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The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT.

Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education and organization of work.

The book will provide a cohesive and holistic treatment of Social Collective Intelligence, including challenges emerging in various disciplines (computer science, sociology, ethics) and opportunities for innovating in various application areas.

By going through the book the reader will gauge insight and knowledge into the challenges and opportunities provided by this new, exciting, field of investigation. Benefits for scientists will be in terms of accessing a comprehensive treatment of the open research challenges in a multidisciplinary perspective. Benefits for practitioners and applied researchers will be in terms of access to novel approaches to tackle relevant problems in their field. Benefits for policy-makers and public bodies representatives will be in terms of understanding how technological advances can support them in supporting the progress of society and economy.





Towards the Ethical Governance of Smart Society

This chapter is concerned with how social order is established within collectives and the ethical problems that arise when we attempt to create and direct collectives towards particular ends. It draws on our work to establish governance principles for Smart Society—an EU project aiming to engineer Collective Adaptive Systems comprised of people and machines with diverse capabilities and goals that are able to tackle societal grand challenges. We examine how social values are implicated in and transformed by Collective Adaptive Systems, and suggest approaches to multilevel governance design that are responsive to emergent capabilities and sensitive to conflicting perspectives. Finally we illustrate our approach with a worked example of a sensor-based system in a care setting.
Mark Hartswood, Barbara Grimpe, Marina Jirotka, Stuart Anderson

Collective Intelligence and Algorithmic Governance of Socio-Technical Systems

In applying the methodology of sociologically-inspired computing to the idea of self-governing institutions for common-pool resource management, an algorithmic basis for self-organising resource allocation in open computer systems and networks has been established. This algorithmic base is not intended to be a testable model of how people manage decentralised resource allocation: on the other hand, it does raise the issue of: what happens when these computer models are made manifest in socio-technical systems for management of resources like energy, water, transport, and so on. This chapter investigates this issue from the perspective of decentralised Community Energy Systems, in which societies of people and societies of ‘agents’ are interleaved in a form of collective social intelligence. Two systems for demand-side self-organisation are presented, one based on collective awareness in a ‘serious game’, the other based on representation and reasoning with an electronic form of social capital. These systems suggest an implementation route for socio-technical systems, comprising both people and agents, in which ‘fair’ treatment of people is grounded in algorithms executed by the agents.
Jeremy Pitt, Dídac Busquets, Aikaterini Bourazeri, Patricio Petruzzi

A Taxonomic Framework for Social Machines

Within the context of the World Wide Web, we have witnessed the emergence of a rich range of technologies that support both collaboration and distributed processing. Applications such as Wikipedia, for instance, have demonstrated the power and potential of the Web to facilitate the pooling of geographically dispersed knowledge assets. The result has been the creation of the world’s largest online encyclopedia, available for free in more than 200 languages for everyone to access and use.
Paul Smart, Elena Simperl, Nigel Shadbolt

The Mathematician and the Social Computer: A Look into the Future

In our evolving world, machines interact more and more in natural human terms across a range of activities and applications. By combining the strengths of human mathematical reasoning and machine capabilities for increasingly high level automated processing, we have a new paradigm for problem solving. We are closer every year to having human and intelligent agents brainstorming together. In the words of a modern philosopher, “The machine frees the human mind, and challenges it to new horizons.” Thus, our mathematician just might be able to help an intelligent agent with some of its major challenges, and vice versa.
Martin Charles Golumbic

Twelve Big Questions for Research on Social Collective Intelligence

In this chapter we present and discuss twelve ‘big questions’ for research on social collective intelligence. Such research questions represent as many scientific challenges that the relevant research communities should tackle in order to move the understanding and engineering of social collective intelligence systems to the next level.
Stuart Anderson, Daniele Miorandi, Iacopo Carreras, Dave Robertson



Privacy in Social Collective Intelligence Systems

The impact of Social Collective Intelligent Systems (SCIS) on the individual right of privacy is discussed in this chapter under the light of the relevant privacy principles of the European Data Protection Legal Framework and the OECD Privacy Guidelines. This chapter analyzes the impact and limits of profiling, provenance and reputation on the right of privacy and review the legal privacy protection for profiles. From the technical perspective, we discuss opportunities and challenges for designing privacy-preserving systems for SCIS concerning collectives and decentralized systems. Furthermore, we present a selection of privacy-enhancing technologies that are relevant for SCIS including anonymous credentials, transparency-enhancing tools and the PrimeLife Policy Language (PPL) and discuss how these technologies can help to enforce the main legal principles of the European Data Protection Legal Framework.
Simone Fischer-Hübner, Leonardo A. Martucci

