Blog of Collective Intelligence (since 2003)

Collective intelligence has existed at least as long as humans have, because families, armies, countries, and companies have all–at least sometimes–acted collectively in ways that seem intelligent. But in the last decade or so a new kind of collective intelligence has emerged: groups of people and computers, connected by the Internet, collectively doing intelligent things. In order to understand the possibilities and constraints of these new kinds of intelligence, a new interdisciplinary field is emerging. This book will introduce readers to many disciplinary perspectives on behavior that is both collective and intelligent. By collective, we mean groups of individual actors, including, for example, people, computational agents, and organizations. By intelligent, we mean that the collective behavior of the group exhibits characteristics such as, for example, perception, learning, judgment, or problem solving. The book is under contract with MIT Press, and we are making early draft chapters available here, in part, to solicit comments from a wide range of people via the Web.

Source: The Collective Intelligence Handbook – An Open Experiment | Learning Change

How can technology that we are able to build with today’s tools help us to solve the big problems of individuals, organizations, and the world at large? More specifically: How can we use the internet in the best way to improve our collective problem-solving capabilities? Questions like these don’t seem to be asked very often, perhaps because people usually focus on specific problems, rather than general problem-solving in its own right. Today, a vast plethora of different websites, online platforms, and apps exists. Currently, the web is dominated by what can be called web 2.0 platforms, which facilitate social interactions and collaborative co-creation. Can these platforms help us to use some kind of global Collective Intelligence (CI) that is actually good at solving difficult problems? The answer is probably yes. Nevertheless, there doesn’t seem to be one single absolutely prominent platform that is really dedicated to solving serious real-world problems by using CI. Again, this may come from people not seeing themselves as problem-solvers, or not associating the internet with solving big problems – as opposed to solving “minor” problems like boredom.

Source: Solving Problems With Collective Intelligence – Towards an Internet of Thinkers? | Learning Change

Cognitive and psychological research provides useful theoretical perspectives for understanding what is happening inside the mind of an individual in tasks such as memory recall, judgment and decision making, and problem solving – including meta-cognitive tasks, when an individual is reflecting on their own or other people’s performance. Understanding these processes within individuals can help us understand under what conditions collective intelligence might form for a group and how we might optimize that group’s collective performance. Each of these components alone, or in concert, can be understood to form the basic building blocks of group collective intelligence. In this chapter, we will review the cognitive and psychological research related to collective intelligence. We will begin by exploring how cognitive biases can affect collective behavior, both in individuals and in groups. Next, we will discuss the issue of expertise, and discuss how more knowledgeable individuals may behave differently, and how they can be identified. We will also review some recent research on consensus-based models and meta-cognitive models such as the Bayesian truth serum that identify knowledgeable individuals in the absence of any ground truth. We will then look at how information sharing between individuals affects the collective performance, and review a number of studies that manipulate how that information is shared. Finally, we will look at collective intelligence within a single mind.

Source: Cognition and Collective Intelligence | Learning Change

An interview with French philosopher Pierre Lévy on why Elon Musk is wrong about AI

What if computers could take the words we type on the internet and convert them into a language that describes what they actually mean? Analyzing data pulled from social media would reveal insights into the deeper questions about our real motives and feelings, instead of mere statistics.

Pierre Lévy, a French philosopher who’s been writing about cyberspace since the 1990s and who is the Canada research chair in collective intelligence at the University of Ottawa, is working on software that can do just this. He’s done the math andannotated the entire French dictionary with a language—or, as he calls it, a hyper-language, since it describes words that already form a language of their own—that he calls IEML, or the Information Economy MetaLanguage. All that’s left is to do the actual coding to turn it into an automatic system.

Source: How the Internet’s Collective Human Intelligence Could Outsmart AI | Motherboard

“Apple has quickly caught on to the power of collective intelligence to solve our most pressing societal problems. And the company has productized this in the form of a new global platform to use sensors within their 700 million device network — a platform to help diagnose and record treatments for the world to learn from. This same network could be used for reporting potholes and other city issues in the future.”

Source: Government Technology, March 9, 2015