Published on February 24, 2014
Software-Sorted Cities The New Architectures of Inequality Stephen Graham Newcastle University
Recap: *Infrastructure “forgotten, the background, the frozen in place” (Leigh-Star) * Splintering Urbanism and the Architectures of Infrastructure
I Introduction: • ”The modern city exists as a haze of software instructions" (Amin & Thrift) • Computer software mediates, saturates and sustains contemporary capitalist societies. • Enrolled into complex technoscientiﬁc systems, stretched across time-space • Vast universe of code provides the hidden “calculative background” to the functioning and ordering of such societies • This “background” has become the ‘ordinary’ socio-technical world
• Ubiquitous, pervasive, interlinked spaces, systems, and equipment • Link databases to sensor, tracking, logistics and access control systems • Continuously classify, standardise, and demarcate rights, privileges, inclusions, exclusions, mobilities and normative social judgements across multiple scales • Geographies of exclusion are now performed through the agency of software algorithms Software-Sorting: The Agency of Algorithms
• Socio-technical architectures of software-sorting are tending to blend into the wider urban environment • “Surveillant assemblages” embedded into infrastructures and urban spaces: Transponders, RFID Chips, ‘smart’ cards, biometrics, mobile handsets etc • Urban everyday life becomes series of obligatory passage points policed by software-sorting systems (with proliferating codes, identiﬁers, scans, passwords) ‘The Most Profound Technologies Are Those That Disappear’
Software-Sorting: A New Technological Politics? • "Software challenges us to understand new forms of technologies politics and new practices of political invention, legibility and intervention that we are only beginning to comprehend as political at all" (Thrift and French, 2002)
• Helping to facilitate neoliberal infrastructural transformations • Undermine barriers to recommodiﬁcation, mass-customisation, Software- and individualisation Sorting and • From standardised service regimes based Neoliberal on generalised tariffs or universal service Transformations obligations and supply monopolies • To complex infrastructural marketplaces where each user is surveilled, tracked and treated differently based on normative judgments of their ﬁtness, worth or proﬁtability
III Code Space: Software-Sorted Mobilities • (a) Biometric IDs and Airport Immigration Filtering • Opt-in biometric bypass for elite travellers combined with tightened controls for those identiﬁed by risk proﬁling • "the control of international mobilities that cross through airports and border zones are effectively managed, ﬁltered and screened within these sites" (Peter Aday, 2004), • Politics of differential speed and anticipatory proﬁling
• To Peter Aday, this “facilitates the ease of speed for trusted, ‘good’ and economically sound business travellers and yet impede the ﬂow of ‘bad guys’ or secondary processing – where ofﬁcers ‘really don’t care how long it takes’ to process their entry" • Aday concludes, "the airport is now a surveillance machine— an assemblage where webs of technology and information combine. Movement, and, increasingly, the body, identity, and objects are made legible, momentarily fusing with technology and virtual realism" (2004).
(b) Road Pricing: Unbundling Public Roadspace Monopolies: • Most road-pricing (e.g. London) still based on standard tariffs at all times • Rely on transponders, automatic number plate recognition, call centres, cameras and databases • Do allow differential pricing • London proposing to charge big extra levy for 4x4s by 2009
The Quest for ‘Real-Time’ Road Pricing • Software-sorting being introduced to display variable pricing in real time -for example I-15 highway in San Diego • This is based on algorithms which estimate exactly the level of price per journey that is likely to deter enough drivers to guarantee free-ﬂowing trafﬁc -- no matter how bad the congestion is on the surrounding public highway system. • May also be built into proposal for EU roadspace pricing using GPS technology
(c ) The Internet: From ‘Best Effort’ to ‘Squelching the Scavenger Class’ • Internet originally developed to accord all the ‘packets’ of information that ﬂowed within it equal status. This was the so-called ‘best effort’ model of packet switching • Now, under pressure of congestion and pressures to introduce neoliberal service regimes, the entire Internet is being reengineered into a corporately controlled system of systems dominated by a wide range of commercial services
• Software-sorted Internet systems allow a guaranteed quality of service to premium users and prioritised services, even at times of major internet congestion • But those packets deemed unproﬁtable will slowed down or actually ‘dropped’ • This is likely to lead to a dramatic deterioration in the electronic mobilities of marginalised users or nonprioritised services
• World’s largest provider of Internet Routers, Cisco (2002), describe how premium internet services can now be offered to what they call the "transactional/interactive data class" of users, whilst, at the same time, what they term the "scavenger class" will be actively impeded based on softwaresorting of every single Internet packet. • "The Scavenger class [categorisation] is intended to provide differential services, or ‘less-than-BestEffort"’ services, to certain applications", the document suggests. "Applications assigned to this class have little or no contribution to the organizational objectives of the enterprize. Assigning a minimal bandwidth queue to Scavenger trafﬁc forces it to be squelched to virtually nothing during periods of congestion" .
