Our Society Cannot Long Continue on its Old Premises

In some small degree, we feel bored and uneasy with the orderly chrome and porcelain vacuum of our lives. In this contemporary life the book of experience is filled with blank and mysterious pages. We die from our machines, our own poisons, our own weapons, our own despair. We call such Worlds Complex Adaptive Systems. In Complex Adaptive Systems there are often many participants, perhaps even many kinds of participants. They interact in intricate ways that continually reshape their collective future. New ways of doing things—even new kinds of participants—may arise, and old ways—or old participants—many vanish. Such systems challenge understanding as well as prediction. These difficulties are familiar to anyone who has seen small changes unleash major consequences. Conversely, they are familiar to anyone who has been surprised when large changes in policies or tools produce no long-run change in people’s behaviour. When managers and policy makers hear about complexity research, they often ask, “How can I control complexity?” What they usually mean is, “How can I eliminate it?” However, complexity, as we shall see, stems from fundamental causes that cannot always be eliminated. Although complexity is often perceived as a liability, it can actually be an asset. However, there is no doubt that complexity can be harnessed. So, rather than seeking to eliminate complexity, we shall explore how the dynamism of a Complex Adaptive System can be used for productive ends. #RandolphHarris 1 of 22

In a World of mutually adaptive players, even though prediction may be difficult, there is quite a bit that you can do. Complexity itself allows for techniques that promote effective adaptation. When there are many participants, numerous interactions, much trial-and-error learning, and abundant attempts to imitate each other’s success, there will also be rich opportunities to harness the resulting complexity. And there will be thing to avoid. To take a simple example: Even though one action seems best, it usually pays to maintain variety among the actions you take so that you can continue to learn and adapt. Managers and policy makers must learn to harness complexity. There are three main foundations that we will deal with. These include biology, computer science, and social design. From evolutionary biology come the insights of Darwinian evolution, particularly that extraordinary adaptations can come about through the selection and reproduction of successful individuals in populations. Even though moths in England could not understand or predict that the Industrial Revolution would turn white-barked trees into soot-covered trees, it did not take very long for selection by predatory birds to transform the population of moths near a factory from white to black. From computer science come insights about how systems with many artificial agents can be designed to work together and even adapt over time to each other and to their ever-changing environment. #RandolphHarris 2 of 22

Two area of computer science have been especially important to us. First, there is the field of evolutionary computation, which has fostered an engineering approach to adaptation. With an engineering approach, one asks how system can be designed to become more effective over time. By making evolution and adaptation an engineering problem, evolution computation has shed light on how complex systems can be adaptive. Second, there is the rapid growth of distributed and network-mediated computing (including the Internet), which has led computer science into deeper analyses of just what it takes to make systems of many agents work together and grow. From social design come insights into people and their activities in political, economic, and social systems. Entire disciplines—such as political science, economies, sociology, psychology, and history—have been devoted to understanding human beings and the settings they build and live in. Among the approaches that have concentrated on social design are organization theory and game theory. Organization theory provides insight into how institutional structure matters. Game theory provides insight into how people can choose strategies to maximize their payoffs in the presence of other people who are doing the same. #RandolphHarris 3 of 22

While the foundations of this work come from evolutionary biology, computer science, and social design, our analysis differs from all three of these in important ways. Unlike evolutionary biology, we are primarily interested in the shaping of evolutionary processes rather than just observation and explanation, in intelligent individuals with language and culture, rather than plants and animals that rely primarily on their genetic heritage, and in different measures of success rather than taking the ability to have offspring as the sole measures of success. Unlike computer science, we are primarily interested in systems composed of people or organizations rather than pieces of software, in systems with long and rich histories rather than systems that have little or no history, and in systems in which the costs of trials needed for adaptation are measure in terms of efforts and even lives of people rather than in cycles of computer time. Unlike some approaches to social design, we are primarily interested in problems in which the preferences and even the identities of the participants can evolve over time, rather than situations in which the players and their preferences are fixed, as they are in game theory, and in problems in which decentralization is both promising and problematic, rather than situations in which decentralization is seen as practically a panacea, as in some forms of neoclassical economics. #RandolphHarris 4 of 22

