Analytics (198, 226, 232)
perceptron (214)
Père Lachaise cemetery (2, 5, 26)
persoonskaart (Dutch identity card) (60)
Pew Research Center (41, 193)
Pinellas County, Florida (256)
Placemeter (51)
polylactic acid plastic filament (PLA) (94, 98, 101)
Pokémon Go (63-65, 76, 79)
Polari (311)
policy network (264)
Pollock, Jackson (261)
Pony Express (256)
porosity (28, 173)
POSIWID (155, 302)
Postcapitalism (88)
power/knowledge (62)
predictive policing (227, 230, 232, 235)
PredPol (229, 231, 236, 244, 254)
proof-of-work (128-130, 140-141, 143, 290)
prosopagnosia see faceblindness
Protoprint (99-100, 102)
provisioning of mobile phone service (17, 56)
Průša, Josef (105)
psychogeography (40, 51)

Q
Quantified Self movement (33-36, 40)

R
Radical Networks conference (314)
radio frequency identification (RFID) (200, 296)
Radiohead (35)
RAND Corporation (56-58)
RATP (5)
recall (machine learning) (217, 234-235)
redboxing (229-230)
regtech (157)
Reich, Robert (196)
Relentless (265)
Rensi, Ed (195)
RepRap 3D printer (86-87, 93, 104-105, 306)
RER (2, 5)
Richelieu (62)
Rifkin, Jeremy (88, 205, 312)
RiteAid (197)
Riverton, Wyoming (63)
Royal Dutch Shell Long-Term Studies Group (287)

S
Samsung (285-286)
Sandvig, Christian (252)
“Satoshi Nakamoto” (115, 118, 147, 303)
scenario planning (287)
Schneier, Bruce (45, 243)
Scott, James C. (311)
SCUM Manifesto (191)
Seoul (6, 18, 54, 264-265, 284)
– Metro (54)
Sennett, Richard (111)
sentiment analysis (198)
Serra, Richard (70)
SHA-256 hashing algorithm (123)
Shenzhen Special Economic Zone (18-19, 43)
Shodan search engine (43)
Shoreditch (London neighborhood) (136)
Shteyngart, Gary (246)
Sidewalk Labs see Google
Siemens (52-54, 56)
Silk Road exchange (131)
Silver, David (265)
Simone, Nina (261)
Sipilä, Juha (204)
Sirer, Emin Gün (178)
Siri virtual assistant (39)
Situationism (64, 190)
Slock.it (156, 170, 175-176)
slow jam (music genre) (221)
Slum- and Shackdwellers International (169)
smart city (33, 48, 52, 52, 55, 59)
smart contracts (115, 147, 150, 153-157, 163, 166, 168, 170, 172, 306)
smart home (33, 36, 38, 46, 48)
smartphone (3, 8-33, 38, 49, 64, 67, 72, 77, 133, 137, 273, 285-286, 313)
– as “network organ” (27-29)
– as platform for augmented reality (67, 72)
– as platform for financial transactions (133, 137)
– environmental implications of (18-19)
– incompleteness at time of purchase (17)
– teardown of (14-16)
– ubiquity of (313)
smart property (149-153)
Smith, Zachary (103, 105)
Snæfellsjökull glacier (83)
Snaptrends (227-228, 231, 254)
Sobibor death camp (61)
“social credit” (China) (285, 311)
social dividend (204)
social media (26, 192, 227-228, 276, 286)
Sociometric Solutions (197)
Solanas, Valerie (191)
South Sea Company, the (165)
Soylent nutrient slurry (35)
SpatialKey (227)
Spielberg, Steven (227)
Spivak, Gayatri Chakravorty (311)
Srnicek, Nick (88, 90-91, 111, 190, 203, 205, 303)
“Stacks” (275, 277, 280-281, 283-286, 292-295, 299, 313-314)
Stanford Dogs Dataset (219)
Stanford University (283)
startups (13, 118, 137, 145-146, 280-282, 286)
Stavrides, Stavros (173)
Sterling, Bruce (275)
Stolpersteine (72, 74)
Stratasys (103-104, 108)
Summers, Larry (201)
Super Sad True Love Story (246)
Superstudio (191)
supervised learning (216)
SWaCH wastepickers’ collective (98-99)
Swedish death metal (music genre) (221)
SweepTheStreets (170)
Szabo, Nick (150, 303, 306)

T
Target (retail chain) (196)
Taylor,
– Frederick (35)
– Simon (160)
technolibertarians (140, 150, 283)
Tencent (285)
Tešanović, Jasmina (62)
Tesla (166, 193, 222-225, 243, 254, 264, 270, 285)
– Autopilot feature (222-225, 243, 254, 256, 270)
– Model S (222-224)
– Model X (222)
– operating system 7.0 (222)
tetrapods (301-307)
Theatro (196-197)
Theory of Self-Reproducing Automata (86)
“Theses on Feuerbach” (305)
Thiel, Peter (148)
Thingiverse (103, 105)
Tide laundry detergent (46-47)
Topography of Terror (Berlin museum) (70)
touchscreen (15-16, 38, 43, 194)
travel-to-crime (231)
Tual, Stephan (170)
Twitter (51, 137, 268)

U
Uber (4, 40, 41, 193, 245, 270, 276, 285, 293)
– driverless cars (193, 270)
Ultimaker 3D printer (88, 101, 104, 295)
United States Constitution (230, 235)
universal basic income (UBI) (203-205, 288, 292, 294)
universal constructor (86)
Universal Declaration of Human Rights (91)
University College London (85)
unnecessariat (181, 206, 297)
unsupervised deep learning (220)
Urban Dynamics (56)
Utrecht (204)

V
value network (264)
van Rijn, Rembrandt Harmenszoon (262)
Vélib (2)
Velvet Underground, the (228)
Venezuelan bolívar (122)
Venmo (41)
Verlan (311)
Virginia Company, the (165)
virtual assistants (38, 41-42, 286)
virtual reality (65, 82-83, 275, 296)
Visa (120, 136, 159)
Vitality (36)
Vkontakte (241)
von Furstenberg, Diane (84)
von Neumann, John (86)

W
“wake word” (interface command) (41)
Washington State (192)
Waterloo University (148)
Watt, James (104)
Wendy’s (197)
Wernick, Miles (233)
Westegren, Tim (220)
Western Union (120)
WhatsApp (281)
Whole Earth Review (34)
WiFi (11, 17, 25, 46, 66)
Wiggins, Shayla (63-65)
WikiLeaks (120, 137)
Williams,
– Alex (190, 203)
– Raymond (315)
Wilson, Cody (108, 111)
Winograd Schema (270)
The Wire (54)
Wired magazine (34)
Wolf, Gary (34)
World Bank (133)
World Economic Forum (194)

Y
Yahoo (219)
yamato-damashii (267)
Yaskawa Motoman MH24 industrial robot (266)

Z
Zamfir, Vlad (177)
Zen Buddhism (34, 284)
ZeroBlock application (131)
The Zero Marginal Cost Society (88, 205)

Radical Technologies: The Design of Everyday Life, now available for pre-order

The other night I selected-all in a file on Google Docs and turned the entire text bright red. This was my signal to my editor Leo that I’d made the final round of edits on the last outstanding chapter I owed him. And this, in turn, means that after eight years and eleven months, I’m finally done with the project I started in this blog post. I’ve finished my book.

