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Matthew Fuller and Graham Harwood
Introduction
One of the first computational models of a city was set out in Thomas
Schelling’s paper Models of Segregation (1969). In this and related papers,
he attempted to provide a logical model of the dynamics of racial segregation
in North American cities and laid groundwork for what later became known
as agent-based modelling (Schelling 1969). Although Models of Segregation
did not at first use a computer, it sets up some of the basic characteristics
and problems of the field. Such work is also expressed contemporarily, for
instance in the work of J. M. Epstein (2002) and others in the area of computational social modelling.1 We use this work as a starting point to think about
the relationship between urban morphologies and the politics of models and
with the increasing and multiform kinds of merger between computational
systems, models and city forms, what it means to inhabit different scales of
abstract structure. It is in this juncture that abstract urbanism arises.
This chapter examines the ways in which logical forms are positioned
in relation to urban life as a means of discussing the relations between the
city and software and will develop a discussion of such logics in relation
to questions of abstraction, reduction and empiricism. By working with
the materiality of computational systems, especially as they unfold into
the urban – and the urban in a full sense, as something involving complex
comings into being of desire, imagination, technologies and forms of power
– we can at the same time recognise an art of working with the tendency to
reductionism through which modes of abstraction may operate and also
work with the highly and complexly empirical. As social simulations are
increasingly embedded in, or cleave close to, lived social forms, the texture
and reality-forming capacities of these logics and the fantasies they inspire
and live by need to be examined.
Development of simulation as a scientific practice
One attractive aspect of modelling as a means of experimental understanding
is that it offers a science of behaviours rather than of essences. It is peculiar,
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therefore, that one of the earliest examples of social simulation derives from
a highly essentialist ontology. Perhaps this might be seen as an example of a
new epistemic form emerging out of a prior set of commitments that it has
yet to break. Models of Segregation builds on the game theory established
by Morgenstern and von Neumann (1947). Schelling’s (1960) earlier gametheoretic book, The Strategy of Conflict, can be seen as a presiding spirit
in Models of Segregation’s attempt (Schelling 1969) to map and rationalise
options in the decisions around actions in the schematised space of non-zerosum conflict.2 The opening stages of the paper set up segregation as a fundamental axiom of great applicability. Schelling mentions men and women,
Catholics and Protestants, boys and girls, and officers and enlisted men in an
army. Not all types of segregation necessarily tend towards dichotomous formation. People are also sorted by ‘sex, age, income, language, colour, taste,
comparative advantage and the accidents of historical location’, amongst
other factors. It is assumed that the sorting behaviour for each of these is the
same.
In the model, a two-dimensional line is drawn (it is important to note that
this is a line, not a grid) with equal divisions of space along its axis. The line is
populated with an equal number of ‘black’s and ‘white’s. While the distribution looks even on the macroscopic level, at the microscopic level it is uneven.
Maybe three blacks are conjunct with one white, then a black and then three
whites. If the whites and blacks are content with a 50% split between the
colour of their neighbours then those who have a white neighbour on one
side and a black neighbour on the other reach the contentment threshold and
stand still if the neighbourhood to be considered has a radius of one. Those
with ‘too many’ black neighbours or white neighbours will move in order
to achieve contentment. In a neighbourhood with a radius of one, the line
BBBWBWWW would, several iterations later, become BWBWBWBW. If
the neighbourhood extends to two houses, then the B and W in the middle of
BBBWBWWW would be looking for new neighbourhoods. To summarise,
in Schelling’s model, each agent is ‘black’ or ‘white’ and aims to reside in
a neighbourhood where the fraction of blacks or whites is above a predefined tolerance. Schelling’s algorithm for determining the pattern of residence
either creates complete integration or complete segregation.
Curiously, there is no reflection on the constitution of racial sorting even
in excusatory fig-leaf terms. Like the stories of house-hunting amongst ‘professors and their wives’ that Schelling (1971; 1978: Chapter 4) describes elsewhere, the specific categories upon and through which segregation operates
are described as if natural, not even worthy of equivocation as to their relation to social structure. The racism of the work is both that it operates by
means of racial demarcation as an autocatalytic ideological given and second
that it provides a means of organising racial division at a higher level of
abstraction. To say that Schelling operates within an ideologically racialised
frame is not to claim either way as to whether Schelling as a person is or was
consciously racist, but that, in these papers, racial division is an uncontested,
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‘obvious’ social phenomenon that can be reduced in terms of its operation
to a precise set of identifiers and operations. Goldberg’s formulation of the
problem of racism is useful here:
The mark of racist expression or belief, then, is not simply the claim of
inferiority of the racially different. It is more broadly that racial difference warrants exclusion of those so characterized from elevation into the
realm of protection, privilege, property, or profit. Racism, in short, is
about exclusion through depreciation, intrinsic or instrumental, timeless
or time-bound.