Strategic thinking is the art of outdoing an adversary, knowing that the adversary is trying to do the same to you. All of us must practice strategic thinking at work as well as at home. Businessmen and women and corporations must use good competitive strategies to survive. Politicians have to devise campaign strategies to get elevated, and legislative strategies for the players to execute on the field. Parents trying to elicit good behaviour from children must become amateur strategists (the children are the pros). For forty years, superpowers’ nuclear strategies have governed the survival of the human race. Good strategic thinking in such numerous diverse contexts remains an art. However, its foundations consist of some simple basic principles—an emerging science of strategy. A variety of backgrounds and occupations can become better strategists if they know these principles. The science of thinking is called game theory, as mentioned before. However, like all sciences, it has become shrouded in jargon and mathematics. How should people behave in society? All of us are strategists, whether we like it or not. It is better to be a good strategist than a bad one. Work, even social life, is a constant stream of decisions. What career to follow, how to manage a business, whom to marry, how to bring up children, whether to run for president, are just some examples of such fateful choices. The common element in these situations is that you do not act in a vacuum. #RandolphHarris 5 of 22

Instead, you are surrounded by active decision-makers whose choices interact with yours. This interaction has an important effect on your thinking and actions. To illustrate the point, think of the difference between the decisions of a lumberjack and those of a general. When the lumberjack decides how to chop wood, he does not expect the wood to fight back; his environment is neutral. However, when the general tries to cut down the enemy’s army, one must anticipate and overcome resistance to one’s plans. Like the general, one must recognize that one’s business rivals, prospective spouse, and even your children are intelligent and purposive people. Their aims often conflict with yours, but they include some potential allies. Your own choices allow for the conflict, and utilize the cooperation. Such interactive decisions are called strategic, and the plan of action appropriate to them is called strategy. It is important to think strategically, and then translate these thoughts into action. The branch of social science that studies strategic decision-making is called game theory. The games in this theory range from chess to child-rearing, from tennis to takeovers, and from advertising to arms control. Many continentals think life is a game, the English think cricket is a game. We think both are right. Playing these games requires many different kinds of skills. Basic skills, such as shooting ability in basketball, knowledge of precedents in law, or a blank face in poker, are one kind; strategic thinking is another. #RandolphhHarris 6 of 22

Strategic thinking starts with your basic skills, and considers how best to use them. Knowing the law, you must decide the strategy for defending your client. Knowing how well your football team can pass or run, and how well the other team can defend against each choice, your decision as the coach is whether to pass or to run. Sometimes, as in the case of superpowers contemplating an adventure that risks nuclear war, strategic thinking also means knowing when not to play. We develop the ideas and principles of strategic thinking; to apply them to a specific situation you face and to find the right choice there, you will have to so some work. This is because the specifics of each situation are likely to differ in some significant aspects, and any general prescriptions for action we might give could be misleading. In each situation, you will have to pull together principles of good strategy we have discussed, and also other principles from other considerations. You must combine them and, where they conflict with each other, evaluate the relative strengths of the different arguments. We do not promise to solve every question you might have. The science of the game theory is far from being complete, and in some ways strategic thinking remains an art. We often have to translate ideas into action. Strategic issues arise in a variety of decisions. Some broad classes of strategic situations—brinkmanship, voting, incentives, and bargaining—where one can see the principles in action. #RandolphHarris 7 of 22

The examples range from the familiar, trivial, or amusing—usually drawn from literature, sports, or movies—to the frightening—nuclear confrontation. The former are merely a nice and palatable vehicle for the game-theoretic ideas. As to the subject of nuclear war too horrible to permit rational analysis. However, as the cold war winds down and the World is generally perceived to be a safer place, we hope that the game-theoretic aspects of the arms race and the Cuban missile crisis can be examined for their strategic logic in some detachment from their emotional content. Some cases we examine are open-ended; but that is also a future of life. At times there is no clearly correct solution, only imperfect ways to cope with the problem. We are often asked how “complexity” differs from “chaos.” The simple answer is that chaos deals with situations such as turbulence that rapidly become highly disordered and unmanageable. On the other hand, complexity deals with systems composed of many interacting agents. While complex systems may be hard to predict, they may also have a good deal of structure and permit improvement by thoughtful intervention. We view the process of biological change as wonderful example in the larger set of Complex Adaptive Systems. However, they have special kinds of agents, particular sorts of strategies, distinctive patterns of interaction, and their own special process of selection. #RandolphHarris 8 of 22