It is, in too many ways to count, a different book from the one I set out to write. I owe most of this to Leo, actually. Do you know the scene in Inception where Joseph Gordon-Levitt and Tom Hardy, as intruders in the virtual world of another man’s mind, are under assault by the ghostly brigades of their subject’s “militarized subconscious”? Gordon-Levitt’s character is standing at the door of a warehouse, plinking away ineffectually at the encroaching horde with an assault rifle, when Hardy shoulders him aside. With the words, “You mustn’t be afraid to dream a little bigger, darling,” he hoists a massive South African grenade launcher, lobs a round onto the opposite rooftop, and blows things up reeeeal good.

That was Leo. I came to him with a book about cities and technology — a book that had been dangling out in public for six years at that point, a book I’d already published a quarter of — and two chapters into our work on it, he pulled a Hardy on me, in the biggest possible way. “I don’t think you’re writing a book about cities anymore,” he told me, over stand-up espressos beneath the awning of the Algerian Coffee Stores, as drizzle dampened the greasy Soho asphalt. “I think you’re writing a book about Everyday Life.”

I could hear the capital letters, and knew immediately (as my bowels turned to ice) that he was invoking the whole tradition of thought that starts in Michel de Certeau and Henri Lefebvre. Which is to say that he wasn’t simply asking me to paint on a bigger canvas, though he was definitely doing that. He was demanding that I take myself and my work seriously, and understand that what I was writing might someday find its place on a shelf alongside people who had actually contributed to Western thought and culture. (In Lefebvre’s case, rather explosively, given his influence on the events of May ’68.)

It put the zap on my head so hard that I didn’t get any further work done on the book for a good six months.

I don’t know what it’s like for you. I won’t presume to say I understand anyone else’s interiority, or process, or approach to their work. I imagine that there are some creators who are safely armored by a transcendent belief in their own talent, who glide through pitches and contracts and reviews lubricated by a sense of inevitability and rightness. I’m not one of those people.

So in a way, what Leo did to me was cruel. But it also led directly to a change of title, a change of scope, and a much bigger and more ambitious book. What had started out as a rather constrained proposition turned into a sprawling survey of some of the major ways in which networked information technologies shape the choices arrayed before us. I should be clear that it probably misses as much as it gets right; I have a sustained history of focusing too much on the wrong aspects of a technology, or at least not the aspects that turn out to be most salient to our understanding of it, and I’m not sure it’s any different here.

I’m also a little gutted to have written a book that’s so obviously and prominently about information technology. As I’d originally envisioned it, this was supposed to be a decisive pivot away from all of that, and toward the thing I care more deeply about, which is the life of cities. But as Nurri always reminds me, there are any number of writers in the world who have deeper or more original insight into cities. It just isn’t what people seem to want from me. After awhile, if you’re smart, you listen to what the world tells you about what it wants from you, with intense gratitude that it appears to want anything at all.

So: Radical Technologies: The Design of Everyday Life, now available for pre-order.

In its ten chapters, I take up some of the recent and emerging technical developments that now condition the way we experience the everyday, just about everywhere on Earth. I start with the smartphone, ready-to-hand as it is, and continue on to augmented reality; the so-called internet of things; 3D printing, CNC milling and other digital fabrication technologies; cryptocurrency and the technology underlying it, the blockchain; and finally the constellation of practices and ideas that is dedicated to the eclipse of human discretion, and includes machine learning, the automation of work and artificial intelligence. I spend some time considering the ways in which these discrete techniques are brought together in particular ensembles and commercial value propositions — and by whom, and particularly toward what ends — and finish up by asking if there’s a space for tactics or even resistance available to us in any of this. All in all, I think it’s turned out rather well.

Most writers say something along these lines, but it’s really true and I really do mean it: though I take full responsibility for whatever infelicities and misapprehensions remain, just about all the good in this book arises from the conversations I’ve had with you. It’s not — and I’m not — Lefebvre, but that’s OK. It’s not half-bad. I don’t think I’ll ever stop being grateful.

I’m rather fond of the title, by the way. It’s ambitious, a title to conjure with. It has a certain amount of what the Rastafarians used to call Dread. I don’t know if the book I’ve written really deserves a title like that, but I guess you’ll let me know, won’t you?

Thanks to those of you who came along for the ride — especially those who’ve stuck with me all the way from that first blog post, when I was promising you a self-published book called The City Is Here For You To Use, and it was 90% a reaction to the incompetence of my first publisher. Thanks doubly to the 859 of you (!) who ponied up to pre-order that book, most of you in the weeks immediately following the project’s announcement, and who had to wait until the last quarter of 2013 to get your hands on anything resembling the thing you’d ordered. Thanks, eternal thanks, to Leo Hollis, for kicking out the jams. And thanks always to Nurri for sticking with me through all the chicanes and blind alleys of this endless, endless project. Let’s see what happens now.

“What Shapes The City?”: Upcoming talk at University of Toronto, November 21st

Just want to give you a real quick heads-up on a talk I’m pretty jazzed about: on November 21st, I’ll be speaking at an event called “What Shapes The City?,” at the architecture school of the University of Toronto.

What’s got me so amped for this? Well, did you happen to notice who I’m speaking with? Oh, this is going to be gooooood. [chortles, rubs hands] See you there!

Can you smell what I’m cooking?

This here’s the bibliography I put together for the last chapter of my Radical Technologies: The Design of Everyday Life, forthcoming from Verso. I think it will probably give you a decent idea what I’m on about in this section of the book.

UPDATE: Dang, I just noticed that my copy-and-paste out of Scrivener failed to pick up three further citations. They are:

Powell, Alison. “Algorithms, accountability, and political emotion: On the cultural assumptions underpinning sentiment analysis,” London School of Economics Impact of Social Sciences blog, July 20th, 2016.

Shteyngart, Gary. Super Sad True Love Story: A Novel, New York: Random House, 2010.

Yaskawa Electric Corporation. “YASKAWA BUSHIDO PROJECT: Industrial robot vs sword master,” June 4th, 2015.

1 Keynes, John Maynard. “Economic Possibilities for our Grandchildren,” The Nation and Athenaeum, Vol 48 Issues 2 & 3, October 11th & 18th, 1930.