(d) Call Centres: The Politics of Speed-Up and Slow-Down • Call centres can detect the telephone numbers of incoming calls, and instantly check these against customer and geodemographic databases • Use software-sorting techniques to queue ‘good customers’ for shorter times than ‘bad’ customers.
Initially, Mediated by Call Centre Operator • A marketing brochure from the Avaya Corporation (2000): "One of your best customers dials the national customer service number for your company. The ANI [Automatic Number Identiﬁcation] database reveals the customer to be among the top 5% of your customers. [Our system] routes the customer at high priority. When the agent picks up the call, he hears a whispered announcement that this caller is ‘Top 5’"
But Shifting to Automated Prioritisation • Ian Davis, a customer relations manager at the IT company ATG: “It’s all about ﬁnding out who the customer is, and putting then in the correct bucket. The unproﬁtable customers never hear about the discounts and promotions”. • Can be used to allocate scarce operator time. The phone company Orange, for example, allows immediate access to a human being only to those users who sign up for a premium ‘Panther’ service. The Virgin call centre, Thetrainline, deters ﬁrst time callers with lengthy interactive voice response menus whilst prioritising regular, business, passengers for tailored, human, support.
IV Code Place: Software-Sorted Cities • Geosurveillance and geotracking boom (e.g. Radio Frequency Identiﬁcation Tags) • Databases link to Geographic Information Systems (GISs) to offer different services to different neighbourhoods
Supports Geographical Unbundling of Previously Standard Services/Prices • E.g. Amazon has offered different DVD prices to different customers in USA • UK train travellers now access a labyrinth of different tariffs and prices based, using software-sorted web sites and call centres, on when they book their tickets, who they are, and even where they live.
RFIDs: The Politics of Ubiquitous Tracking? • Once RFID based ‘tracking’ becomes routine, software-sorting techniques will move beyond crude, generalised, and ‘lumpy’ simulations of places, to personalised advertising and real-time tracking • In Japan, owners of malls or privatised public spaces are experimenting with using RFID cards to identify each individual who enters their realm covertly and automatically. May allow trackings of their tastes, wealth, habits, associations and potential proﬁtability. • Could allow extra services and beneﬁts to be offered to those deemed most desirable whilst supporting attempts to remove or discourage those deemed to be problematic • So may work to “chill [speech, actions or assembly deemed] irregular, deviant or unpopular” in such places (Kang and Cuff, 2005)
V Code Face: Software-Sorted Streets? • Building on the massive and rapid diffusion of analogue CCTV, which relies on the (expensive) ‘MK1 eyeball’ of human operators, scanning monitors and recording footage using banks of domestic-style video recorders, a major effort is now being made to install much cheaper, automated, facial recognition, or ‘event-driven,’ CCTV in the place of such systems • Here algorithms scan for ‘abnormal or ‘target’ events or people based on software which monitors and learns the putative ‘normal’ background
Face-Recognition CCTV • Many technological problems inhibit FR CCTV on open city streets (as opposed to airport passage points) • But major R and D to address these • ”Unlike other biometrics [facial recognition CCTV] can operate anonymously in the background" (Koskela, 2003) • The code within the facial recognition system becomes a key political site because its operation automatically stipulates the subjects, locations or behaviours that are deemed by the operators to be ‘abnormal’, ‘threatening’ and worthy of further scrutiny or tracking. • There are very real risks that the multiple ‘islands’ of private and public CCTV systems, each monitored by its own human operators, could quickly merge, or link, into much more massive and geographically-stretched facial recognition CCTV systems.
The Politics of Facial Tracking • Mitchell Gray (2003): "As the technology advances", the clear risk is that "the software will effortlessly track individuals moving through urban space, public and private. Any appearance of a person deemed threatening can be set to trigger an alarm, assuming that that person’s face has been recorded in a linked database". • Inherent biases. On one trail "identiﬁcation rates for males were 6% to 9% points higher than for female. Recognition rates for older people were higher than for younger people" (Introna, 2003). • Also, the trial report states that "Asians are easier [to recognise] than whites, African-Americans are easier than whites, [and] other race members are easier than whites" (FRVT, 2002)
VI Conclusions: The Agency of the Algorithm • This paper has sought to underline the centrality of software-sorting in structuring contemporary social and geographical inequalities. • It has also attempted to illustrate the need to maintain a broad, multisectoral perspective which can capture how different software-sorting techniques are encroaching across different dimensions of contemporary societies. • Clearly, though, much more detailed analyses on software sorted assemblages in practice is needed
(i) Software-Sorting: New ‘Digital Divides’? (ii) Politics of Speed and (Relative) Immobilisation (iii) Challenges of Transparency and Visibility
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