A new field of collective intelligence has emerged in the last few years, prompted by a wave of digital technologies that make it possible for organizations and societies to think at large scale. This “bigger mind”human and machine capabilities working togetherhas the potential to solve the great challenges of our time. So why do smart technologies not automatically lead to smart results? Gathering insights from diverse fields, including philosophy, computer science, and biology, Big Mind reveals how collective intelligence can guide corporations, governments, universities, and societies to make the most of human brains and digital technologies.
Geoff Mulgan explores how collective intelligence has to be consciously organized and orchestrated in order to harness its powers. He looks at recent experiments mobilizing millions of people to solve problems, and at groundbreaking technology like Google Maps and Dove satellites. He also considers why organizations full of smart people and machines can make foolish mistakesfrom investment banks losing billions to intelligence agencies misjudging geopolitical eventsand shows how to avoid them.
Highlighting differences between environments that stimulate intelligence and those that blunt it, Mulgan shows how human and machine intelligence could solve challenges in business, climate change, democracy, and public health. But for that to happen we’ll need radically new professions, institutions, and ways of thinking.
Informed by the latest work on data, web platforms, and artificial intelligence, Big Mind shows how collective intelligence could help us survive and thrive.
|Publisher:||Princeton University Press|
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About the Author
Geoff Mulgan is chief executive of Nesta, the UK’s National Endowment for Science, Technology and the Arts, and a senior visiting scholar at Harvard University’s Ash Center. He was the founder of the think tank Demos and director of the Prime Minister’s Strategy Unit and head of policy under Tony Blair. His books include The Locust and the Bee (Princeton) and Good and Bad Power (Penguin).
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The Paradox of a Smart World
We live surrounded by new ways of thinking, understanding, and measuring that simultaneously point to a new step in human evolution and an evolution beyond humans.
Some of the new ways of thinking involve data — mapping, matching, and searching for patterns far beyond the capacity of the human eye or ear. Some involve analysis — supercomputers able to model the weather, play chess, or diagnose diseases (for example, using the technologies of firms like Google's DeepMind or IBM's Watson). Some pull us ever further into what the novelist William Gibson described as the "consensual hallucination" of cyberspace.
These all show promise. But there is a striking imbalance between the smartness of the tools we have around us and the more limited smartness of the results. The Internet, World Wide Web, and Internet of things are major steps forward in the orchestration of information and knowledge.
Yet it doesn't often feel as if the world is all that clever. Technologies can dumb down as well as smarten up. Many institutions and systems act much more stupidly than the people within them, including many that have access to the most sophisticated technologies. Martin Luther King Jr. spoke of "guided missiles but misguided men," and institutions packed with individual intelligence can often display collective stupidity or the distorted worldview of "idiots savants" in machine form. New technologies bring with them new catastrophes partly because they so frequently outstrip our wisdom (no one has found a way to create code without also creating bugs, and as the French philosopher Paul Virilio put it, the aircraft inevitably produces the air disaster).
In the 1980s, the economist Robert Solow commented, "You can see the computer age everywhere but in the productivity statistics." Today we might say again that data and intelligence are everywhere — except in the productivity statistics, and in many of the things that matter most. The financial crash of the late 2000s was a particularly striking example. Financial institutions that had spent vast sums on information technologies failed to understand what was happening to them, or understood the data but not what lay behind the data, and so brought the world to the brink of economic disaster. In the 1960s and 1970s, the Soviet government had at its disposal brilliant minds and computers, but couldn't think its way out of stagnation. During the same period, the US military had more computing power at its disposition than any other organization in history, but failed to understand the true dynamics of the war it was fighting in Vietnam. A generation later the same happened in Iraq, when a war was fought based on a profound error of intelligence launched by the US and UK governments with more invested than any other countries in the most advanced intelligence tools imaginable. Many other examples confirm that having smart tools does not automatically lead to more intelligent results.
