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This chapter argues that collective intelligence offers an attractive solution to the problem of the average citizen's ignorance and irrationality. It first illustrates this point by presenting the metaphor of the maze, inspired by Descartes' thought experiment in the Discourse on Method. Next, the chapter sets out the definition of “democracy,” which gains a certain meaning and relevance within the context of this book—as, primarily, an inclusive collective decision procedure, that is, a procedure for collective decisions characterized by the fact that it is inclusive, more or less directly, of all the members of the group for whom decisions need to be made. The chapter then considers the domain of democratic reason and politics, before turning to the concept of democratic reason as the collective intelligence of the people. Finally, the chapter closes with a brief overview of the following chapters.

This concluding chapter returns to the metaphor of the maze and the masses introduced in the first chapter and addresses a few concerns about the possibility of democratic “unreason.” Introducing the dimension of time and reflection over time, the chapter suggests, first, that democracies can learn from their mistakes and, second, that certain democratic institutions and norms serve as cognitive artifacts that help the people control for or correct their potential cognitive failures. Those cognitive artifacts at the level of society include institutions and norms that embody the collective intelligence of the people distributed across both space and time. Democratic reason thus includes the wisdom of the past “many” crystallized into social cognitive artifacts that help reduce democratic unreason. Because of the synchronic and diachronic collective intelligence tapped by democratic institutions, democracy, this chapter concludes, is a gamble worth taking.

Starting with a narrative detailing of the personal experience of being close to the murder of Dutch filmmaker Theo van Gogh on an Amsterdam street, the introduction lays out the crucial role of giving meaning to events for authoritative governance. Based on the assumption that political situations are often far more open than is appreciated the introduction develops the question how to conceive of an authoritative political governance in today's conflict-ridden situations. The Van Gogh case is seen as an illustration of a ‘dislocation’ – a situation where political routine is lifted from its solid institutional hinges. At those moments, the quality of the performance can make claims authoritative or failures. Moreover, government performances influence whether reasoned elaboration may take place. The introduction suggests to break with the separation of style from content and collective intelligence: it is through the presentation of the political self that meaning is given, roles are defined, and narratives of conflict or cohesion are promoted. This introduction sketches the contours of the dramaturgical method used to analyse governance as political drama.

Collective intelligence allows groups of individuals to solve problems which otherwise could not be solved by a single individual. Insect workers have tiny brains, but by functioning as part of a self-organized colony, they find sophisticated solutions to vital organizational problems (e.g., finding a suitable new home or exploiting the best food sources in a changing environment). In consensus decision making, unanimity among workers is crucial. In contrast, combined decision making requires that different groups of workers within the colony choose different options. Communication and learning are often fundamental in collective decision making. However, as workers gain experience, communication may lose importance as an information source for workers. How social insects collectively solve problems parallels decision making in other biological systems (e.g., neuronal networks), and investigation into social insect collective decision making has inspired new solutions to optimization problems in areas such as computer sciences and the organization of communication networks.

Social cognitivism illuminates two of the most important processes in business, leadership and marketing, which turn out to have remarkable similarities. Effectiveness in both endeavors requires understanding cognitive and emotional mechanisms operating in the minds of individuals, and also social mechanisms by which thoughts and emotions are communicated. Both leadership and marketing require elicitation of multimodal semantic pointers that combine verbal, sensory, motor, and emotional information. Leaders and marketers all need to understand the emotional processes of their followers and customers by using theories of emotion (based on semantic pointers, not folk psychology) and modes of empathy ranging from verbal analogy to multimodal rule simulation. For employees and purchasers, emotion is a major contributor to motivations that produce intentions that lead to action.

Howard Rheingold, professor and expert in cultural, social and new digital media fields, who coined the term ‘Virtual Community’, starts this dialogue by defining the complex meaning encompassed in another expression that lends its name to one of his books: “Smart Mobs”. He goes on to explain why the terms ‘artificial intelligence’ (AI) and ‘intelligent machines’ are being used wrongly, and describes how collective intelligences emerge from ‘smart mobs’. Later he reflects on why radio has not killed off movies, movies haven’t put an end to theatre, television will not kill off movies, and the Internet will not be the end of television; in other words, new media do not ‘do away with’ any of their predecessors. He then argues why poetry and business are not mutually exclusive, before finishing with an explanation of why there are more people, in more places, who are able to do things they never used do with personal computers, and they do them almost exclusively with a smartphone with a ubiquitous connection (anywhere, anytime) to the Internet.

