- Direct democracy as the keystone of smart city governance as a complex system
- 1 Introduction.
- 2 The smart city: a collection of smarties or a system?
- 3 How smart were the cities of the past?
- 4 Cities as far from equilibrium adaptive systems.
- 5 What makes a city smart?
- 6 Why do we need strong citizen-based interactions within the urban system?
- 7 Distributed sense-making as a theoretical framework for a processual approach of direct democracy
- 7.1 Distributed sensemaking and complexity
- 7.2 Collective sensemaking
- 7.3 A processual approach of collective sensemaking in the context of a direct governance initiative
- 8 Conclusion
- Articles similaires
Direct democracy as the keystone of smart city governance as a complex system
Abstract We consider the smart city not as an addition of « smarties » (technological devices) but as a system capable of evolution all along its lifecycle, described as Urban Lifecycle Management (Rochet 2015) since a city never dies and must be able to reconfigure itself while its internal and external environment changes. The literature on cities as evolving ecosystems (Batty 2015) considers this evolutionary process can’t be steered in a top-down way, either by a supra-rational actor or on a self-regulating basis as claimed by the authors of the first order cybernetics. By integrating all the components of this evolution in the context of iconomics (economics of the III° industrial revolution) we examine why direct democracy appears to be the best drivers for this regulation and what could be its underpinning collective future-oriented sensemaking dynamics.
The recurrent problem appearing in the attempts to define smart cities is the understanding of how a smart city grows and evolves out of a sum of technological devices. Michael Batty’s groundbreaking opus ‘The New Science of Cities‘ (2013) defines the challenge, in the line of thought of Jane Jacobs and Chris Alexander, as comprehending the city “as systems built more like organisms than machines”, i.e a network of flows. Consequently, if we want the city to be smart, we need to monitor the growth of the city and predicting its evolution with modelling tools up to the age of the digital economy. We need to analyze the smart cities dynamics through the lens of complex systems architecture, to envisage which competencies, and specifically, public ones, may be updated to take on this task of modelling. Following Batty and other complex systems scientists, the city aspiring to be smart is to be conceived from the bottom-up and no longer from the top down as it has been the rule until now in the tradition of urban planning, therefore putting emphasis on the role of the ordinary citizen as a key actor.
2 The smart city: a collection of smarties or a system?
Mainstream definition of smart cities, adopted by the European Union, relies on Giffinger categorization: a city is smart if she gathers “smart” characteristics: smart people, smart governance, smart transportation, smart buildings, smart economy, technology…. Basing on such criteria, EU accounts up to 240 smart cities in Europe! This approach is meaningless from a systemic point of view: we may have smart people working with cutting-edge technologies in BIM positive energy buildings, using trendy solar transportation cars, and producing a stupid system as a whole.
A smart city is more than the sum of “smarties” (smart grids, smart buildings, smart computing…) in spite we have no precise and operational definition of what a smart city is (Lizaroiu & Roscia, 2012). In the recent literature, the smart city tends to be defined as an ecosystem, that is to say a system where the whole is more than the sum of the parts and has autopoeitic properties (Neirotti et a., 2013, Batty, 2013).
What makes a system, and most of all an ecosystem, is integration. Integration is an emergence, that is a state defined as a process which cannot be described by a fixed model, consisting of invariant distinctions. Hence emergence must be described by a metamodel, representing the transition from one model to another one by means of a distinction dynamic (Heylinghen, 1992). The literature on cities as evolving ecosystems (Batty 2015) considers this evolutionary process can’t be steered in a top-down way or on a self-regulating basis as claimed by the authors of the first order cybernetics (Heylighen &Joslin, 1991).
Therefore, if we apply the law of requisite variety developed in the stream of complexity theories, we see clearly, as had stated Karl Weick (1995), that “human thoughts and action (in the context of complex ecosystems) must be highly varied to grasp the variations in an ongoing flow of events”. In other words, for such a transition stated above to succeed at the scale of a social system (city, district, etc.), the metamodel and its underlying process must be “as complex as the system they (actors involved) intend to regulate” (Weick, 1987b).