The patterns one sees in biology are not always found in other Complex Adaptive Systems. Copying a strategy for stock trading (such as a computer algorithm) involves only digital information and so nearly costless compared with producing a new organism that contained a copied gene. Evaluating a business strategy (say, the introduction of a new product) can be enormously expensive compared with making a random variation of a fruit fly. Variation, interaction, and selection are at work in the population of business strategies, but detailed mechanisms are often distinctly unbiological. To harness complexity effectively, many kinds of Complex Adaptive Systems must be considered. We choose to harness because it conveys a perspective that is not explanatory but active—seeking to improve but without being fully able to control. The Complex Adaptive System approach is a way of looking at the World. It provides a set of concepts, a set of questions, and a set of design issues. By itself, it is not a falsifiable theory. Such a theory would have to specify the operational meaning of the key concepts and mechanisms in a particular domain. For example, to apply the Complex Adaptive Systems approach to economic markets, one would have to specify who the economic actors are, what they can see and do, how they generate variety in their behaviour, how they interact with each other, and how the actors and their strategies are selected for retention, amplification, or extinction. #RandolphHarris 9 of 22

Complexity research can be made relevant to problems social design. It offers a way to those who want to improve the World as well as marvel at it. The hard reality is that the World in which we must act is often beyond our understanding. Each action we take is partly an instrumental step and partly a learning experience. Adaptation can be regarded as an engineering problem. The complexity of the World is real. We do not know how to make it disappear. To create a positive host culture for a flexible knowledge-intensive economy, Japan, for example, will also have to reexamine the social rules that contribute to inflexibility—including the way decisions are made. Much has been written about Japan’s emphasis on group decision-making, especially about the fact that once a consensus decision has been reached, its implementation is rapid because all relevant parties have by then bought into the goal and understand what needs to be done. The reverse side of this, however, is the length of time needed to reach a decision, and the difficulty of changing quickly in response to new information or conditions. We saw this at work once during a television shoot with a crew of Japanese, Canadians and Americans. The Japanese team was extremely professional and, during the many months of working together, formed warm relations with the westerners. Each side had an opportunity to observe and learn from the other. #RandolphHarris 10 of 22

Typically, the night before shooting at a new location, the Japanese team would stay up late debating every aspect of the task—who would do what, exactly when and where. By morning the team was fully prepared. By contrast, the Americans and Canadians were more likely to spend the evening hours chatting, downing a beverage or two and going to be. However, Wally Longul, the Canadian director, would get up very early and go, by himself, to look the location over again. One morning her discovered a nearby location that he believed would provide a better background for the shoot. When he suggested to the Japanese that they switch to the alternate location, he faced a wall of stubborn refusal—even though none of them had seen the place he proposed. The reason for this seemingly blind resistance was clear. The Japanese had invested a great deal of time and energy in arriving at their decision in the first place. Switching to a better location—which, under the circumstances, might have been a better decision—was ruled out. Yet in today’s increasingly accelerated and complex economy and society, the ability to change plans rapidly, to arrive at decision quickly, is a vital survival mechanism. We can expect to see a decline in collective decision-making in Japan under the pressure of high-speed change and the rise of a new generation that is increasingly individuated. #RandolphHarris 11 of 22

Some companies attempt to impose order on information by designing computerized management information systems (MIS). Some of these, it turns out, are intended to buttress the old system by employing computer and communication links merely to expand the cubbyholes and the capacity of the communication channels. Others are truly revolutionary in intent. They seek to crush the cubby-hole-and-channels system and replace it with free-flow information. To appreciate the full significance of this development, and the power shift it implies, it helps to note the quite remarkable (though largely unremarked) parallels between bureaucracies and our early computers. The first big mainframes ministered to by the data priests supported the existing bureaucracies in business and government. This accounts for the initial fear and loathing they aroused in the public. Ordinary people sensed that these monster machines were yet another tool of power that might be used against them. The very data bases they held resembled the bureaucracies they served. Early business computers were used chiefly for routine purposes like keeping thousands of payroll records. John Doe’s record was made up of what the computer experts called “field.” Thus his name might be the first field, his address the second, his job title the third, his base salary the fourth, and so on. Everyone’s address went into his or her second “field.” Everyone’s base salary figure went into one’s fourth field. In this way, all information entered into the payroll files went to pre-specified locations in the data base—just as information in a bureaucracy was addressed to pre-specified departments or cubbyholes. #RandolphHarris 12 of 22