2 Economic Report of the President, February 2016. Washington DC: Government Printing Office, 2016.

3 O’Reilly, Tim. “Managing the Bots That Are Managing the Business,” MIT Sloan Management Review, May 31st, 2016.

4 McEleny, Charlotte. “McCann Japan hires first artificially intelligent creative director,” The Drum, March 29th, 2016.

5 Bostrom describes a quiverfull of these as “decision trees, logistic regression models, support vector machines, naive Bayes, [and] k-nearest neighbor regression, among others.” Bostrom, Nick. Superintelligence: Paths, Dangers, Strategies, Oxford, UK: Oxford University Press, 2014.

6 Mick, Jason. “Foxconn Billionaire Hints at Robotic Apple Factory, Criticizes Dead Employees,” DailyTech, June 30th, 2014.

7 An advertisement for Columbia/Okura palletizing robots touts, even ahead of their “surprising affordability,” the fact that they “eliminate costly stacking-related injuries.”

8 International Labor Organization. “Global Wage Report, 2014/2015,” December 5th, 2014.

9 Chamayou, Grégoire. Drone Theory, London: Penguin, 2015; Singer, P.W. Wired for War: The Robotics Revolution and Conflict in the 21st Century, New York: Penguin Press, 2009.

10 United States Department of Health and Human Services, Centers for Disease Control and Prevention. “Motor Vehicle Crash Deaths,” July 6th, 2016.

11 United States Department of Transportation, National Highway Traffic Safety Administration. “Critical Reasons for Crashes Investigated in the National Motor Vehicle Crash Causation Survey,” February 2015. See also Bryant Walker Smith’s comprehensive review of causation statistics.

12 United States Department of Transportation, National Highway Traffic Safety Administration. “Economic and Societal Impact Of Motor Vehicle Crashes, 2010 (Revised),” May 2015.

13 Grossman, Lt. Col. Dave. On Killing: The Psychological Cost of Learning to Kill In War and Society, London: Little, Brown, 1995.

14 The reality of the US remote assassination program is comprehensively detailed in The Intercept, “The Drone Papers,” October 15th, 2015.

15 Gonzales, Daniel and Sarah Harting, “Designing Unmanned Systems With Greater Autonomy,” Santa Monica: RAND Corporation, 2014; United Nations General Assembly. “Report of the Special Rapporteur on extrajudicial, summary or arbitrary executions: Lethal Autonomous Robotics and the protection of life,” April 9th, 2013. For a poignant, if chilling, depiction of an autonomous combat system nearing the threshold of self-awareness, see Watts, Peter. “Malak,” rifters.com, 2010.

16 American Civil Liberties Union, “War Comes Home: The Excessive Militarization of American Policing,” June 2014. See also Else, Daniel H. “The ‘1033 Program,’ Department of Defense Support to Law Enforcement,” Congressional Research Service, August 28th, 2014.

17 Williams, Alex and Nick Srnicek, “#ACCELERATE MANIFESTO for an Accelerationist Politics,” Critical Legal Thinking, May 14th, 2013.

18 Novara Media. “Fully Automated Luxury Communism,” podcast, June 2015.

19 Yeoman, Ian and Michelle Mars. “Robots, Men and Sex Tourism,” Futures Vol. 44, May 2012: pp. 365-371.

20 Firestone, Shulamith. The Dialectic of Sex, New York: Bantam Books, 1971.

21 Solanas, Valerie. SCUM Manifesto, New York: Olympia Press, 1968.

22 Kitchin, Rob. The Data Revolution: Big Data, Open Data, Data Infrastructures & their Consequences, London: Sage Publications, 2014.

23 Rosenberg, Daniel. ”Data Before The Fact,” in Gitelman, Lisa, ed., “Raw Data” Is An Oxymoron, Cambridge, MA: MIT Press, 2013.

24 Readers who would like to pursue these questions in greater depth are directed to the excellent Critical Algorithm Studies reading list maintained by Tarleton Gillespie and Nick Seaver of Microsoft Research’s Social Media Collective.

25 A more rigorous and detailed, though still accessible, history of artificial intelligence research can be found in Bostrom 2014 op. cit.

26 This history is fantastic.

27 Barr, Alistair. “Google Mistakenly Tags Black People as ‘Gorillas,’ Showing Limits of Algorithms,” The Wall Street Journal, July 1st, 2015.

28 Khosla, Aditya et al. “Novel dataset for Fine-Grained Image Categorization,” First Workshop on Fine-Grained Visual Categorization, IEEE Conference on Computer Vision and Pattern Recognition, 2011.

29 ImageNet. “Large Scale Visual Recognition Challenge 2012.”

30 Stavens, David M. “Learning to Drive: Perception for Autonomous Cars,” Ph.D dissertation, Stanford University Department of Computer Science, May 2011.

31 Bui, Quoctrung. “Map: The Most Common* Job In Every State,” National Public Radio, February 5th, 2015.

32 Musk, Elon. “Master Plan, Part Deux,” July 20th, 2016.

33 See the site of Amazon’s fully-owned robotics subsidiary, and the video of one of its warehouses in operation.

34 Pew Research Center. “Digital Life in 2025: AI, Robotics and the Future of Jobs,” August 6th, 2014.

35 In fairness, while nobody invokes the Bui map directly, several of Pew’s respondents did point out that truck driver is the number-one occupation for men in the United States, and that alongside taxi drivers, current holders of the job would be among the first to be entirely displaced by automation. The Gartner research firm takes a still harder line, predicting that one in three workers will be displaced by robotics or artificial intelligence by 2025. See Thibodeau, Patrick. “One in three jobs will be taken by software or robots by 2025,” ComputerWorld, October 6th, 2014.

36 Frey, Carl Benedikt and Michael A. Osborne. “The Future of Employment: How Susceptible Are Jobs To Computerisation?,” Oxford Martin Program on the Impacts of Future Technology, September 17th, 2013.

37 Frey, Carl Benedikt et al. “Technology At Work v2.0: The Future Isn’t What It Used To Be,” Citi Global Perspective & Solutions, January 2016.

38 World Economic Forum, “The Future of Jobs Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution,” January 18th, 2016.

39 Elliott, Larry. “Robots threaten 15m UK jobs, says Bank of England’s chief economist,” The Guardian, November 12th, 2015.

40 Kasperkevic, Jana. “McDonald’s CEO: robots won’t replace workers despite tech opportunities,” The Guardian, May 26th, 2016.

41 Machkovech, Sam. “McDonald’s ex-CEO: $15/hr minimum wage will unleash the robot rebellion,” Ars Technica, May 25th, 2016.

42 Soper, Spencer. “Inside Amazon’s Warehouse,” Lehigh Valley Morning Call, September 18th, 2011. For a comparable and equally disturbing look at the conditions Amazon’s white-collar workers contend with, see Kantor, Jodi and David Streitfeld, “Inside Amazon: Wrestling Big Ideas in a Bruising Workplace,” The New York Times, August 25th, 2015.