The Future of Social Is Personal: The Potential of the Personal Data Store

This chapter argues that technical architectures that facilitate the longitudinal, decentralised and individual-centric personal collection and curation of data will be an important, but partial, response to the pressing problem of the autonomy of the data subject, and the asymmetry of power between the subject and large scale service providers/data consumers. Towards framing the scope and role of such Personal Data Stores (PDSes), the legalistic notion of personal data is examined, and it is argued that a more inclusive, intuitive notion expresses more accurately what individuals require in order to preserve their autonomy in a data-driven world of large aggregators. Six challenges towards realising the PDS vision are set out: the requirement to store data for long periods; the difficulties of managing data for individuals; the need to reconsider the regulatory basis for third-party access to data; the need to comply with international data handling standards; the need to integrate privacy-enhancing technologies; and the need to future-proof data gathering against the evolution of social norms. The open experimental PDS platform INDX is introduced and described, as a means of beginning to address at least some of these six challenges.
Max Van Kleek, Kieron OHara

An Auditable Reputation Service for Collective Adaptive Systems

The reputation of subject is a measure of a community’s opinion about that subject. A subject’s reputation plays a core role in communities within Collective Adaptive Systems (CAS) and can influence a community’s perception and their interactions with the subject. Their reputation can also affect computational activities within a system. While reputation is frequently used in CAS, there is a lack of agreed methods for its use, representation, and auditability. The aim of this chapter is to investigate key facets of an auditable reputation service for CAS, we contribute: Use cases for reputation and provenance in CAS, which are categorised into functional, auditable, privacy and security, and administrative; and a RESTful Reputation API, which allows users access to subject feedback and to access feedback reports and reputation measures.
Heather S. Packer, Laura Drăgan, Luc Moreau

Applications and Case Studies


Surfacing Collective Intelligence with Implications for Interface Design in Massive Open Online Courses

The massive open online course (MOOC) has gained significant popularity in the last few years, garnering enrolment rates usually in the order of tens of thousands of teenagers and adults [16].With so many people congregating online to learn, harnessing the enrolled learners’ social collective intelligence (SCI) becomes a very real possibility. Moreover, the sorts of learner-leaner and learner-platform interactions needed to realise the MOOC as an SCI platform align strongly with educational paradigms such as constructivism [9];lending a pedagogical plausibility to using MOOCs in this way. Our study aims to capture how learners actively make the learning content within a MOOC relevant to their personal concerns. An analysis of 670 qualitative responses to an open-ended question in a live MOOC titled ‘Internet History, Technology, and Security’ [6]provides some understanding of the ‘relational work’. This helps us conceive of MOOC interface designs which simultaneously support SCI. With few theories existing which concern SCI and MOOCs, our empirical study is timely.
Anna Zawilska, Marina Jirotka, Mark Hartswood

Who Were Where When? On the Use of Social Collective Intelligence in Computational Epidemiology

A triangular (case, theoretical, and literature) study approach is used to investigate if and how social collective intelligence is useful to computational epidemiology. The hypothesis is that the former can be employed for assisting in converting data into useful information through intelligent analyses by deploying new methods from data analytics that render previously unintelligible data intelligible. A conceptual bridge is built between the two concepts of crowd signals and syndromic surveillance. A concise list of empirical observations supporting the hypothesis is presented. The key observation is that new social collective intelligence methods and algorithms allow for massive data analytics to stay with the individual, in micro. It is thus possible to provide the analyst with advice tailored to the individual and with relevant policies, without resorting to macro (statistical) analyses of homogeneous populations.
Magnus Boman

Social Collective Awareness in Socio-Technical Urban Superorganisms

Smart cities are characterized by the close integration of ICT devices and humans. However, the vast majority of current deployments of smart technologies relies on sensing devices collecting data and data mining techniques squeezing little meanings out of them. Nevertheless, we believe that citizens integrated with ICT technologies could collaboratively constitute large-scale socio-technical superorganisms supporting collective awareness and behaviours. This paper clarifies our vision on urban superorganisms, identifies the key challenges towards their actual deployment and proposes a prototype architecture supporting their development.
Nicola Bicocchi, Alket Cecaj, Damiano Fontana, Marco Mamei, Andrea Sassi, Franco Zambonelli

Collective Intelligence in Crises

New practices of social media use in emergency response seem to enable broader ‘situation awareness’ and new forms of crisis management. The scale and speed of innovation in this field engenders disruptive innovation or a reordering of social, political, economic practices of emergency response. By examining these dynamics with the concept of social collective intelligence, important opportunities and challenges can be examined. In this chapter we focus on socio-technical aspects of social collective intelligence in crises to discuss positive and negative frictions and avenues for innovation. Of particular interest are ways of bridging between collective intelligence in crises and official emergency response efforts.
Monika Büscher, Michael Liegl, Vanessa Thomas

The Lean Research: How to Design and Execute Social Collective Intelligence Research and Innovation Projects

In this chapter we advocate the use of a research methodology, that we term ‘the lean research’, for research and innovation projects in the field of Social Collective Intelligence. Motivated by the unique features of Social Collective Intelligence setting, in particular its people-centric nature and its multidisciplinary character, we propose a set of guidelines for maximising the success chances and the potential impacts of projects in the field. A parallel with the ‘lean startup’ approach currently getting popular among Web entrepreneurs and high-tech companies is used extensively throughout the chapter.
Daniele Miorandi, Iacopo Carreras, Imrich Chlamtac
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