The purpose of this paper is first to understand the basic tenets of complex adaptive system theory applied to the emerging field of smart city and its self-regulation dynamics, second to explore what kind of “complexity-enabled” process could be adapted to experiment direct democracy principles on a specific social system, using a combination of future-oriented collective sensemaking recent theoretical developments (Stigliani & Ravasi 2012; Gephart, Topal, & Zhang, 2010; Gioia & Chittipeddi, 1991) and the emerging field of design thinking applied to smart cities (several examples driven by different contexts, motives and approach : Christchurch, New Zealand, Panama-city, Barcelona etc.).
3 How smart were the cities of the past?
The seminal The City in History by Lewis Mumford tells us cities of the past were self-evolving ecosystems obeying the laws of organic planning. Organic planning, as analyzed by Mumford has no preconceived objectives. It’s a self-adaptive system which reinforces its coherence along time. The resulting pattern has not been foreseen beforehand but is strongly coherent and harmonious.
This evolution was made possible by a shared common sense of beauty and of the ends of life in the city. One of the most salient traits of these towns is they were free merchant cities ruled by various forms of democracy, drawing from direct democracy (e. g. Veliki Novgorod in XI°century Russia) to complex mix regimes to preserve the equilibrium of powers among the few powerful and the many of citizens (e.g. Florence, Venice). The sense of the Common good, sense of harmony made these cities working as a continuous problem solver, a learning system which reinforced its coherence along time.
As Mumford put it, the coherence of these cities was reinforced by the wall that we could call, in the contemporary system language, the perimeter of the system which defines what is inside and outside the system. The relationships between the city and its periphery were organized as described at the beginning of the XIX° century by Von Thünen, by concentric circles. But what made the success of the medieval town made its loss: the wall was fixed and the city appeared to be an open evolutionary system with the advent of the “death of distance”, first with more secure roads and with the revolution of transportation by the middle of the 19th century. With the appearance of networks of infrastructure technologies and the spread of the telegraph that transformed the government of the city, critical obstacles to the growth of cities were removed making the wall senseless. Today digital technologies amplify this move, providing new tools such as smartphones that became a digital “Swiss knife” that allows inhabitants to be active actors in the city life, communicating and coordinating with each other, using and feeding databases.
4 Cities as far from equilibrium adaptive systems.
Growing cities began to be considered a system in the practice of urban planning that appeared formally in the 1950s to solve the problem of transportation between workplaces and housing, under the banner of “social physics”, the utilitarian approach propelled by Stanley Jevons at the end of the XIX° century (Jevons, 1871) who considered economy ruled by the general laws of mechanics. These key ideas assumed the system was in equilibrium and might be regulated by single feedback loops according to the principles of first-order cybernetics. This kind of model relied on spatial interaction for testing, e.g. how people might shift from one mode of transportation to another, as decided to solve the congestion in London in 2003 by charging car traffic, and predict the effect on global pollution, the growing density of the city to shorten the traffic between workplace and habitation.
But in the recent decades, since the 1980s, the paradigm has changed fundamentally. In first-order cybernetics, the system is centrally organized, in equilibrium, being able to return to its state of equilibrium after a perturbation – an equilibrium slightly different but not questioning the dominant pattern of the city. This kind of system is viewed as centrally organized and structured from the top down, as exemplified by Rio do Janeiro central control system built by IBM.
The development of second-order cybernetics in the 1980s moved the structures and behaviours of the city toward a system being organized from the bottom up. These systems are in dynamic disequilibrium, notwithstanding that disequilibrium is not permanent since the system is undergoing to one state of equilibrium to another. Michael Batty has coined the expression “far from equilibrium” to describe this phenomenon (2016).