43 Kosner, Anthony Wing. “Google Cabs And Uber Bots Will Challenge Jobs ‘Below The API’,” Forbes, February 4th, 2015.

44 Silverman, Stuart. “Target’s Cashier Game – Is It Really a Game?,” LevelsPro, November 29th, 2011.

45 Frucci, Adam. “Target Makes Cashiering More Tolerable By Turning It Into a Game,” Gizmodo, December 8th, 2009.

46 Theatro. “The Container Store Enhances Customer Experience and Operational Productivity with Nationwide Rollout of Theatro’s Voice-Controlled Wearable,” June 14th, 2016.

47 Yano, Kazuo et al. “Measurement of Human Behavior: Creating a Society for Discovering Opportunities,” Hitachi Review Vol. 58, No. 4, 2009, p. 139.

48 Hitachi Ltd. “Business Microscope Identifies Key Factors Affecting Call Center Performance,” July 17th, 2012.

49 Lohr, Steve. “Unblinking Eyes Track Employees,The New York Times, June 21st, 2014.

50 Deleuze, Gilles. “Postscript on the Societies of Control,” October Vol. 59. (Winter, 1992), pp. 3-7.

51 Poole, Steven. “Why the cult of hard work is counter-productive,” The New Statesman, December 11th, 2013.

52 Streitfeld, David. “Data-Crunching Is Coming to Help Your Boss Manage Your Time,” The New York Times, August 17th, 2015.

53 Ganeva, Tana. “Biometrics at Pizza Hut and KFC? How Face Recognition and Digital Fingerprinting Are Creeping Into the U.S. Workplace,” AlterNet, September 26th, 2011.

54 Downie, James. “Japanese railway company scanning employees’ smiles,” Foreign Policy, July 7th, 2009.

55 Payne, Brian, Colin Sloman and Himanshu Tambe, “IQ plus EQ: How technology will unlock the emotional intelligence of the workforce of the future,” Accenture Strategy, January 7th, 2016. See also Hochschild, Arlie Russell. The Managed Heart: Commercialization of Human Feeling, Oakland: University of California Press, 1983.

56 BetterWorks Systems, Inc. Website, 2016.

57 Burt, Ronald S. “Structural Holes and Good Ideas,” American Journal of Sociology, Vol 110 Number 2, 2004, pp. 349-399.

58 Bicknell, David. “Sloppy human error still prime cause of data breaches,” Government Computing, June 2nd, 2016.

59 Baker, Dean. “The Job-Killing Robot Myth,” Center for Economic Policy Research, May 6th, 2015.

60 Blunden, Mark. “Enfield Council uses robotic ‘supercomputer’ instead of humans to deliver frontline services,” Evening Standard, June 16th, 2016.

61 Hongo, Jun. “Fully Automated Lettuce Factory to Open in Japan,” The Wall Street Journal, August 21st, 2015.

62 Tankersley, Jim. “Robots are hurting middle class workers, and education won’t solve the problem, Larry Summers says,” The Washington Post, March 3rd, 2015.

63 Dyer-Witheford, Nick. Cyber-Marx: Cycles and Circuits of Struggle in High-technology Capitalism, Urbana: University of Illinois Press, 1999. See also Summers, Lawrence H. “The Inequality Puzzle,” Democracy, Summer 2014 No. 33. 

64 Graeber, David. “On the Phenomenon of Bullshit Jobs,” STRIKE!, August 17th, 2013.

65 Van Trier, Walter. “Who Framed ‘Social Dividend’?,” USBIG Discussion Paper No. 26, March 2002. See also Danaher, John. “Libertarianism and the Basic Income (Part One),” Philosophical Disquisitions, December 17th, 2013; Gordon, Noah. “The Conservative Case for A Guaranteed Basic Income,” The Atlantic, August 2014.

66 Alberti, Mike and Kevin C. Brown. “Guaranteed income’s moment in the sun,” Remapping Debate, April 24th, 2013; Bregman, Rutger. “Nixon’s Basic Income Plan,” Jacobin, May 5th, 2016.

67 Grice, Will. “Finland plans to give every citizen 800 euros a month and scrap benefits,” The Independent, December 6th, 2015; Hamilton, Tracy Brown. “The Netherlands’ Upcoming Money-for-Nothing Experiment,” The Atlantic, June 21st, 2016.

68 See the archives of the Waterfront Workers History Project.

69 Siegel, Jenifer Z. and Molly J. Crockett. “How serotonin shapes moral judgement and behavior,” Annals of the New York Academy of Sciences, September 2013; 1299(1): pp. 42–51.

70 Danaher, John. “Will life be worth living in a world without work? Technological Unemployment and the Meaning of Life,” Science and Engineering Ethics, forthcoming.

71 Arendt 1958 op. cit.

72 Zeeberg, Amos. “Alienation Is Killing Americans and Japanese,” Nautilus, June 1st, 2016.

73 United Nations General Assembly, op cit.

74 Greenfield, Adam. “Against the smart city,” New York: Do projects, 2013.

75 I have often remarked on this propensity in the past, in just about so many words, not least in my 2013 pamphlet cited above. I point it out again here because it keeps happening, equally word-for-word. Some reflexes are apparently immune to mockery.

76 See image.

77 Kelley, Richard et al. “Context-Based Bayesian Intent Recognition,” IEEE Transactions on Autonomous Mental Development, Volume 4 Number 3, September 2012.

78 Socher, Richard et al. “Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank,” Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1631–1642, Stroudsburg, PA, October 2013.

79 Sullivan, Bob. “Police sold on Snaptrends, software that claims to stop crime before it starts,” bobsullivan.net, September 4th, 2014.

80 Ibid.

81 Mirani, Leo. “Millions of Facebook users have no idea they’re using the internet,” Quartz, February 9th, 2015.

82 Huet, Ellen. “Server And Protect: Predictive Policing Firm PredPol Promises To Map Crime Before It Happens,” Forbes, February 11th, 2015.

83 Ibid.

84 Mitchell, Robert L. “Predictive policing gets personal,” ComputerWorld, October 24th, 2013.

85 Stanley, Jay. “Chicago Police ‘Heat List’ Renews Old Fears About Government Flagging and Tagging,” American Civil Liberties Union, February 25th, 2014.

86 McCarthy, Garry F., Superintendent of Police, City of Chicago. “Custom Notifications In Chicago — Pilot Program,” Chicago Police Department Directive D13-09, July 7th, 2013.

87 Callahan, Yesha. “Chicago’s Controversial New Police Program Prompts Fears Of Racial Profiling,” Clutch, February 2014.

88 On January 6th, 2014, the Chicago Police Department Office of Legal Affairs denied Freedom of Information Act request 14-0023, which had sought information pertaining to the Heat List program, on grounds that its disclosure would “endanger the life or physical safety of law enforcement personnel or any other person.”

89 The problem of police misconduct is so pervasive and of such long standing in the city that the Chicago Tribune website maintains a standing category dedicated to it. (Not all of the articles linked concern the Chicago police, but the great majority do.) A representative article is Sweeney, Annie. “Chicago doesn’t discipline rogue cops, scholar testifies in bar beating trial,” Chicago Tribune, October 24th, 2012.