(Goldberg 2009: 5)
The naturalisation of such a situation of depreciation by at-a-distance
means in which entities kindly self-organise into ghettos out of their own
otherwise unlimited choice must have been a marvellous boon to someone.
What these papers offer is the construction of a machine for the operation of
binary categorisation that in turn becomes an engine for spatial organisation,
of preference-based segregation, as if the provision of housing in the form of
a market is entirely smooth and demand driven, as if there are no variations
in housing kinds and qualities, geographical features, cultural variations in
population, of wealth, and so on.
What Schelling’s work allows for is an operation of governance beyond
that of direct sorting and selection, the direct command and control of populations, but rather by eliciting and installing an action grammar in which
people ‘spontaneously’ recognise, in the words of Nina Simone’s Mississippi
Goddam (1964), ‘I don’t belong here, I don’t belong there’.
Schelling offers the image of urban form being operated upon by an ‘invisible hand’, emerging at a higher level in social and material channelling.
There is a tension, then, between the figure of this invisible hand and the view
of the agent. The hand operates in an ostensibly emergent or natural way,
arising out of the conditions of the situation as they are, beyond how they are
seen by individual actants.
Abstraction as urbanism
Schelling’s abstract machine is one for the bipolar reduction of variation.
One of the advantages of such an abstraction is that it requires no specific material form, simply logical equivalence. As recounted in a glowing
festschrift chapter, Schelling initially used pennies, heads or tails up, on a
draughts board to simulate, ‘what sort of segregation patterns develop given
various types of preferences and alternative definitions of neighbourhood’
(Zeckhauser 2006: x). The scale of the board becomes the limit factor of
the diagrams published in a later paper, Dynamic Models of Segregation
(Schelling 1971). One can imagine a media-archaeological analysis of the
history of simulation starting with such boards. John Conway, in developing
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the Game of Life, famously extended his to cover most surfaces of his office
(Gardner 1970). Equally, only having four significant neighbours, termed
‘Neumann neighbours’,3 draws a simplifying factor from the board, the
constraints of which may in turn be surpassed by the volume of processing
offered by electronic computing.
Indeed, a media analysis of the field can divulge a number of aspects of its
material practice that are often rendered conceptually and procedurally invisible. One such is that models tend to be bound by the temporal constraints
of ‘turns’ in which all agents shift at the same time. Most models need to
have all variables change at the same time – but models of sociality need to
vary the periodicity of change for individual agents. Equally, in the model’s
interaction with hardware, the need to represent data to human users renders
the allocation of CPU cycles to drawing graphical representations something
of an interference when compared with how many agents could be processed
instead.
A few years after Schelling’s work was published, Ted Nelson (1987: 149)
stated in Computer Lib that simulation is always political.4 Computers, as an
abstract machine for the integration of all symbol systems – those operated
upon by discrete values, or values that can be rendered as digital – provide a
great degree of plasticity in the social forms they might potentiate: hence the
significance of Nelson’s formulation. But the specific kind of politics simulated is also articulated by the qualities of the mathematical structures they
come into composition with (rule sets; systems of four or eight neighbours;
bounded, unlimited or wrapping grids; and so on). It is a rare case in which
there is a direct correlation between the various scales of model, media, mathematics, the social form modelled, the ideological commitments specified as
politics in such simulations and the actual politics of the material operations
of such systems in use. Each of these scales is active.
Diagram city
Epstein and Axtell’s (1994) Growing Artificial Societies: Social Science from
the Bottom Up drew on Models of Segregation and from Conway’s Game of
Life. In Conway’s cellular automata and Schelling’s space of segregation,
the environment has no active properties, something that has consequences
when these models carry over into urban planning and cityscape modelling.
Epstein and Axtell’s innovation was to place agents in an active environment
and to programme them to explore for simple codifications of basic resources
to keep their metabolisms alive. Agents and environment have internal states
and behavioural rules that are fixed at the start or that can inherit change in
interaction with each other. This is a model as a form of regression analysis,
or rather of using regression as a form of proposition-making mechanism,
where the relations between entities are fixed but variable. The environment
is a lattice of resource-bearing sites in a medium that is separate from the
agents, but on which they operate and with which they interact.5
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Epstein has produced a body of work discussing the ethics around agentbased modelling that seek to affect US governmental policy by creating
explicit models that can be used to explain social phenomena; something he
is careful to distinguish from prediction. In Why Model?, Epstein (2008) challenges the assumption that scientific theories are created from the study of
data. He asserts that without a good theory, it is not clear what data should
be collected. Modelling requires theorisation and so creates enquiring habits
of mind that he posits as essential to freedom.