In this dialogue, the philosopher of science and mathematician Javier Echeverria, begins by explaining how Leibniz created the first modern binary system, in which ‘1 and 0’ is capable of expressing everything, - something that marked the beginning of all modern computing and the subsequent digital revolution -, and why there would be no Internet without this language. He then argues why everything that is intelligible cannot be digitized. After, he explains why digitization is part of the invention of writing, how it transforms the world and might imply a great evolutionary step forward. He then rationalizes why we should speak of “intelligences”, in the plural, rather than just one intelligence and why, for him, intelligence is a question of degree. Later in the dialogue, he reflects on collective and “biosocial” intelligence, as well as explaining his vision of the Internet as Plato’s Cave, why he thinks metaverses are possible, and why he believes in the possibility that the universe is a huge hologram. Finally, he describes how our brains are starting to become bionic (“techno-brains”), thus enabling control technologies, and why this digital revolution poses a great challenge for the humanities

This chapter considers purely epistemic conceptions of deliberative democracy. For advocates of this approach the value of democratic procedures is a function of the quality of their outcomes. They also assume that the quality of outcomes is a function of the quality of the knowledge generated by the best decision makers. On this basis, epistocrats recommend that citizens blindly defer to the political decisions of experts (be it political elites or a representative sample of the population) to reach better political outcomes. This approach misses the democratic significance of public deliberation. By reducing the epistemic function of deliberation to the aim of figuring out the best policies, it disregards another crucial epistemic function of deliberation—ensuring that the policies in question can be justified to those who must comply with them and without whose cooperation the intended outcomes will not materialize. Thus, if we care about outcomes we must abandon the temptation of the “expertocratic shortcut” and focus on improving the processes of opinion- and will-formation in which citizens participate so that better outcomes can actually be achieved.

This chapter defends an epistemic argument for democracy, namely the argument that the rule of the many is better at aggregating knowledge and, in the version presented here, at producing better decisions than the rule of the few. This argument builds on the formal properties of two key democratic decision-making mechanisms of democracy, namely inclusive deliberation on equal grounds and majority rule with universal suffrage. Properly used in sequence and under the right conditions, these two mechanisms ensure that no information and viewpoint is ignored and maximize the cognitive diversity brought to bear on collective political problems and predictions. Building on existing formal results by Lu Hong and Scott Page, the chapter introduces the “Number Trumps Ability” theorem, which formalizes the intuition that many minds are smarter than just a few. Under the right conditions systems governed by democratic decision-procedures can be expected to deliver greater epistemic performance than less inclusive and egalitarian systems.

This chapter examines the main epistemic and political challenges we find today when we make claims about the future. From an epistemic perspective, this chapter asks whether the quality of future claims that are mostly linear (as in Humean epistemology) is more satisfying if future claims are the output of a collective debate or whether individual experts are more reliable. From a political perspective, this raises the question of the institutionalization of knowledge. As in oracles’ networks, indicators are today composed of other indexes that are embedded with our political and economic decisions. This chapter defines the future as a story that has to follow certain rules. When making historical counterfactual claims, we find multiple paths in different scenarios. There is no striking opposition between a closed past and an open future (David Lewis); both of them are enigmas to be unveiled, requiring specific tools.

Creativity can be viewed as the outcome of interacting mental and social mechanisms. In individual designers, thinking is multimodal, depending on sensory, motor, and emotional representations in addition to words. Creativity works in minds that are capable of taking previously unconnected representations and combining them into ones that turn out to be new, valuable, and surprising. Well-functioning groups such as design teams, scientific laboratories, and artist colonies can be more creative than individuals on their own, when the groups foster communication of semantic pointers among individuals. Apple’s production of novel and successful products such as the Apple II, Macintosh, iMac, iPod, iPhone, and iPad illustrates the mental and social mechanisms responsible for creative design.

In this dialogue, Tim O’Reilly begins by explaining why change is natural and good and how we have to be open to the future. Later he discusses how the logic that makes things work is related to science and not to a particular set of beliefs; to understanding what is efficient and why within this logic there is a hierarchy that is made up of a set of values. He goes on to explain how the Web 2.0 applications he formulated— for example, the social networks—use network effects by harnessing collective intelligence in such a way that the more people there are who use them, the better they become. After this, he describes how his analysis of the paradigm shift in open code is equivalent to that expressed by Thomas Kuhn in his work “The Structure of Scientific Revolutions”. Later on, O’Reilly reflects on the different possible kinds of Internet of the future before moving on to explain why the most innovative people go beyond the limits of “canonical knowledge” in their daily practice, and the way in which their artistic transgressions or discoveries make them part of the new canon.

Henry Jenkins, former professor of humanities, MIT, is one of the leading science authorities in the analysis of New Media. Today, he is Professor of Communication, Journalism, and Cinematic Arts at USC. In this dialogue, Jenkins explains how technology is transforming the traditional view of humanities. He outlines his vision of convergence culture in his book, Convergence Culture: Where Old and New Media Collide. He explains why he thinks the idea of copyright is an aberration. He goes on to relate the causes for conglomerates losing control of media flows and how to deal with this situation. He describes the new logic framework under which our current participatory culture is run. He defines himself in this dialogue as a critical utopian trying to demonstrate how to harness the great power that changes taking place in new media have on people. Emphasizing the ‘new social skills’, which bring about new forms of ethics, interactions, politics, types of economic activities and legal culture, in the clash between the new digital media and the old mass media.