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In the context of a citizen lab, this article describes how a vanguard of activists, designers, scholars and participation practitioners were involved in a participatory prototyping process. CoGovern was designed as an online participation tool whose focus is to incorporate citizen preferences in local policy making. It is aimed at supporting informed and transparent participatory processes while reducing the ability of sponsoring authorities to “cherry-pick” policy proposals and avoid providing explanations. This article proposes a decision-making processthat incorporates artificial intelligence techniquesinto a collective decision process and whose result is mainly based on standard optimization techniques rather than vote-counting.
DOI: 10.4018/IJPADA.2018100101
Volume 5 • Issue 4 • October-December 2018
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
José Luis Fernández-Martínez, Institute of Advanced Social Studies (IESA-CSIC) & University of Granada, Granada, Spain
Maite López-Sánchez, Universitat de Barcelona, Barcelona, Spain
Juan Antonio Rodríguez Aguilar, Articial Intelligence Research Institute (IIIA-CSIC), Cerdanyola, Spain
Dionisio Sánchez Rubio, Universitat Politècnica de València (UPV) & Escola d’Art i Superior de Disseny de València
EASD, Valencia, Spain
Berenice Zambrano Nemegyei, MediaLab Prado, Madrid, Spain
In the context of a citizen lab, this article describes how a vanguard of activists, designers, scholars
and participation practitioners were involved in a participatory prototyping process. CoGovern was
designed as an online participation tool whose focus is to incorporate citizen preferences in local
policy making. It is aimed at supporting informed and transparent participatory processes while
reducing the ability of sponsoring authorities to “cherry-pick” policy proposals and avoid providing
explanations. This article proposes a decision-making process that incorporates artificial intelligence
techniques into a collective decision process and whose result is mainly based on standard optimization
techniques rather than vote-counting.
Artificial Intelligence, CoDesign, Collective Intelligence, Decision Making, Participatory Democracy,
Participatory Prototyping
The field of democratic innovations (Fung & Wright, 2001; Smith, 2009) is currently crowded with
digital tools aimed at facilitating deliberative and participatory processes. Frequently, these tools
emerge within activism environments characterised by a high level of civic engagement and political
interest. In particular, most of these environments largely embrace the principles promoted by those
social movements in defense of free and open source software such as More recent
initiatives also promulgate the coproduction of knowledge between the general public and the scientific
community such as Citizen Science (Socientize Consortium, 2013).
This article stems from one of those spaces: MediaLab Prado, a Citizen Lab located in Madrid
(Spain). This experimental Lab organized a Workshop for Collective Intelligence on Democracy whose
Volume 5 • Issue 4 • October-December 2018
main purpose was to prototype digital tools addressing the challenges posed by citizen participation
in the age of social media.
We address some of these challenges by focusing on two main questions: How can digital tools
be designed in order to make participatory processes more transparent and accountable? Can artificial
intelligence enhance participatory processes in an objective and publicly auditable manner, without
deviating from participants’ interests?
Firstly, this paper seeks to reflect how a vanguard of activists, designers, scholars and practitioners
currently envision what – according to them will be one of the most common forms of citizen
participation in the coming years. Secondly, it proposes the basis for the future development of
CoGovern, an online citizen participation tool whose focus is to incorporate citizen preferences in
local policy-making. Thirdly, our tool proposal aims to ensure informed and transparent participatory
processes to avoid that sponsoring authorities cherry-pick policy proposals and omit to provide
explanations. And finally, for these purposes, this article proposes a decision-making process which
incorporates artificial intelligence (AI) techniques in order to align citizen preferences, budgetary
constraints and priorities, or strategic objectives about what policies and investments should be
chosen for implementation.
The result has been the initial design of CoGovern, a prototype web application in which citizen
participation is grounded in information fusion (Torra, V. & Narukawa, Y., 2007), argumentation
theories (Awad, E. et al., 2015), and standard optimization techniques. In other words, the main
substantive contribution is to propose a decision-making process in which the outputs – normally
participatory policy proposals – are selected using optimization techniques. The central argument
is that a proposal selection method based on the best possible combination, according to previously
agreed and weighted criteria, instead of the traditional vote-counting system, can enhance participatory
decision making.
The article proceeds as follows. The next section presents the sociological and technological
research background. In particular, it introduces artificial intelligence techniques that can be applied to
decision support in the context of political participatory processes. Next, we present the methodological
approach which is based on a collective intelligence (CI) experiment; more specifically, a case study
about a Citizen Lab is described. Subsequent section presents the resulting prototype design by focusing
on its graphical design, functionalities, and automated decision making. Lastly, some implications
of these types of participatory tools and future research paths are discussed.
Political sociology often distinguishes three decision-making models in democratic regimes:
representative, participatory, and technocratic (Bengtsson & Christensen, 2014). The major
difference between them resides in the actors responsible for the decision making. Thus, in the
representative model, a group of elected politicians are in charge of making decisions, whereas that
is the responsibility of citizens and experts in the participatory and technocratic models, respectively.
Recent public opinion research argues that most citizens prefer decision-making processes that involve
both elected politicians and ordinary people; however, people believe that decisions are solely taken
by elected politicians (Allen et al. 2015; Font et al. 2015, 2017).
On the contrary, in Stealth Democracy, Hibbing and Theiss-Morse (2002) question the existence
of a real demand for more participation. They argue that people actually prefer not to participate but
decisions to be taken “efficiently, objectively and without commotion and disagreement” (2002:143).
Other participation criticisms revolve issues such as the lack of efficiency and the perception that
participatory processes are highly time consuming. This article addresses this tension between a
desire for more opportunities to participate and a demand of political processes to be more objective
and efficient. Overall, our aim is to work towards convergence of diverting positions rather than
their confrontation.
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