By contrast, agent-based models have been eagerly taken up as objective
explanations of conflictual social forms. The capacity to express forms of
emergence, with the invisible hand effectively rationalising commonsensical
observations of the inevitability of such phenomena as racial segregation
excites dreams of implementation. As such, this aspect of this work evinces
a fascination with finding fundamental laws of social aggregation, rhetorically building on those found in natural sciences, in turn afforded by those
historically associated with mathematics. Such kinds of model and associated
discourse still act in a representational mode, rather than one of enquiry.
Simulations now operate in a wide range of cases and kinds. They act as
a form of prognosis and forecasting, of pre-emption and the maintenance of
irresolvability as well as having the ability to formulate an explanation with
empirical traction without having to be true. Simulations also develop specific kinds of techniques and vocabularies, as well as the software to handle
and interpret them – object-oriented programming being one such example
(see Fuller and Goffey 2014). Object-oriented programming is fundamental to how agent-based modelling conceives of itself, as it allows objects to
hold data and functions in internal states. The object exports a limited set
of methods with which to interact with it – and the data, rather than being
globally accessible, are held privately to the object. This is why the behaviour
of objects comes to the surface – rather than the data that underlie them.
Functions or methods are the agents’ rules of behaviour.
One novelty in this kind of work is the way particular forms of computational abstraction themselves become operative elements in social and urban
formations. Computation becomes folded into the operations of societies,
and social forms become computational problems. As the programmable
city begins to incorporate models, such systems become more than representational. Here, there is a correlation between formulations, such as those of
Epstein and Schelling (and those that followed in developing simulated societies), and the social sorting by software described by Steven Graham (2005)
in his noted article Software-Sorted Geographies. In agent-based modelling,
by contrast, there is an interplay between the schema of sorting and the
actions of individuals and social formations, without engaging with the level
of implementation. Where there is a difference is that Graham describes a disciplinary sorting on the social. There are kinds of sorting occurring, but these
are more adequately expressed as a multiscalar, multivariable sorting enacted
by agents bearing seemingly lucid and operable preference lists arrayed in
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relation to the behaviour and imagined preferences of others, apparently
reducible to hard and fast organisation. A particularly interesting moment to
watch for is when the two merge to some extent, either in actual implementation, or in the seductive idea that such reductions are fully adequate explanations of specific slices of reality.
In the case of the racism of Schelling’s Models of Segregation, the categories pre-exist the machine. The machine is there to sort them, to anticipate
their actualisation, to provide a degree of abstraction in which they can be
reckoned, and by which the abstraction too can be worked up into an actor
of a kind in itself. This operation of abstraction is crucial to understanding
software as a cultural, city-making force.
Logics
The use of computers implies the interrelation of different forms of logic, at
the levels, for instance, of programming the machine to perform calculations
and of regulating the behaviour of users in pushing around mice and navigating menu systems to produce desired results. One way to think about how the
mass adoption of these forms of logic effects society is in the mode Foucault
described as discipline, one that analyses and breaks down a phenomenon
through modelling it to produce a kind of remote control. Computation disciplines the way a phenomenon is approached and analysed so that when it
becomes visible again from within the computer it makes the phenomenon
materially available for comparison and modification. As users participate in
the flows of power created by the comparison of information, they become
normalised to its process and are themselves enrolled in the interrelation of
logics.
Computational forms of normalisation establish the configuration of logics
needed to make the materiality of the phenomenon available for modification
via abstraction, verification and reward. The repeated construction and use
of these forms of logic provides a form of progressive training for those that
model, feed, collect, process and react to such logics, as well as those objects
that are the subject of its calculations. Logics decompose processes and the
entities, including people, that are aggregate with them. The routine processing of or interaction with such models provides a collective logic to be applied
to all areas of society and the natural world. The move beyond discipline,
however, is characterised by the absence, further withdrawal or multiplicity
and duplicity of the ultimately reliable, central control that discipline implies
as a structuring principle.
Logic gates
Part of the legacy of Schelling’s and Epstein’s work is in the police, academic and intelligence projects aiming to predict riots via sentiment analysis.
