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Planning a city is a systematic process that includes time, space, and groups of people who must communicate. However, due to security problems in such war-ravaged countries as Afghanistan, the traditional forms of public participation in the planning process are untenable. In particular, due to gathering space difficulties and culture issues in Afghanistan, women and religious minorities are restricted from joining male-dominated powerholders’ face-to-face meetings which are nearly always held in fixed places called masjids (religious buildings). Furthermore, conducting such discussions with human facilitation biases the generation of citizen decisions that stimulates an atmosphere of confrontation, causing another decision problem for urban policy-making institutions. Therefore, it is critical to find approaches that not only securely revolutionize participative processes but also provide meaningful and equal public consultation to support interactions among stakeholders to solve their shared problems together. Toward this end, we propose a joint research program, namely, crowd-based communicative and deliberative e-planning (CCDP), a blended approach, which is a mixture of using an artificial-intelligence-led technology, decision-support system called D-Agree and experimental participatory planning in Kabul, Afghanistan. For the sake of real-world implementation, Nagoya Institute of Technology (Japan) and Kabul Municipality (Afghanistan) have formed a novel developed and developing world partnership by using our proposed methodology as an emerging-deliberation mechanism to reframe public participation in urban planning processes. In the proposed program, Kabul municipality agreed to use our methodology when Kabul city needs to make a plan with people. This digital field study presents the first practical example of using online decision support systems in the context of the neighborhood functions of Gozars, which are Kabul’s social and spatial urban units. The main objective was to harness the wisdom of the crowd to innovative suggestions for helping policymakers making strategic development plans for Gozars using open call ideas, and for responding to equal participation and consultation needs, specifically for women and minorities. This article presents valuable insights into the benefits of this combined approach as blended experience for societies and cities that are suffering long-term distress. This initiative has influenced other local Afghan governments, including the cities of Kandahar and Herat as well as the country’s central government’s ministry of urban planning and land, which has officially expressed its intention to collaborate with us.

The intricate relationship between structure and function spans various disciplines, from biology to management, offering insights into predicting interesting features of complex systems. This interplay is evident in online forums, where the organization of the threads interacts with the message’s meaning. Assessing readability in these discussions is vital for ensuring information comprehension among diverse audiences. This assessment is challenging due to the complexity of natural language compounded by the social and temporal dynamics within social networks. One practical approach involves aggregating multiple readability metrics as a consensus alignment. In this study, we explore whether the structural complexity of online discussions can predict consensus readability without delving into the semantics of the messages. We propose a consensus readability metric derived from well-known readability tests and a complexity metric applied to the tree structures of Reddit discussions. Our findings indicate that this proposed metric effectively predicts consensus readability based on the complexity of discourse structure.

The skill to take part in and to contribute to debates is important for informal and formal learning. Especially when addressing highly complex issues, it can be difficult to support learners participating in effective group discussion, and to stay abreast of all the information collectively generated during the discussion. Technology can help with the engagement and sensemaking of such large debates, for example, it can monitor how healthy a debate is and provide indicators of participation's distribution. A special framework that aims at harnessing the intelligence of - small to very large - groups with the support of structured discourse and argumentation tools is Contested Collective Intelligence (CCI). CCI tools provide a rich source of semantic data that, if appropriately processed, can generate powerful analytics of the online discourse. This study presents a visualisation dashboard with several visual analytics that show important aspects of online debates that have been facilitated by CCI discussion tools. The dashboard was designed to improve sensemaking and participation in online debates and has been evaluated with two studies, a lab experiment and a field study in the context of two Higher Education institutes. The paper reports findings of a usability evaluation of the visualisation dashboard. The descriptive findings suggest that participants with little experience in using analytics visualisations were able to perform well on given tasks. This constitutes a promising result for the application of such visualisation technologies as discourse-centric learning analytics interfaces can help to support learners' engagement and sensemaking of complex online debates.