90 Ackerman, Spencer. “The disappeared: Chicago police detain Americans at abuse-laden ‘black site’,” The Guardian, February 24th, 2015.

– “Homan Square revealed: how Chicago police ‘disappeared’ 7,000 people,” The Guardian, October 19th, 2015.

91 Clark, Matthew and Gregory Malandrucco. “City of Silence,” Vice, December 1st, 2014.

92 Accenture. “London Metropolitan Police Service and Accenture Police Solutions Complete Analytics Pilot Program to Fight Gang Crime,” 2015.

93 Ibid.

94 Berg, Nate. “Predicting crime, LAPD-style,” The Guardian, June 25th, 2014.

95 Brantingham, Paul J. and Patricia L. Brantingham. “Notes on the geometry of crime,” In P.J. Brantingham and P.L. Brantingham eds., Environmental Criminology, Beverly Hills, CA: Sage Publications, 1981. See also Eck, John E. and David Weisburd. “Crime Places In Crime Theory,” In J. Eck, J. and D. Weisburd eds., Crime And Place. Crime Prevention Studies No. 4., Monsey, NY: Criminal Justice Press, 1995 and Hodgkinson, Sarah and Nick Tilley. “Travel-to-Crime: Homing In On The Victim,” International Review of Victimology Vol. 14, pp. 281–298, 2007.

96 Stroud, Matt. “The minority report: Chicago’s new police computer predicts crimes, but is it racist?,” The Verge, February 19th, 2014.

97 Davey, Monica. “Chicago Police Try to Predict Who May Shoot or Be Shot,” The New York Times, May 23rd, 2016; Robinson, David. “Chicago police have tripled their use of a secret, computerized ‘heat list,’” EqualFuture, May 26th, 2016.

98 Davey 2016 op. cit.

99 Ferguson, Andrew Guthrie. “Policing Predictive Policing,” Washington University Law Review, Vol. 94, 2017.

100 My account here is indebted to the reporting a team of journalists with the FiveThirtyEight blog conducted⁠ in collaboration with the Marshall Project.

101 Visher, Christy A. “Transitions From Prison To Community: Understanding Individual Pathways,” The Urban Institute, Justice Policy Center, Washington, DC., 2003.

102 Langan, Patrick A. and David J. Levin. “Recidivism of Prisoners Released in 1994.” Washington, DC: U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics, 2002.

103 Barry-Jester, Anna Maria, Ben Casselman and Dana Goldstein.“The New Science of Sentencing,” The Marshall Project, August 4th, 2015.

104 Hardt, Moritz. ”How big data is unfair: Understanding sources of unfairness in data-driven decision-making,” Medium, September 26th, 2014.

105 Angwin, Julia et al. “Machine Bias,” Pro Publica, May 23rd, 2016.

106 Carson. E. Ann. Prisoners in 2014, Washington DC: US Department of Justice Bureau of Justice Statistics, September 2015.

107 Humes, Karen R., Nicholas A. Jones and Roberto R. Ramirez. “Overview of Race and Hispanic Origin: 2010,” US Census Bureau, March 2011.

108 Palamar, Joseph J., et al. “Powder cocaine and crack use in the United States: An examination of risk for arrest and socioeconomic disparities in use,” Drug & Alcohol Dependence, Vol 149, April 1st, 2015, pp 108-116.

109 Tett, Gillian. “Mapping crime – or stirring hate?”, The Financial Times, August 22nd, 2014.

A line in Tett’s FT coverage of the CPD’s precrime initiative is also inadvertently revealing: ”Thus the police can be in the right spot, at the right time, even when resources are being cut due to fiscal austerity.” This is, again, one of those bizarre, almost non sequitur introjections of a neoliberal justificatory logic that seem to crop up so often in discussions of information technology. Apparently it didn’t interest Tett to ask if it might not be cheaper or more effective to avoid eliminating those policing resources in the first place.

110 State of Michigan Department of Technology, Management & Budget, Contract 071B3200096, January 11th, 2011. See Change Notice Number 8, effective January 26th, 2016.

111 Anderson, Ben. “Preemption, precaution, preparedness: Anticipatory action and future geographies,” Progress in Human Geography 34.6 (2010): pp. 777-798.

112 Donohue, John J. III and Steven D. Levitt. “The Impact of Legalized Abortion on Crime,” The Quarterly Journal of Economics, Volume CXVI, Issue 2, May 2001.

113 Rosenberg, Daniel. “Data before the Fact,” in Gitelman, Lisa, ed. “Raw Data” Is An Oxymoron, Cambridge: The MIT Press, 2013. See also Poovey, Mary. A History of The Modern Fact: Problems of Knowledge In The Sciences of Wealth and Society, Chicago: University of Chicago Press, 1998.

114 Eno, Brian and Peter Schmidt. Oblique Strategies: Over One Hundred Worthwhile Dilemmas, London: Opal Ltd., January 1975.

115 Ricanek Jr., Karl and Chris Boehnen. “Facial Analytics: From Big Data to Law Enforcement,” Computer Volume 45, Number 9, September 2012.

116 Arthur, Charles. “Quividi defends Tesco face scanners after claims over customers’ privacy,” The Guardian, November 4th, 2013.

117 Sethuram, Amrutha et al. “Facial Landmarking: Comparing Automatic Landmarking Methods with Applications in Soft Biometrics,” Computer Vision – ECCV 2012, October 7th, 2012.

118 Butler, Judith. Gender Trouble: Feminism and the Subversion of Identity, New York and London: Routledge, 1990.

119 Khryashchev, Vladimir et al. “Gender Recognition via Face Area Analysis,” Proceedings of the World Congress on Engineering and Computer Science 2012 Volume 1, October 24, 2012.

120 Greenfield, Adam. Everyware: The dawning age of ubiquitous computing, Berkeley: New Riders, 2006.

121 Venkatesh, Sudhir Alladi. Off The Books: The Underground Economy of the Urban Poor, Cambridge, MA: Harvard University Press, 2006.

122 Tonkiss, Fran. “Informality and its discontents,” in Angélil, Marc and Rainer Hehl, eds., Informalize!: Essays on the Political Economy of Urban Form. Berlin: Ruby Press, 2012.

123 The Digital Matatus Project. “Digital Matatus: Collaborative Mapping For Public Transit Everywhere,” 2015.

124 Williams, Sarah. Personal communication, November 11th, 2013.

125 Scott, James C. Seeing Like A State: How Certain Schemes to Improve the Human Condition Have Failed, New Haven: Yale University Press, 1998.

126 Wa Mungai, Mbugua. Nairobi’s Matatu Men: Portrait Of A Subculture, Nairobi: Goethe-Institut Kenya, 2013.

127 Walker, Shaun. “Face recognition app taking Russia by storm may bring end to public anonymity,” The Guardian, May 17th, 2016.