Health is perhaps the most striking example of the paradoxical combination of smart elements and often-stupid results. We now benefit from vastly more access to information on diseases, diagnoses, and treatments on the Internet. There are global databases of which treatments work; detailed guidance for doctors on symptoms, diagnoses, and prescriptions; and colossal funds devoted to pushing the frontiers of cancer, surgery, or pharmaceuticals.
But this is far from a golden age of healthy activity or intelligence about health. The information available through networks is frequently misleading (according to some research, more so than face-to-face advice). There are well over 150,000 health apps, yet only a tiny fraction can point to any evidence that they improve their users' health. The dominant media propagate half-truths and sometimes even lies as well as useful truths. And millions of people make choices every day that clearly threaten their own health. The world's health systems are in many ways pioneers of collective intelligence, as I will show later, but much doesn't work well. It's estimated that some 30 to 50 percent of antibiotic prescriptions are unnecessary, 25 percent of medicines in circulation are counterfeit, somewhere between 10 and 20 percent of diagnoses are incorrect, and each year 250,000 die in the United States alone because of medical error (the third leading cause of death there). In short, the world has made great strides in improving health and has accumulated an extraordinary amount of knowledge about it, yet still has a long way to go in orchestrating that knowledge to best effect.
Similar patterns can be found in many fields, from politics and business to personal life: unprecedented access to data, information, and opinions, but less obvious progress in using this information to guide better decisions. We benefit from a cornucopia of goods unimaginable to past generations, yet still too often spend money we haven't earned to buy things we don't need to impress people we don't like.
We have extraordinary intelligence in pockets, for specific, defined tasks. Yet there has been glacial, if any, progress in handling more complex, interconnected problems, and paradoxically the excitement surrounding new capacities to sense, process, or analyze may distract attention from the more fundamental challenges.
In later chapters, I address what true collective intelligence would look like in some of the most important fields. How could democracy be organized differently if it wanted to make the most of the ideas, expertise, and needs of citizens? Various experiments around the world suggest what the answers might be, but they baffle most of the professionals brought up in traditional politics. How could universities become better at creating, orchestrating, and sharing knowledge of all kinds? There are seeds of different approaches to be found, but also extraordinary inertia in the traditional models of three-year degrees, faculty hierarchies, lecture halls, and course notes. Or again, how could a city administration, or national government, think more successfully about solving problems like traffic congestion, housing shortages, or crime, amplifying the capabilities of its people rather than dumbing them down?
We can sketch plausible and achievable options that would greatly improve these institutions. In every case, however, the current reality falls far short of what's possible, and sometimes tools that could amplify intelligence turn out to have the opposite effect. Marcel Proust wrote that "nine tenths of the ills from which intelligent people suffer spring from their intellect." The same may be true of collective intelligence.
The Nature of Collective Intelligence in Theory and Practice
The word intelligence has a complex history. In medieval times, the intellect was understood as an aspect of our souls, with each individual intellect linked into the divine intellect of the cosmos and God. Since then, understandings of intelligence have reflected the dominant technologies of the era. René Descartes used hydraulics as a metaphor for the brain and believed that animating fluids connected the brain to limbs. Sigmund Freud in the age of steam power saw the mind in terms of pressure and release. The age of radio and electrics gave us the metaphors of "crossed wires" and being "on the same wavelength," while in the age of computers the metaphors turned to processing and algorithmic thinking, and the brain as computer.
There are many definitions of intelligence. But the roots of the word point in a direction that is rather different from these metaphors. Intelligence derives from the Latin word inter, meaning "between," combined with the word legere, meaning "choose." This makes intelligence not just a matter of extraordinary memory or processing speeds. Instead it refers to our ability to use our brains to know which path to take, who to trust, and what to do or not do. It comes close in this sense to what we mean by freedom. The phrase collective intelligence links this with a related idea. The word collective derives from colligere. This joins col, "together," and once again, legere, "choose." The collective is who we choose to be with, who we trust to share our lives with. So collective intelligence is in two senses a concept about choice: who we choose to be with and how we choose to act.