These systems are adaptive (Arthur, 1997) meaning that equilibrium is renewed from within through unanticipated innovations reacting unanticipated events. This is an endogenous evolutionary process, compared to the exogenous command and control process of the first order cybernetics. Here we find this kind of architecture without architects as described by Mumford in the case of the Middle-age city. The city is growing organically from the bottom-up. Christopher Alexander, in his seminal book on system architecture of cities, A Timeless Way of Building, has given an iconic definition of organic growth, putting that “quality in buildings and towns cannot be made, but only generated, indirectly, by the ordinary actions of the people, just as flower cannot be made but only generated from the seed ».
This supposes that, as in biology, it exists some kind of genetic code that made the system self-regulating. In that case, asserts Alexander, this code is « replaced by people conscientiousness of the larger scale patterns, which provides the rules of growth. If people have agreements about these larger scale patterns, then they can use their knowledge of the patterns, and the degree to which these patterns have been attained, or not, to guide the growth and the assembly of the smaller patterns. Slowly, under the impact of this guidance, the sequence of small-scale transformations will, of its own accord, create the larger patterns, piece by piece: without any individual person necessarily knowing how or where these larger patterns will be in the finished town » (1979).
To sum it up, the more the city as a system is confronted to as well endogenous as exogenous changes, the more it accumulates this « people consciousness » that allows new patterns to emerge. The smartness of the city consists of this continuous learning process that relies on interactions between basic cells and actors of the city. If the lessons of the middle-age city as an archetype of organic development that produced the smart city of that time, its failure was it was conceived as a closed system locked in behind the wall.
In the 19th century, intents to reinvent such self-contained cities were made by utopians such as Ebenezer Howard in reaction to the unhealthy sprawling of industrial revolution cities. He thought of the smart city as an ideal city conceived from scratch as a mix of country and city. His insight was to conceive the city as an interaction between a city with jobs and opportunity, but with pollution, and the countryside with fresh air and cheap land, but with fewer opportunities, each one acting as magnets attracting and repelling people. He invented a third magnet, The Garden City, which combined the most attractive elements of both city and countryside (Howard, 1902). Garden city was the Songdo of its day (Townsend 2013) that galvanized architects, engineers and social planners in search of a rational and comprehensive approach to building a city. Howard’s approach was excoriated by Jane Jacobs in his Death and Life of Great American Cities (1961) for not giving room to real life: “He conceived of good planning as a series of static acts; in each case, the plan must anticipate all the needed… He was uninterested in the aspects of the city that could not be abstracted to serve his utopia”. As Dennis Hardy (1991) put it, Howard’s garden cities were a quasi-utopia of a perfect city in an imperfect world (while communist and fascist utopias have dreamed of the city as a perfect city in a perfect world). Unable to evolve, the garden city dream, not relying on a global systemic architecture, has degenerated in the banal reality of suburban sprawl.
The same risk exists today with digital technologies, which could revive the ideal city dream, under the impulse of the big players such as Cisco, IBM, Siemens, GE … who have an interest in a top-down and deterministic approach that reduce smart cities to the adoption of their “intelligent” technology.
5 What makes a city smart?
In their analysis of present smart cities initiative, Neirotti et al. (2013) notice that there is no practice that encompasses all the domains, hard and soft, of the cities. The most covered domains are hard ones: transportation and mobility, natural resources and energy. Government is the domain in which the cities report the lowest number of initiatives. More, in the present smart cities research program, there is an inverse correlation between investment in hard and soft domains, smart government being still the poor relative in smart cities initiatives, while cities that have invested in hard domains are not necessarily more livable cities. In fact, two models emerge from Neirotti et al. survey: one focused on technology (with a strong impetus of technology vendors) and another focused on soft aspects, the hard model being dominant. The problem is there are no vendors for soft domains apart from the citizens themselves whereas systemic integration relies on soft domains, mainly taking into account the context and valuing social capital.