128 Rothrock, Kevin. “The Russian Art of Meta-Stalking,” Global Voices Advox, April 7th, 2016.

129 Russon, Mary-Ann. “Russian trolls outing porn stars and prostitutes with neural network facial recognition app,” International Business Times, April 27th, 2016.

130 Lin, Weiyao, et al. “Group event detection for video surveillance,” 2009 IEEE International Symposium on Circuits and Systems, May 24th, 2009.

131 Hu, Nan, James Decraene and Wentong Cai. “Effective crowd control through adaptive evolution of agent-based simulation models,” Proceedings of the 2012 Winter Simulation Conference, December 9th, 2012. 10.1109/WSC.2012.6465040

Park, Andrew J. et al. “A Decision Support System for Crowd Control Using Agent-Based Modeling and Simulation,” 2015 IEEE International Conference on Data Mining Workshop, November 14th, 2015. http://dx.doi.org/10.1109/ICDMW.2015.249

132 Torrens, Paul. Personal conversation, April 14th, 2008. See also  http://www.geosimulation.org/riots.html

133 Greenfield 2013 op. cit.

134 Difallah, Djellel Eddine, Philippe Cudré-Mauroux and Sean A. McKenna. “Scalable Anomaly Detection for Smart City Infrastructure Networks,” IEEE Internet Computing, Volume 17 Number 6, November-December 2013.

135 Knight, Will. “Baidu Uses Map Searches To Predict When Crowds Will Get Out Of Control,” MIT Technology Review, March 24th, 2016.

136 Schneier, Bruce. “Technologies of Surveillance,” March 5th, 2013.

137 Canetti, Elias. Crowds and Power, New York: Farrar, Straus and Giroux, 1984.

138 Pasquale, Frank. The Black Box Society: The Secret Algorithms Behind Money and Information, Cambridge, MA: The Harvard University Press, 2015.

139 Though even here there is increasing pressure to use algorithmic guidelines in the selection of applicants, or at least in crafting the terms they will differentially be offered. See McGrath, Maggie. “The Invisible Force Behind College Admissions,” Forbes, July 30th, 2014.

140 Dwoskin, Elizabeth. “Lending Startups Look at Borrowers’ Phone Usage to Assess Creditworthiness,” The Wall Street Journal, November 30th, 2015.

141 Traub, Amy. “Discredited: How Employment Credit Checks Keep Qualified Workers Out Of A Job,” Demos, March 4th, 2013.

142 Dwoskin 2015 op.cit. See also Andrews, Lori. I Know Who You Are And I Saw What You Did, New York: Free Press, 2011.

143 This is Marilyn Strathern’s rather more accessible gloss of Goodhart’s original statement, “Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” Strathern, Marilyn. “‘Improving ratings’: audit in the British University system,” European Review Volume 5 Issue 3, July 1997, pp 305-321. See also Simon, David, Kia Corthron, Ed Burns and Chris Collins, The Wire, Season 4 Episode 9: “Know Your Place,” first aired 12 November 2006.

144 United States Federal Trade Commission. “Your Equal Credit Opportunity Rights,” January 2013.

145 O’Neil, Cathy. “Summers’ Lending Club makes money by bypassing the Equal Credit Opportunity Act,” Mathbabe, August 29th, 2013.

146 Lobosco, Katie. “Facebook friends could change your credit score,” CNN Money, August 27th, 2013.

147 Ibid.

148 Goodman, Bryce and Seth Flaxman. “EU regulations on algorithmic decision-making and a “right to explanation,” 2016 ICML Workshop on Human Interpretability in Machine Learning, New York.

149 Kroll, Alice and Ernest A. Testa. “Predictive Modeling for Life Underwriting,” Predictive Modeling for Life Insurance Seminar, May 19th, 2010.

150 Recall Karl Rove: “We’re an empire now, and when we act, we create our own reality. And while you’re studying that reality — judiciously, as you will — we’ll act again, creating other new realities, which you can study too, and that’s how things will sort out. We’re history’s actors…and you, all of you, will be left to just study what we do.” Suskind, Ron. “Faith, Certainty and the Presidency of George W. Bush,” The New York Times, October 17th, 2004.

151 Tabarrok, Alex. “The Rise of Opaque Intelligence,” Marginal Revolution, February 20th, 2015.

152 Stafford-Fraser, Quentin. Facebook comment, June 2016.

153 Mannon, Travis. “Facebook Outreach Tool Ignores Black Lives Matter,” The Intercept, June 9th, 2016.

154 This is easier to do than it is to explain.

155 Murphy, David. “Amazon Algorithm Price War Leads to $23.6-Million-Dollar Book Listing,” PC, April 23rd, 2011.

156 United States Commodity Futures Trading Commission and Securities and Exchange Commission. “Findings Regarding The Market Events of May 6, 2010,” September 30th, 2010.

157 United States Securities and Exchange Commission.“SEC Approves New Stock-by-Stock Circuit Breaker Rules,” Press Release 2010-98, June 10th, 2010.

158 Tesla Motors, Inc. “Your Autopilot Has Arrived.” October 14th, 2015.

159 Davies, Alex. “The Model D is Tesla’s Most Powerful Car Ever, Plus Autopilot,” Wired, October 10th, 2014.

160 Lavrinc, Damon. “Tesla Auto-Steer Will Let Drivers Go From SF To Seattle Hands-Free,” Jalopnik, March 19th, 2015.

161 Fingas, Roger. “‘Apple Car’ rollout reportedly delayed until 2021, owing to obstacles in ‘Project Titan,’AppleInsider, July 21st, 2016.

162 Yadron, Danny and Dan Tynan. “Tesla driver dies in first fatal crash while using autopilot mode,” The Guardian, July 1st, 2016.

163 Musk, Elon. Tweet, April 17th, 2016.

164 Tesla Motors, Inc. “A Tragic Loss,” June 30th, 2016.

165 Tesla Motors, Inc. “Misfortune,” July 6th, 2016.

166 Lambert, Fred. “Google Deep Learning Founder says Tesla’s Autopilot system is ‘irresponsible’,” Electrek, May 30th, 2016.

167 Bourré, August C. Comment, Speedbird blog, May 28th, 2014.

168 Morris, David Z. “Trains and self-driving cars, headed for a (political) collision,” Fortune, November 2nd, 2014.

169 Americans For Prosperity Florida. “Economic Freedom Scorecard: 2016 Legislative Session,” May 3rd, 2016.

170 Hawkins, Jeff. Keynote speech, “Why Can’t a Computer Be More Like a Brain? How a New Theory of Neocortex Will Lead to Truly Intelligent Machines,” O’Reilly Emerging Technology Conference 2007, San Diego, CA, March 27th, 2007.

171 The Next Rembrandt project. Website, undated.

172 Silver, David, et al. “Mastering the game of Go with deep neural networks and tree search,” Nature, Volume 529, Issue 7587, pp. 484–489, January 28th, 2016.