The phrase has been used in recent years primarily to refer to groups that combine together online. But it should more logically be used to describe any kind of large-scale intelligence that involves collectives choosing to be, think, and act together. That makes it an ethical as well as technical term, which also ties into our sense of conscience — a term that is now usually understood as individual, but is rooted in the combination of con (with) and scire (to know).
We choose in a landscape of possibilities and probabilities. In every aspect of our lives we look out into a future of possible events, which we can guess or estimate, though never know for certain. Many of the tools I describe through the course of this book help us make sense of what lies ahead, predicting, adapting, and responding. We observe, analyze, model, remember, and try to learn. Although mistakes are unavoidable, repeated mistakes are unnecessary. But we also learn that in every situation, there are possibilities far beyond what data or knowledge can tell us — possibilities that thanks to imaginative intelligence, we can sometimes glimpse.
One of the first historical accounts of collective intelligence is Thucydides's description of how an army went about planning the assault on a besieged town. "They first made ladders equal in length to the height of the enemy's wall, which they calculated by the help of the layers of bricks on the side facing the town, at a place where the wall had accidentally not been plastered. A great many counted at once, and, although some might make mistakes, the calculation would be more often right than wrong; for they repeated the process again and again, and, the distance not being great, they could see the wall distinctly enough for their purpose. In this manner they ascertained the proper length of the ladders, taking as a measure the thickness of the bricks."
Understanding how we work together — the collective part of collective intelligence — has been a central concern of social science for several centuries. Some mechanisms allow individual choices to be aggregated in a socially useful way without requiring any conscious collaboration or shared identity. This is the logic of the invisible hand of the market and some of the recent experiments with digital collective intelligence like Wikipedia. In other cases (such as communes, friends on vacation, or work teams), there is the conscious mutual coordination of people with relatively equal power, which usually involves a lot of conversation and negotiation. Loosely networked organizations such as Alcoholics Anonymous are similar in nature. In others (for instance, big corporations like Google or Samsung, ancient Greek armies, or modern global NGOs), hierarchy organizes cooperation, with a division of labor between different tiers of decision making.
Each of these produces particular kinds of collective intelligence. Each feels radically different, and works well for some tasks and not others. In some cases there is a central blueprint, command center, or plan — someone who can see how the pieces fit together and may end up as a new building, a business plan, or initiative. In other cases the intelligence is wholly distributed and no one can see the big picture in advance. But in most cases the individual doesn't need to know much about the system they're part of: they can be competent without comprehension.
The detailed study of how groups work shows that we're bound together not just by interests and habit but also by meanings and stories. But the very properties that help a group cohere can also impede intelligence. These include shared assumptions that don't hold true, a shared willingness to ignore uncomfortable facts, groupthink, group feel, and mutual affirmation rather than criticism. Shared thought includes not only knowledge but also delusions, illusions, fantasies, the hunger for confirmation of what we already believe, and the distorting pull of power that bends facts and frames to serve itself. The Central Intelligence Agency informing President George H. W. Bush that the Berlin Wall wouldn't fall, just as the news was showing it doing just that; investment banks in the late 2000s piling into subprime mortgages when all the indicators showed that they were worthless; Joseph Stalin and his team ignoring the nearly ninety separate, credible intelligence warnings that Germany was about to invade in 1941 — all are examples of how easily organizations can be trapped by their frames of thinking.
We succumb all too readily to illusions of control and optimism bias, and when in a crowd can suspend our sense of moral responsibility or choose riskier options we would never go for alone. And we like to have our judgments confirmed, behaving all too often like the Texas sharpshooter who sprays the walls with bullets and then draws the target around where they hit. These are just a few reasons why collective intelligence is so frequently more like collective stupidity.
They show why most groups face a trade-off between how collective they are and how intelligently they can behave. The more they bond, the less they see the world as it really is. Yet the most successful organizations and teams learn how to combine the two — with sufficient suspension of ego and sufficient trust to combine rigorous honesty with mutual commitment.