This article aims to lay out the reflections resulting from the presentation of Marc Jeannotte entitled “What ways of civic life do we want in our metropolises?”. Emphasizing the link between urban transitions and the human project, the speaker advanced the essential role of citizen participation and the citizen as an actor in these transitions. Our analysis of this questioning is based on three notions of the theory of action: the structural fields of action, the actors and the representations of the actors. By applying this conceptual framework to the discussion, we can conclude that to enable collective intelligence in participatory approaches, these three elements must be considered. Thus, the speaker and the discussants place importance on the expertise of citizens and social capital, accessibility to information and the digital divide, diversity of opinions and learning. Further, we identify the lines of questioning to pursue in order to improve our understanding of the forms of citizen participation from the point of view of citizens'representations and strategies of action. Cet article vise à exposer les réflexions engendrées par la présentation de Marc Jeannotte intitulée “Quels modes de vie citoyenne voulons-nous dans nos métropoles?”. Soulignant le lien entre les transitions urbaines et le projet humain, l’intervenant a avancé le rôle essentiel de la participation citoyenne et du citoyen comme un acteur de ces transitions. Notre analyse de ce questionnement est basée sur trois notions de la théorie d’action : les champs structurels d’action, les acteurs et les représentations des acteurs. En appliquant ce cadre conceptuel à la discussion, nous pouvons conclure que pour permettre l’intelligence collective dans les démarches participatives, il faut prendre en compte ces trois éléments. Ainsi, l’intervenant et les discutants mettent l’importance sur l’expertise des citoyens et le capital social, l’accessibilité à l’information et la fracture numérique, la diversité des opinions et l’apprentissage. Ensuite, nous identifions les lignes de questionnement à poursuivre afin d’améliorer notre compréhension des formes de la participation citoyennes du point de vue des représentations et des stratégies d’action des citoyens.

We review recent research on collective intelligence, which we define as the ability of a group to perform a wide variety of tasks. We focus on two influences on a group's collective intelligence: (a) group composition (e.g., the members' skills, diversity, and intelligence) and (b) group interaction (e.g., structures, processes, and norms). We also call for more research to investigate how social interventions and technological tools can be used to enhance collective intelligence.

A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton’s discovery of the “wisdom of crowds” [Galton F (1907) Nature 75:450–451], theories of collective intelligence have suggested that the accuracy of group judgments requires individuals to be either independent, with uncorrelated beliefs, or diverse, with negatively correlated beliefs [Page S (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies]. Previous experimental studies have supported this view by arguing that social influence undermines the wisdom of crowds. These results showed that individuals’ estimates became more similar when subjects observed each other’s beliefs, thereby reducing diversity without a corresponding increase in group accuracy [Lorenz J, Rauhut H, Schweitzer F, Helbing D (2011) Proc Natl Acad Sci USA 108:9020–9025]. By contrast, we show general network conditions under which social influence improves the accuracy of group estimates, even as individual beliefs become more similar. We present theoretical predictions and experimental results showing that, in decentralized communication networks, group estimates become reliably more accurate as a result of information exchange. We further show that the dynamics of group accuracy change with network structure. In centralized networks, where the influence of central individuals dominates the collective estimation process, group estimates become more likely to increase in error.

Within current debates about the future impact of Artificial Intelligence (AI) on human society, roughly three different perspectives can be recognised: (1) the technology-centric perspective, claiming that AI will soon outperform humankind in all areas, and that the primary threat for humankind is superintelligence; (2) the human-centric perspective, claiming that humans will always remain superior to AI when it comes to social and societal aspects, and that the main threat of AI is that humankind’s social nature is overlooked in technological designs; and (3) the collective intelligence-centric perspective, claiming that true intelligence lies in the collective of intelligent agents, both human and artificial, and that the main threat for humankind is that technological designs create problems at the collective, systemic level that are hard to oversee and control. The current paper offers the following contributions: (a) a clear description for each of the three perspectives, along with their history and background; (b) an analysis and interpretation of current applications of AI in human society according to each of the three perspectives, thereby disentangling miscommunication in the debate concerning threats of AI; and (c) a new integrated and comprehensive research design framework that addresses all aspects of the above three perspectives, and includes principles that support developers to reflect and anticipate upon potential effects of AI in society.

Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group’s ability to work together across a diverse set of tasks. We further show that CI is predicted by the proportion of women in the group, mediated by average social perceptiveness of group members, and that it predicts performance on various out-of-sample criterion tasks. We also find that, overall, group collaboration process is more important in predicting CI than the skill of individual members.