Moreover, the first computerized data systems were largely hierarchical, again like the bureaucracies they were designed for. Information was stored hierarchically in memory, and the actual hardware itself concentrated computer power at the top of the company pyramid. Brains resided in the mainframe, while at the bottom the machines were unintelligent. The jargon referred to them appropriately as “dumb terminals.” The microcomputer revolutionized all this. For the first time, it placed intelligence on thousands of desk tops, distributing data bases and processing power. However, while it shook things up, it did not seriously threaten bureaucratic organization. The reason for this was that even though there were now many computerized data banks instead of one giant central bank, the knowledge stored in them was still crammed into rigid predesigned cubbyholes. Today, however, we are at the edge of a further revolution in how information is organized in computerized data bases. So-called “relational” data bases now permit users to add and subtract fields and to interrelate them in new ways. Taking all dimensions of change into account, we realized upfront that hierarchical relationships between the data would be a disaster. The new data bases had to allow new relationships to emerge. #RandolphHarris 13 of 22

However, such systems today are still so cumbersome they cannot be easily run on microcomputers. The next step has come with the introduction recently of “hyper-media” data bases capable of storing not merely text but also graphics, music, speech, and other sounds. More important, hyper-media combine data bases and programs to give the user far greater flexibility than earlier data base systems. Even in the relational systems, data could be combined in only a few pre-specified ways. Hyper-media vastly multiplies the way in which information from different fields and records can be combined, recombined, and manipulated. Information in the original data bases was structured like a tree, meaning that to go from a leaf on one branch to a leaf on another, you had to go back to the trunk. “Hyper” systems are like a web, making it possible to move easily from once piece of information to another contextually. The ultimate goal of the hyper-media pioneers—admittedly still a distant grail—is systems in which information can be assembled, configured, and presented in an almost infinite number of ways. The goal is “free-form” and “free-flow” information. A striking example of the genre (called “HyperCard” and popularized by Apple) was first demonstrated at a Boston computer show by its author, Bill Atkinson. What he showed stunned the audience at the time. #RandolphHarris 14 of 22

First to appear on his screen was a picture of a cowboy. When Atkinson indicated the cowboy’s hat, other hats began to appear on the screen, one of which was the hat on a baseball player. When Atkinson indicted the player’s hat, other images associated with baseball began to appear, one after another, on the screen. He was able to extract information from the data base and detect patterns in it, in highly varied ways. This was so different from earlier data base systems that it gave the illusion that the computer was free-associating—much like a person. By crossing conventional categories, reaching across different collections of data, hyper-media makes it possible for, say, a designer creating a new product to let one’s mind weave through the stored knowledge naturally and imaginatively. One might instantly shift, for instance, from technical data to pictures of earlier products that preceded in the market…to chemical abstracts…to biographies of famous scientist…to video clips of the marketing team discussing the product…to transportation tariff tables…to slips of relevant focus groups…to spot prices for oil…or lists of the components or ingredients the new product will need…plus the latest study of political risk in countries from which its raw materials will have to come. In addition to vastly increasing the sheer quantity of accessible knowledge, hyper-media also permits a “layering” of information, so that a user can first access the most or least abstract form of it, and move by stages up or down the abstraction ladder. Or, alternatively, generate innovative ideas by creating novel juxtapositions of data. #RandolphHarris 15 of 22