General and Specific
How we think can then be imagined as running in a continuum from general, abstract intelligence to intelligence that is relevant to specific places, people, and times. At one extreme there are the general laws of physics or the somewhat less general laws of biology. There are abstracted data, standardized algorithms, and mass-produced products. Much of modernity has been built on an explosion of this kind of context-free intelligence. At the other end of the spectrum there is rooted intelligence — intelligence that understands the nuances of particular people, cultures, histories, or meanings, and loses salience when it's removed from them.
The first kinds of intelligence — abstract, standardized, and even universal — are well suited to computers, global markets, and forms of collective intelligence that are more about aggregation than integration. By contrast, the ones at the other extreme — like knowing how to change someone's life or regenerate a town — entangle multiple dimensions, and require much more conscious iteration and integration along with sensitivity to context.
Collective Intelligence and Conflict
The simplest way to judge individual intelligence is by how well it achieves goals and generates new ones. But this is bound to be more complex for any large group, which is likely to have many different goals and often-conflicting interests.
This is obviously true in the economy, since information is usually hoarded and traded rather than shared. Societies try to design arrangements (including patents and copyrights) that reward people for both creating and sharing useful information, though, as I will show in chapter 17, the rise of economies based on information and knowledge has shifted the balance between private ownership and the commons, and led to an evident underproduction of informational commons. Even if this problem were fixed, though, there would still be unavoidable tensions thanks to conflicting interests.
Many collective actions that appear stupid may be intelligent for some of the people involved, such as a country setting out on a war it is unlikely to win (to shore up support for an insecure dictator), a bank taking apparently mad risks (which offer huge personal gains to a few at the top), or a religious community holding on to beliefs in the face of overwhelming contrary evidence (as the price for holding the community together).
Many traditions of social science have grappled with these issues: How can the principal (for instance, the public) ensure that their agent (say, government) really does act in their interests?
Seeing these issues through the lens of collective intelligence opens up the possibility that shared observation, reasoning, memory, and judgment will all increase the pressure to find mutually advantageous solutions. Think, for example, of a country coming out of civil war and strife. The ones that have done well intensify what we will see later as the hallmarks of successful collective intelligence: bringing facts and feelings to the surface in ways that are detached from interests; jointly deliberating about what is to be done and opening up alternative scenarios; discussing openly who is to be punished and who deserves restitution; and addressing memory openly through truth and reconciliation commissions.
Excerpted from "Big Mind"
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Table of Contents
Introduction Collective Intelligence as a Grand Challenge 1
What Is Collective Intelligence? 9
1 The Paradox of a Smart World 11
2 The Nature of Collective Intelligence in Theory and Practice 14
Part II Making Sense of Collective Intelligence as Choice 33
3 The Functional Elements of Collective Intelligence 35
4 The Infrastructures That Support Collective Intelligence 48
5 The Organizing Principles of Collective Intelligence 60
6 Learning Loops 70
7 Cognitive Economics and Triggered Hierarchies 76
8 The Autonomy of Intelligence 90
9 The Collective in Collective Intelligence 99
10 Self-Suspicion and Fighting the Enemies of Collective Intelligence 119
Part III Collective Intelligence in Everyday Life 129
11 Mind-Enhancing Meetings and Environments 131
12 Problem Solving: How Cities and Governments Think 145
13 Visible and Invisible Hands: Economies and Firms as Collective Intelligence 161
14 The University as Collective Intelligence 174
15 Democratic Assembly 181
16 How Does a Society Think and Create as a System? 193
17 The Rise of Knowledge Commons: It’s for Everyone 200
Part IV Collective Intelligence as Expanded Possibility 215
18 Collective Wisdom and Progress in Consciousness 217
Afterword: The Past and Future of Collective
Intelligence as a Discipline 229
Summary of the Argument 237