173 An, Younggil and David Ormerod. Relentless: Lee Sedol vs Gu Li, Go Game Guru, 2016.

174 Nature Video, “The computer that mastered Go,” January 27th, 2016.

175 Ormerod, David. “AlphaGo shows its true strength in 3rd victory against Lee Sedol,” Go Game Guru, March 12th, 2016.

176 See Machii’s official website.

177 Metz, Cade. “The Sadness and Beauty of Watching Google’s AI Play Go.” Wired, March 11th, 2016.

178 Liss, Jo. Tweet, December 8th, 2015. The tweets that follow are a cogent argument as well.

179 Levesque, Hector J., Ernest Davis and Leora Morgenstern. “The Winograd Schema Challenge,” Proceedings of the Thirteenth International Conference on Principles of Knowledge Representation and Reasoning, 2012.

180 Salthouse, Timothy A. “When does age-related cognitive decline begin?,” Neurobiology of Aging, April 2009, Volume 30, Issue 4, pp. 507–514.

On the Master Bullshit Matrix

The following is a very lightly edited version of something I wrote for the newsletter I published on a weekly basis all through 2015. I always understood these pieces as ephemera, and so my policy was that there would be no persistent archive of them, and no way for anyone to read a weekly entry they hadn’t received by virtue of being subscribed to the newsletter at the time it was published. They were strictly of and for the moment.

I still think that was a sound policy. But not a week goes by that someone doesn’t ask me to repost the following, and in the interest of saving everyone some time I figured I’d do so here. For reasons that I cannot fathom, it remains the single most-requested among the sixty-odd newsletters I published last year. Usual disclaimers apply, but I hope you enjoy it.

Many of you will recall that for the two years before we moved to London, I was in the habit of convening drinks every Friday night at Temple Bar on Lafayette Street. This standing get-together, imaginatively dubbed FRIDAYS AT 7, remains one of the best things I’ve ever been involved with. I still derive an enormous amount of satisfaction out of having brought this particular assortment of people together, still glow from the memory of a great many great nights, and to this day try to arrange a FATSEVEN gathering whenever I happen to be in New York City for more than 48 hours or so.

But it also taught me something very deep about the nature of human socialization. You should know that I inherit from my mother a profound tendency to want to please everyone I’m interacting with, at least in certain contexts — even when there are more than two people involved, even when some of those people disagree with or outright dislike one another. Now, this can be a beautiful trait. Buried within it, I’m sure, are the seeds of some future generation’s ability to settle all invidious contentions, bring all parties to a common table and drape the world in universal harmony. But of all the troublesome tendencies in my psychological makeup (and there are a few), this one quality has perhaps caused more chaos in my various relationships and jobs than any other.

Because as it happens, you just can’t give everyone you know everything they want. I’m not necessarily saying that all relationships are brutally zero-sum games of resource management, but, y’know, they take place inside history. Like anything else that does, they’re subject to entropy, scarcity, the rules of physics. That I can see, there are no Pareto-optimal solutions for interpersonal relationships, any more than there are for any other system above a certain threshold of complexity. They’re like a three-body problem. (Sometimes they are a three-body problem.)

It turned out that my dearly beloved FRIDAYS AT 7 crew was like that. Now, I need to do a little bit of stage-setting, so you understand the particular dynamic at play here. Though to a one they were (and are) all fascinating, funny, talented and endearing, not everyone who came to drinks on a regular basis had necessarily tasted success as the world defines it. But there was a subset of folks there who had done so, and by any rational standard these were all accomplished people. They’d published well- and widely-reviewed books, or shown films at world-famous festivals, or played a part in the development of some piece of software you use on a daily basis.

I certainly don’t think any more highly of them because this happens to be the case, because god knows why any of our lives break the way they do. But naturally I admired them for their achievements, as well as for the other things that commended them to my friendship in the first place. And I had assumed that within the social universe of the particularly accomplished, there existed something like a consensus that anyone you might care to name more or less knows what they’re talking about.

And so I’ll confess that it floored me when late one night, on hearing me praise a mutual acquaintance who I myself did consider to be highly accomplished, one of these people said, “I can’t believe you rate that guy. He’s just such total bullshit.” Laboring under my maternal inheritance (which I eventually came to recognize as a mutant strain of Geek Social Fallacy #4, actively operating in both my mother and I decades before it was identified and named as such), it had never occurred to me that some objectively high-achieving people might regard one another in this way.

Yeah, I know. You’d think I would have figured this out on the dewy side of forty, come to some much earlier insight into how contingent and variable human reputation can be. I dunno — maybe I cut class that day. Either way, it wasn’t until that very moment that I realized how acutely uncomfortable my praise of this third party was making my friend. It was clear to me, in fact, that he would begin to question my own judgement if I insisted on proceeding too much further down this path. The conversation would get awkward, then actively difficult, and then who knows? maybe the friendship would too. Doors of perception blasted wide by my third Stolichnaya martini of the evening, I began to wonder how many other times over the years I had put someone in just this uncomfortable position.

I realized on the spot that what I needed was a Master Bullshit Matrix.

The Master Bullshit Matrix, as I saw it in that blinding flash of insight, would take the form of a very large (but mercifully finite) spreadsheet. In its cells would be recorded — would reside for all time — a complete accounting of just who considers whom to be Bullshit. Accomplished or not, celebrated or not, by definition there would be a place for everyone on the Master Bullshit Matrix, and then we’d all finally be able to reckon just where we stood.

On its face, compiling any such thing would certainly appear to be a spectacularly mean-spirited and juvenile thing to do: the kind of effort snotty fourth-graders set themselves to, when deciding who is and is not allowed to sit at their lunch table. But as I imagined it, the point of the Master Bullshit Matrix was letting everyone involved in one of these conflicts of appraisal save a little face.

Armed with the Master Bullshit Matrix, I wouldn’t embarrass myself (or anyone else) by continuing to insist on the quality of someone the person I was talking to considered Bullshit. Not unless I wanted to, anyway. In any given moment, I could decide whether or not I wanted to press the case for someone’s non-Bullshitness, teasingly needle someone by dropping the name of someone I knew full well they thought was Bullshit, or avoid the topic entirely. I could even cross-reference a particular intersection of personalities, and learn whether the Bullshit judgement ran one-way or two-way.

Please do not mistake me to be saying that good conversation requires agreement about everything — that you should ever be insincere yourself, or commit yourself to a position you do not in fact hold, just for the sake of someone’s momentary comfort. But there are clearly times when the greater good of social ease requires the deft avoidance of certain conversational minefields. And as I came to understand so late in life, you enter one of those minefields in arguing for someone’s transcendent genius…when your interlocutor believes that person to be Bullshit.

In an attempt to see what it might take to populate the Master Bullshit Matrix, I gently began to probe certain of my more forthright friends for their opinions. All of them understood the question immediately, offering their own personal Bullshit nominations without hesitation. What I found most interesting was that some of these nominations — many of them, in fact — came to me as a complete surprise. It reinforced my sense that there’s absolutely no predicting ahead of time who is going to strike someone else as Bullshit.

