direct democracy as the keystone of smart city governance as a complex system

Direct democracy as the keystone of smart city governance as a complex system

Claude Rochet 1, Amine Belemlih 2

1 Professeur des universitésLAREQUOI Université de Versailles Saint Quetin en [email protected] PhD studentUniversité Paris Dauphine

mailto:[email protected]

02/05/2023EGPA UTRECHT

Abstract We consider the smart city not as an

addition of « smarties » (technological devices) but as system capable of evolution all along its lifecycle. This cycle has been 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.

Literature on cities as evolving ecosystems (Batty 2015) considers this evolutionary process can’t be steered in 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.

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 process.

Understanding urban dynamicsThe city as a self regulating ecosystemHow direct democracy may work

Summary


What a smart city can’t be

A collection of « smarties » A techno centric city A city without past

A deterministic system

Smart city = Integrated complex system

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Middle age cities were smart: organic development, common good, synergies between economic activities

Common good

Vivere politico

Economic welfare

Pivate good

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Top down mono functional cityTogliatti (Russia):

Monocities have turned to be an obstacle to growth in Russia, representing up to 31% GDP.


A (really) smart city is an emerging ecosystem Smart city framework= A great number of interactions between

people x connected objects whose quantity and speed is in dramatic increase at date.

The behavior of a system is predictable when the sequence of transitions from one state to another can be described.

Emergence takes place when the space of possible states or rules of transitions change: the city can’t be described by the model that described it until then. (Heylighen & Joslyn 1991)

Modeling emergence implies:1. Mapping the properties, desirable an undesirable, the system

can take. 2. The values attached to theses properties in a precise context.



A smart city is an integration of two kinds of systems

Hard systems may be modeled thanks to the laws of physics (conservative systems)

Soft systems can’t be modeled with the laws of physics (dissipative systems)

- Social sciences- Big data- Autopoeisis

- Multi-agents modeling

The key of the success is here…

… while business is there

Politics must prevail on a bottom up basis


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Cities scaling laws

Densité

Pote

ntie

l d’

inte

rcon

nexi

ons

Y=x2 Loi de Metcalfe

But…..

Distance

Inte

rcon

nexi

ons

réel

les

Lois de Von Thünen Tobler

Exte

rnal

ités +

et _

Taille

But…..

Taille

Nom

bre

de v

illesLois de Marshall West Bettencourt

Lois de Zipf

Combining these laws:

02/05/2023Size x Number of cities

Conn

ectio

ns x

wea

lth

New town

Clustering medium size cities

New townDefining the perimeter and the« in and out » interrelations of the system is a key issue in cities’system design

Understanding urban dynamics

The city as a self regulating ecosystemHow direct democracy may work


Urban dynamics: from neo cybernetics to autopeosis

First order cybernetics (Forrester): The city as a self regulating system… ... Or a super command and control machinery

(Rio) The 2nd order of cybernetics includes

autopoeisis of human dissipative systems The complexity of the city is a combination

of several laws There is a positive correlation between

growth of the city size and its complexity.... ... But there is a good and a bad

complexity

Understanding urban dynamics

The city as a self regulating ecosystemHow direct democracy may work

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EGPA UTRECHT

Good and bad complexity

At a certain point growing complexity produces more negative than positive externalities and become unmonitorable

Bad complexityGood complexity

Growing size

Grow

ing

com

plex

ity

E. g. Detroit, Russian monocities…


A quasi zero order cybernetics unable to self regulate


First order cybernetics city

The myth of the super mind and perfect control


Autopoeisis: Why and How?

An autopoeitic 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

Autopoeisis is a property of human dissipative system: strong entropy and correlative capabilities to reproduce itself permanently thanks to its internal interactions


Autopoeisis: Why and How?

Autopoeisis makes the system able to face with the rapid changing 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". C. Gershenson

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Autopeoietic system integration works bottom-up based on “ordinary actions of the people”

NO! An evolutionary process

Integration process is bottom-up…… based on ordinary interactions

We must understand how ordinary people behave

Q: Is there an architect with a master plan?


Why do we need strong citizen based interactions within a system? (1)

Economy: An economic structure based on synergies of economics activities

is the condition to wealth creation which reinforces itself through interaction of a political power based on the Common Good (Reinert, 2006, Rochet, 2012)

FFF (Failed, Fragile and Failing states) : The missing link is related to the lack of increasing returns based on « coopetitive » diffusion of means (…) productive governance often enforces the development sustainable productive structures based usually on a participatory system.

“State failure an fragility are often preceded, or at least accompanied, by failure and fragility of cities” (Reinert & Kattel, 2009)

“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)


Resilience: A smart city is a highly internally connected facing with

a turbulent environment, that challenges its resilience. Strong social capabilities enforces the autopoeitic

properties of the system, and consequently its resilience.

E.g. Christchurch (NZ)


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Citizen is at the interface of technological devices which consume and produce data (e.g. The smart phone)

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).


Direct democracy has a strong record in the management of cities and complex systems

Middle age smart cities (L. Mumford): mix of formal and informal institutions, strong shared system of beliefs (smart cities without architect)

Critical correlations between civic involvement and wealth creation (Lorenzetti: The effect of good government)


Schumpeterian economics correlates synergies between activities, political freedom and common weal.

Traditional decision making system may help modeling a resilient human system e.g: ongoing research project of modeling an eco-efficient drinking water network in Angola with the palaver tree


New paradigms in public decision making

Polycentric governance (Ostrom): deciding in small units on a large scale

Bottom up decision processes : e.g. Michael Batty modeling decision process as a Markov chains to bring back the city in a ergodic state

Large deliberative upfront processes reduce uncertainty e.g. The Parable of the Hare and the Tortoise: Small Worlds, Diversity, and System Performance (Lazer & Friedman 2005)

« In short, cities are more like biological than mechanical systems. The rise of the sciences of complexity, which have changed the direction of system theory from top down to the bottom-up is one that treats such systems as open, based more on the product of an evolutionary process than a grand design » Michael Batty « A new Science of Cities » 2015


New techniques ariseDesign thinking (Stanford, Ecole des Ponts)


A paradoxical research question:Can we conceive the gov’t of a city that should not need a government?

At date, if we assume the benchmark of a smart city is Singapore, it’s not really a democracy.

At date, we don’t know large system that have developped spontaneously self organizing properties .

Rules, as a genetic code of an ecosystem, are the result of a long term learning process: Cf. biomimicry

A Machiavellian approach: The Prince is to fix the good institution from the top down giving the citizens the rights to challenge the power of the few in charge.

We have a lot of reference of direct democracy experiences, how they were born, how they died.