‘Negative words’, ‘hate speech’, ‘positivity’ and expressions of anger stand
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in for a population of shifting emotional registers, moving from stable states
to those that can be used to require the maintenance of policing budgets,
harsher policies and sudden rashes of inflamed and excited research budgets.
The operators of such machines sell their technical fixes as providing a neutral oversight, in which the free expression of populations and individuals
can be mapped and cross-checked for ‘naughtiness’. What happens is rather
more complex; social forms are interwoven with those of the state, which
itself attempts to follow too many filiations and clusterings. In the meantime, academic chancers position themselves as dubious mediators, able to
appear to delve into the firehouse of text produced by a population mapped
according to weightings assigned to strings of characters. We enter into a
condition of a generalised politics of experimental control without controlled
experiment.
Claus Pias suggests that recent theories such as actor–network theory and
radical constructivism come from the same stock of ideas as simulation, since
for both:
Their knowledge is consciously – and as a matter of course – furnished
with a hypothetical index, they admit to their fictional components, they
position themselves within their conceptual frame of reference, they thematize their performance, they are aware of their problematic genesis,
and they specify their limited application.
(Pias 2011: 54)
A useful provocation following such a proposition is to be found in Latour
and Lépinay’s reading of Tarde (2009: 19): ‘If you really want to quantify –
which is after all the foundation of all sciences – you should try to find all
the available types of quantum, instead of just using one to analyse all the
others.’ This premise underlies some of the enthusiasm for big data analysis
at present. It also perhaps implies that social reality is a simplified model of
more adequately complex modelling schema. But we can also suggest that
William Bunge’s (1971) later mode of maximalist empiricism coupled with
high degrees of statistical abstraction is of great relevance here. The proposition is that to study is to become actively involved, to observe is to change,
but also to recognise, that though such change may be reciprocal, it may not
be symmetrical and equivalent. These, now, are the stakes of watching and
participating, since in the city understood as a platform for self-organisation,
algorithms, rule sets, data structures, interfaces and procedures have highly
and perhaps questionably promising agency (Chopra 2014). The recent scandal of researchers from Facebook and the Universities of California and
Cornell using Facebook’s news feed to operate and experiment on whether
people responded to the filtering of what appeared in their news feed on the
basis of whether it was associated with emotional ‘negativity’ or ‘positivity’
should be seen as a part of this tendency. The researchers note that Facebook
constantly experiments with the algorithm to fine-tune this aspect of their
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‘product’ (Kramer, Guillory and Hancock 2014). It is this state of perpetual
experiment, linking different scales of realities, that is characteristic of the
condition of abstract urbanism and the kinds of operation that the integration of modelling with cities encourages.
This operation of the city as open experiment is, of course, one subject
to the analysis of power. For Epstein and Axtell, agent-based modelling
enforces habits of mind that are essential to intellectual and democratic freedom. An agent-based model must be explicit and open and be able to be
examined and doubted, reconfigured and rerun. Epstein aligns agent-based
modelling to scientific modes of inquiry that he sees as antithetical to established discursive intellectual systems. Agent-based modelling provides a freedom to doubt large monolithic and deductive forms of knowledge. Epstein
and Axtell propose that we are on the edge of a new enlightenment based on
the ubiquity of computing. One in which, for Epstein (2008), ‘intellectuals
have a solemn duty to doubt, and to teach doubt. Education, in its truest
sense, is not about “a saleable skill set”. It is about freedom, from inherited
prejudice and argument by authority.’ The question of whether the enlightenment can be fully called upon in this way is in turn open to doubt, but there
is something here that suggests some possibilities in that it is a science that
explicitly calls subjects into being.
This proposed new mode of science of active abstractions involves cities
and social forms in what Stuart Kauffman calls (2000) ‘the physics of semantics’, logics that have effects in the organisation of conjunction, calculation,
control and communication. Such a physics of semantics can be seen, at
other scales, in the way that the agent-based model is involved in the specific
forms of hardware and software development that conjoin both meaningmaking scaffolds and physical properties. Object orientation in programming
is seen as a cogent worldview, capable of answering difficult questions about
behaviour that emerge from complex subjects in the social or in economics,
where, ‘[it] facilitates essentially any interaction structure (social network)
and activation regime’ (Axtell 2003). In contemporary accounts, agentbased modelling also links its ambition to the growth of CPU processing and
the availability of hard-disk space and network processors assumed under
Moore’s law. The ‘promising’ nature of abstract cities is thus also woven into
multiple scales of their materiality.