Broadly speaking, what seemed to make someone vulnerable to the charge that they were Bullshit? It’s hard to pin down precisely, but certain qualities seemed to crop up fairly often. The perception of insincerity, chiefly. Intellectual laziness, from someone my interlocutor believed that we can and should expect better of. Posturing. Ideology when it appeared to be deployed for craven professional, financial or sexual advantage.

There seemed to be some overlap with Dunning-Kruger syndrome, but not entirely so – it is broadly acknowledged that some people just can’t help being dumb, and while they may not be aware that they are dumb, this in itself doesn’t necessarily make them Bullshit. In other people, however, the behavior that constitutes reasonable ground for a Dunning-Kruger diagnosis is 100% the same thing that makes them Bullshit.

Note, too, that the quality of being Bullshit is something that mostly seems to reside at the professional or vocational level. Very importantly, there doesn’t seem to be anything preventing you from liking or enjoying the company of someone you believe to be Bullshit. Indeed, among the friends I talked to, some of their nominations were folks I know full well that they remained greatly fond of. These weren’t bad people. They were just Bullshit.

Of course the most interesting thing you could do with a Master Bullshit Matrix would be using it to discover who believes that you yourself are Bullshit. You could avoid wasting your time with those people; if you were particularly brave, you could even open up the question of your possible Bullshitness with them, and take steps to address the grounds for their belief, if any. Again, as I imagined it, anyway, the Master Bullshit Matrix would be a constructive tool for interpersonal growth and the avoidance of inadvertent offense, not a preteen’s nasty little cut-book. On this count I am probably being optimistic.

Is it possible to know that one is Bullshit? It’s hard to say. Perhaps, like the Dunning-Kruger effect itself, it’s a self-blinding condition: if you knew you had it, you wouldn’t have it. But it’s worth thinking about, isn’t it?

A brief note on “commoning”

I got taken to task the other day regarding my preference for the jargony-seeming construction “commoning” over the more usual “commons.” (The specific wording: “You say you hate bullshit, but ‘commoning’ seems like just so much bafflegab to me.”)

This brilliant 2010 interview with key thinker/doers Massimo de Angelis and Stavros Stavrides ought to go some distance toward explaining that preference; it’s lost none of its luster with the intervening years, despite everything that’s happened in the world over that period.

In the effort to define a space for living that is neither market nor state, De Angelis and Stavrides make it clear that the act of seizing and occupying it is the easy part. All the glamor and all the grandeur attend that first nervy moment when wirecutters meet chainlink. But precisely who gets saddled with the obligation of continuously remaking that space? Who’s left with the physical work of maintenance, the emotional labor of negotiation? It’s a process, not a reified thing, and that in turn seems to demand the gerund form, with its implication that this is something unfolding in time: commoning.

Yeah? No? Works for me.

On counter-hegemony, or: “I got it! We’ll have them write hit songs.”

At the moment, I’m neck-deep in my Verso stablemates Nick Srnicek and Alex Williams’s still-newish book Inventing the Future; things remaining more or less stable schedulewise, I’ll most likely finish it later on today, or tomorrow at the latest.

It’s a strange book, Inventing. You may have caught some of the buzz around it, and that buzz exists for good reason. (It’s not just the superspiffy totebags Verso had ginned up for it, though I’m sure those do not hurt one whit.) At its heart a passionate argument against work and for an end to neoliberalism and its reality control — forged along the same rough lines as those Paul Mason and the Fully Automated Luxury Communism kids are currently touting — Inventing is a genuinely curious mixture of crystal-clear analysis, righteous provocation and infuriating naivety. If you’re even remotely interested in what emergent technologies like machine learning and digital fabrication might imply for our capacity for collective action, and especially if you think of yourself as belonging to the horizontalist left, you should by all means pick it up, read it for yourself and form your own judgments. (Here’s Ken Wark’s take on it; I endorse most of his thoughts, and have a great deal of my own to add, which I’ll do in the form of my own forthcoming book.)

Late in the book there’s a passage concerning the stance Srnicek and Williams feel the postcapitalist left needs to adopt toward the mainstream media: if the “counter-hegemonic” project they describe is to have any hope of success, they argue, “it will require an injection of radical ideas into the mainstream, and not just the building of increasingly fragmented audiences outside it.”

Well. It must be said that this is not one of the book’s high points. In its latent suggestion that the only reason Thomas Piketty and Donna Haraway aren’t cohosting a lively, popular Sunday-morning gabfest on NBC right this very moment is because we, the progressive public, are somehow not trying hard enough, or have failed to sufficiently wrap our pointy heads around the awesome conditioning power of the mass media, in fact, it’s somewhere between irritating and ridiculous. (It’s hard for me to see how Srnicek and Williams’s argument here is substantively any different from that stroke of market-savvy inspiration the beloved but famously marginal Minutemen skewered on the cover of their second-to-last album. And now you know where the title of this post came from.)

Nevertheless, they’re onto something. Though that more-than-faintly patronizing tone never quite dissipates, S&W eventually find themselves on far firmer ground when they argue that “[l]eftist media organizations should not shy away from being approachable and entertaining, gleaning insights from the success of popular websites.” I was able to shake off the momentary harrowing vision I had of Leninist Buzzfeed, and press on through to what I take to be their deeper point: radical thought can actually resonate broadly when care is taken to craft the language in which that thought is expressed, and still more so when insular, self-congratulatory obscurity is avoided in the design of its containers. I endorse this notion wholeheartedly. This recent appreciation of Jacobin hits many of the same notes; whatever you think of Jacobin‘s politics, it’s hard to deny that its publishers consistently put together a sprightly, good-looking read. (I’d call it “the Monocle of the left,” but that would be to imply that Monocle‘s content is far more compelling than in fact it is.)

You might still argue that S&W ought to spend a little more time with McLuhan. My own feeling is that there’s more to distrust about the “mainstream media” than merely its overtly political content — that consuming information in the form of tweets, listicles, Safety Check notifications, screens overloaded with crawlers, and possibly even glowing rectangles themselves is hard to square with the kind of awareness I at least find it necessary to cultivate if I’m to understand anything at all about the way the systems in which I’m embedded work.

But ultimately, these are quibbles. I agree with S&W when they argue that overthrowing the weaponized “common sense” of the neoliberal era is an explicitly counter-hegemonic project; that developing a functioning counter-hegemony is something that requires longterm commitment; and that those with truly radical programs need to reconsider the relationship between “pop,” “popular” and “popularity” if that whole hearts-and-minds thing is ever going to work out for them. (I’m honor-bound to point out that Saul Alinsky said as much fifty years ago, but perhaps that too is a quibble.) So: no. I have no problem at all with presenting complex and potentially challenging ideas accessibly, so long as they can be rendered accessible without dumbing them down. If successful counter-hegemonic media looks a whole lot more like a Beyoncé video than some preciously anti-aesthetic art installation, so much the better. Bring on the hit songs.