These approaches are dead ends, as analyzed by Adam Greenfield in his pamphlet Against the Smart City (2014). Promoted by vendors of technology, the ideology of the smart city is a techno-centric approach that relies on a top-down methodology that has produced the non-habitable cities of Songdo, Masdar, Plan IT valley… The pamphleteer Evgueny Morozov has excoriated this mood in his To Save the World Click Here as “solutionism” that we may sum up as “My technology is the solution, so your problem is the one solved by my technology”.
We might think of the city as an adaptive system which has the same internal coherence as the medieval city, but being open to the turbulence of the external world, an archetype of a quasi-smart city of today being Singapore.
A smart city as an autopoietic ecosystem must be designed as an imperfect city in an imperfect world able to reframe itself according to the evolution of its environment. Therefore, integration is not made once and for all but is a permanent process all along the urban lifecycle. A smart integration is made according to the ends of the city and must be citizen-centered and not techno centered. The “good life” is the basic question of political philosophy since Aristotle. It is an ethical issue that will result from political and strategic debates among the stakeholders.
An autopoietic system is “a network of processes of production (transformation and destruction) of components which: (i) through their interactions and transformations continuously regenerate and realize the network of processes that produced them; and (ii) constitute it as a concrete unity in space in which they (the components) exist by specifying the topological domain of its realization as such a network.” (H. Maturana). Autopoiesis is a property of human dissipative systems: strong entropy and correlative capabilities to reproduce itself permanently thanks to its internal interactions. This property makes the system able to face with the rapid changes of the environment: “This generalized view of autopoiesis considers systems as self-producing not in terms of their physical components, but in terms of its organization, which can be measured in terms of information and complexity. In other words, we can describe autopoietic systems as those producing more of their own complexity than the one produced by their environment”. (Gershenson, 2015)
As a result, the urban system scales from local actions and interactions that lead to global patterns which can only be predicted from the bottom-up (Miller, Page 2007). In this new view of the city being the result of emergent patterns, we need to focus on the role of citizens and direct democracy.
6 Why do we need strong citizen-based interactions within the urban system?
After the city of Christchurch (NZ) has been destroyed by an earthquake in 2011, the government of NZ proposed to rebuild the city based on a traditional top-down approach. The answer of Lianne Dailzel, the newly elected mayor, was to rely on citizens’ intelligence initiatives insisting on the fact that a resilient city able to withstand a shock as an earthquake needed to be built bottom-up mobilizing empirical mundane knowledge and creating the conditions to appropriate scientific knowledge.
The second reason to plead for bottom-up approaches is the economy. An economic structure based on synergies on economic activities is the condition to wealth creation which reinforces itself through the interaction of a political power based on the Common Good (Reinert, 2006, Rochet, 2012)
In the case of FFF (Failed, Fragile and Failing states) Kattel and Reinert (2009) note that “State failure and fragility are often preceded, or at least accompanied, by failure and fragility of cities”. When a city sprawl out of control, it produces negative externalities without positive synergies. “The missing link in the economics is related to the lack of increasing returns based on « coopetitive » diffusion of means in a predictable and conducive environment. (…) productive governance often enforces the development of sustainable productive structures based usually on a participatory system. The more the participatory system is closed to democracy and shared economic growth with special focus on health, education and communication infrastructure building, more quickly the divergence between countries narrow down » (Reinert & Kattel, 2009).
The third reason is the technological intensity of smart cities.
• Citizen is at the interface of technological devices which consume and produce data (e.g. The smartphone). The frontier between production and consumption is blurred more than in other cases of information economy (McLuhan). In a rapid innovative system, the citizen is a lead user of the innovation process (Von Hippel).
• The power of these technical systems requires strong political control to be both fully efficient and not becoming the level of a totalitarian system (Simondon, 1957).
7 Distributed sense-making as a theoretical framework for a processual approach of direct democracy
As forces of globalization and innovation have raised the levels of cultural and technological diversity in our different social systems, including the cities, the ability to adapt to changing environments and the ability of individuals and groups to make good sense out of the situations that they participate in has become increasingly important. In such a context how can we organize bottom-up citizen-centered innovation approaches that catalyze collective sensemaking at the scale of a given territory?