This suggests that there is the possibility for a mode of experimentation,
and of experimental politics and urban living that moves from the logics of
theorems or axioms to an abstract empiricism. Historically, software-based
simulations essentially replaced the kinds of hardware-based simulations or
analogues of biological, cognitive and social systems developed in places such
as Heinz von Foerster’s Biological Computer Laboratory in Illinois (Müller
and Müller 2007). The questions posed change in this transition, becoming
allied less with the philosophical concerns characteristic of the Biological
Computer Laboratory, with its emphasis on epistemology and the question
of abstraction and reduction from material empirical conditions. We are now
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well into another similar transition where, instead of moving from hardware
to software (with hardware becoming less experimental and idiosyncratic as
it is rendered in the form of commodity electronics), social and urban forms
become places of computational interoperation and experiment.
Urban space is increasingly produced in the production, circulation and
analysis of large volumes of structured and unstructured data. Models and
modelisations are being integrated into the design of such spatial forms as
stadia, streets and stations at conceptual and pre-emptive stages for the purposes of safety, transit design and revenue protection. In such cases, agents
become active as urban entities installed and active in the symbolic and material orders of the city.
Just as computational forms structure reality, so do other kinds of model.
Abstract urbanism is hypothetical, fictional, maximally empirical and, of
course, abstract. This means that the way in which abstractions become
materially operative has to operate through these conditions, and also –
under certain regimes of rhetoric – to shield them, as simply fact-based
extrapolations. To recognise that they are imaginary, as models, without
being merely false or simple reifications, is part of the art of abstract urbanism. To see agent-based modelling in such a way is to recognise that models
are also partial cities operating like partial objects, formalised slivers of an
urban configuration taken for a whole and working their drives into active
diagrams. Such a condition, in which the possibilities of social fractures
being triggered in the models and then implemented are manifest, cannot but
add an ambiguous potency to the operations such an art promises. To work
abstract urbanism in the condition of models becoming cities then is also to
open the possibility of operating with a maximalist empiricism. It is to operate with delicacy and attentiveness in the design of models, but also to the
arguments, spaces and politics that they bear, that they determine and into
which they are smuggled, driven and suffused, and which in turn they rely
on to sustain themselves. It is to saturate models with variables, and to open
abstraction to social disruption rather than to prepare the abstract retrenchment of urban injustice.
But to recognise abstract urbanism is not solely to postulate an interesting
set of potential political practice, but more, to come to terms with a fundamental change in the consistency of cities today – they are suffused with
logics. This is not simply to say that streets are data structures, people are
variables and the city is a grid laced with numerical nutrients, which in their
interaction produce an adequate if simplified mimicry of urban life; but that
the city, the exemplary space of modernity in all its complexity of desire, violence, multiscalar layering, imagination, invention and struggle is also a place
of experiment with modes of composition and of self-emergence at multiple
scales of abstraction. Such a space is one where fantasies of control, of understanding, of ordering, of establishing implicit and explicit coordination and
pre-emption coexist with their enactment, their failure, their use as excuse,
and as a space where logic coexists with the surprise of the unforeseen.
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Agent-based modelling provides a means for the phantasmatic appearance
of logics as an always present compliment of logic itself in that it mobilises
means by which things occur in and for themselves in the mode of emergence,
and for a space for arranging the coming into being of ideas of the city that
are beyond the habitual means of interrogating existing coordinates. Here,
in the state of being promising, logics both pre-empt surprise and rely upon
it to provide a gateway to emergence understood as the self-constitution of
reality; a reality that is, on the one hand, seemingly unblemished by mess, or,
on the other, one forged in the full ongoing complications of the cityscape in
which it becomes manifest. This is a deeply ambivalent position. The physics
of semantics in which such emergence is made is therefore worthy of attention with all the precision and inventiveness that can be mustered, as it too
becomes a space in which the city occurs.
Notes
1 Exemplary of work building on Epstein’s model includes Casilli and Tubaro (2011)
and Davies et al. (2013).
2 The paper is revised in Schelling (1978).
3 Edward F. Moore gives his name to systems of eight neighbours, expanded to
include those at the corners in a rectilinear grid.
4 ‘All simulation is political. Every simulation program, and thus every simulation,
has a point of view. Just like a statement in words about the world, it is a model
of how things are, with its own implicit emphases: it highlights some things, omits
others and always simplifies.’ (Nelson 1987: 149).
5 See Axtell and Epstein’s Sugarscape software.
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