7.1 Distributed sensemaking and complexity
Such sensemaking (Weick, 1995; Blackler,1995) requires an appreciation of the highly tacit and distributed nature of knowledge involved as well as the complex, social practices through which such knowledge develops. Therefore, a natural link can be established between the previous developments on smart cities and the sensemaking perspective that allows to view organizations and more broadly, human groups (Weick 1995) as emergent phenomena or complex, adaptive systems (Cicmil et al., 2009; Stacey, 2001; Weick, 2005) that may evolve or learn in conjunction with environments that they in part create. Following Weick (2005), “the ideas of complexity theory, when combined with those of sensemaking theory, provide a powerful combination to understand thick, dense events that have high stakes” and therefore applying the sensemaking perspective to the complexity of cities as emergent phenomena offer promising research opportunities.
Cities from the standpoint of their human and social constituencies, following previous developments, can be considered as “loosely coupled systems” (Weick, 2005). Therefore, in order to better adapt that image to complexity thinking, we can describe autopoietic cities as emerging social orders where “Groups composed of individuals with distributed-segmented, partial-images of a complex environment can, through interaction synthetically construct a representation of it that works; one which, in its interactive complexity, outstrips the capacity of any single individual in the network to represent and discriminate events […] Out of the interconnections, there emerges a representation of the world that none of those involved individually possessed or could possess” (Taylor and Van Every, 2000).
The basic theme implied by this statement is that variations in interconnection produce variations in the representations that are synthetically constructed. In the case of direct democracy initiatives, gathering a broad set of individual / group contributions at its beginning, “mere assembly does not guarantee meaning. Each part is meaningless until it is related to some other part whose meaning, in turn, is dependent on the meaning of the initial part. Making meaning is an iterative process” (Weick, 2005). Stated differently, in a reactive world, a highly-refined planning system as is being used in the classical top-down city development approaches, is less crucial than “the capability to make sense out of an emerging pattern” (Weick, 2005).
Relating these developments with our research question, how can we leverage distributed sensemaking concepts and practices to the complexity attributes of a city viewed as autopoietic systems? In his 2005 book updating Sensemaking perspective, especially with regards distributed sensemaking viewed through the lens of complexity, Weick proposes equivalent statements linking between complexity themes and concepts from cognition, sensemaking, workflow interdependence, and interrelating. Weick’s argument is that these substitutions retain the spirit of complexity analysis but customize those insights so that they better fit human groups enactment and organizing (Weick, 2005), which is at the core of direct democracy initiatives.
7.2 Collective sensemaking
A central theme in sensemaking (Weick Sutcliffe & Obstfeld-2005) is that people organize to make sense of equivocal inputs they get from their environment and “enact” this sense back into the world to make that world more orderly. By enacting Weick means the actions of people that aims at transforming their environment which, recursively transforms their own actions (Weick 1979, 1995)
Sensemaking is commonly understood as a process in which individuals or groups attempt to interpret novel and ambiguous situations (Weick, 1995). The process begins when people confront events or tasks they cannot readily interpret using available mental structures (Kiesler & Sproull, 1982), which is the case when people are asked to change their familiar course of action, for instance in direct democracy local initiatives (e.g changing the way we collectively behave in our district or neighborhood with regards specific issues like transport, common spaces etc).
Collective sensemaking occurs as individuals exchange provisional understandings and try to agree on consensual interpretations and a course of action (Weick, Sutcliffe, & Obstfeld, 2005).
As it has been described by Weick et al (2005), hereafter there are several distinguishing features of sensemaking, including: “its genesis in disruptive ambiguity, its beginnings in acts of noticing and bracketing, its mixture of retrospect and prospect, its reliance on presumptions to guide action, its embedding in interdependence, and its culmination in articulation that shades into acting thinkingly” (Weick, et al, 2005: 413).
Early empirical applications of sensemaking theory focused on discrepancies between a current and an expected state of the world (e.g., Weick, 1988, 1993). Research in this line of inquiry investigated individual and group-level responses to unfamiliar events that occur when people confront circumstances that do not fit available knowledge structures, thus in a retrospective manner (Weick, 1979, 1995).
According to models of sensemaking arising from these studies, individuals respond to cues that disrupt the ordinary, predictable flow of experience and suggest a gap between the reality as it seems to be and how they expected it to be (Barr, 1998), These cues trigger conscious attempts to interpret unexpected occurrences retrospectively and to bring order into ambiguous realities open to multiple interpretations.
Another relevant line of inquiry has explored circumstances under which individuals and groups cope with ambiguous situations that require them to develop novel understandings and engage in forward-looking thinking to “structure the future by imagining some desirable (albeit ill-defined) state” (Gioia & Mehra, 1996: 1229). This different type of sense-making has been referred to as “prospective” (Gioia, 1986) or “future-oriented” sense-making (Gephart, Topal, & Zhang, 2010).
Even though prospective sensemaking underpins fundamental organizational processes, such as those mentioned above, this process is underresearched and undertheorized (Stigliani & Ravasi, 2012). Available models provide an insightful but incomplete conceptualization, as little is known about the social interaction and cognitive work that underpin the transition between individual development of new interpretations (Hill & Levenhagen, 1995) and collective engagement in giving a sense of emerging interpretations to relevant stakeholders (Gioia & Ghittipeddi,1991).
7.3 A processual approach of collective sensemaking in the context of a direct governance initiative
Complex phenomena, such as collective, citizen-based initiatives aiming at “enacting” the social environment (Weick, 1979) are hard to study when it comes to collecting and analyzing qualitative process data (Langley, 1999). Process data tends to be eclectic, drawing on phenomena such as changing relationships, thoughts, feelings, interpretations, artefacts etc. This leads inevitably to the consideration of multiple levels of analysis that are sometimes difficult to separate from one another, which further complicates the sensemaking process (Langley, 1999). Following Langley (99), we propose to use the “temporal bracketing” (Fig. 1) as a sensemaking strategy that “fits well with a nonlinear dynamic perspective” on social processes and can quite easily handle the eclectic data such as events, variables, interpretations, one might expect when trying to analyze bottom-up citizen-centered interactions. The purpose is to produce relevant insights on the fundamental process drivers and mechanisms of collective sensemaking in such complex, multi-level social contexts.
Our ongoing research shall be grounded on a case of a participative design of the brand identity of a seaside resort in the northern part of Morocco, on the Mediterranean Sea, initiated by the “Société de Développement de Saidia” (SDS), a subsidiary of the “Caisse de Dépôt et de Gestion”, the main actor in territory and infrastructure development in Morocco. While this initiative had started as a mere exercise of territory branding, in 2016, it has quickly appeared that without a proper participation of the different stakeholders involved in the broader territory, including the countryside and the citizens of the historical Saidia village, no significant and sustainable result can be reached. Our research project aims at accompanying this dynamic through an intervention research assignment under discussion.
Fig. 1. adapted from Table 1. “Seven strategies for Sensemaking” (in “Strategies for theorizing from process data”; Langley, 1999:696)
In this paper, we’ve analyzed the smart cities dynamics through the lens of complex systems architecture, stating that the smartness of a city consists of this continuous learning process that relies on interactions between basic cells and actors of the city.
In this new view of the city as the result of emergent patterns, we’ve focused on the role of citizens, proposing an original perspective of the dynamics underpinning direct democracy initiatives.
To further explore this perspective, we’ve proposed to leverage the Sensemaking theory, with the purpose of defining a processual view of distributed / future-oriented sensemaking as a potential framework for practical approaches to direct democracy, through a grounded action research, involving a re-design project of an industrial park through its actors.
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