Conventional data bases are good for getting information when you know exactly what you want. Hyper systems are good for searching when you are not certain. Ford Motor Company is developing a “Service Bay Diagnostic System” for mechanics, so that they can search and browse for answers when they are not sure what is wrong with your car. The U.S. Environmental Protection Agency makes available a “hyper-text” data base to help companies sort through and interrelate complex regulations governing 2 million underground storage tanks. Cornell University uses a hyper system for its second-year medical curriculum, permitting students to browse and search for patterns interactively. The University of Toledo has developed a hyper-text-based course in Spanish literature. We are still a little away from being able to throw different kinds of data or information into a single pot and then search it entirely free of a programmer’s preconceptions about what pieces are or are not related. Even in hyper systems the cross-connections a user can make are still dependent on previous programming. However, the direction of research is clear. We are inching toward free (or at least freer) forms of information storage and manipulation. Bureaucracies, with all their cubbyholes and channels prespecified, suppress spontaneous discovery and innovation. In contrast, the new systems, by permitting intuitive as well as systematic searching, open the door to precisely the serendipity needed for innovation. #RandolphHarris 16 of 22

The effect is a dazzling new freedom. The significant fact is that we are now moving toward powerful forms of knowledge processing that are profoundly antibureaucratic. Instead of a little bureaucracy inside a machine, as it were, where everything is sequential, hierarchical, and pre-designated, we move toward free-style, open information. And instead of a single mainframe or a few giant processors having this enormous capacity, companies now have thousands of personal computers (PCs), which before long will all have this capacity. This for of information storage and processing points toward a deep revolution in the way we think, analyze, synthesize, and express information, and a forward leap in organizational creativity. However, it also eventually means the breakup of the rigid little information monopolies that overspecialization created in the bureaucratic firm. And that means a painful shift of power away from the guardians of those specialized monopolies. Even this tells only a fraction of the tale. For to these truly revolutionary ways of storing and using knowledge, we must now add the nonhierarchical communication networks that crisscross companies, crash through departmental perimeters, and link users, not merely between the specialized departments but also up and down the hierarchy. A young employee at the very bottom the ladder can now communicate directly with top-level executives working on the same problem; and, significantly, the CEO at the touch of a button can access any employee down below and jointly call up images, edit a proposal together, study a blueprint, or analyze a spreadsheet—all without going through the middle managers. #RandolphHarris 17 of 22

It is surprising therefore that recent years have seen such savage reductions in the number of middle managers in industry? Just as the new forms of information storage strike a blow against specialization, the new forms of communication end-run the hierarchy. The two key sources of bureaucratic power—cubbyholes and channels—are both under attack. Making familiar products from improved materials will increase their safety, performance, and usefulness. It will also present the simplest engineering task. A greater challenge, though, will result from unfamiliar products made possible by new manufacturing methods. In talking about unfamiliar products, a hard-to-answer question arises: What will people want? Products are typically made because their recipients want them. In our discussion here, if we describe something that people will not want, then it probably will not get built, and if it does get built, it will soon disappear. (The exceptions—fraud, coercion, persistent mistakes—are important, but in other contexts.) To anchor our discussion, it makes sense to look not at totally new products, but instead at new features for old products, or new ways to provide old services. This approach will not cover more than a fraction of what is possible, but will start from something sensible and provide a springboard for the imagination. #RandolphHarris 18 of 22

As usual, we are describing possibilities, not making predictions. The possibilities focused on here arise from more complex applications of molecular manufacturing—nanotechnological products that contain nanomachines when they are finished. Earlier, we discussed strong materials. Now, we discuss some smart materials. The goal of making material and objects smart is not new: researchers are already struggling to build structures that can sense internal and environmental conditions and adapt themselves appropriately. There is even a Journal of Intelligent Material Systems and Structures. By using materials that can adapt their shapes, sometimes hooked up to sensors and computers, engineers are starting to make objects they call “smart.” These are the early ancestors of the smart materials that molecular manufacturing will make possible. Today, we are used to having machines with a few visible moving parts. In cars, the wheels go around, the windshield wipers go back and forth, the antenna may go up and down, the seat belts, mirrors, and steering wheel may be motor-driver. Electric motors are fairly small, fairly inexpensive, and fairly reliable, so they are fairly common. The result is machines that are fairly smart and flexible, in a clumsy, expensive way. In the Desert Rose scenario, we saw “tents” being assembled from trillions of submicroscopically small parts, including motors, computers, fibers, and struts. To the naked eye, materials made from these parts could seem as smooth and uniform as a piece of plastic, or as richly textured as wood or cloth—it is all a matter of the arrangement of the submicroscopic parts. #RandolphHarris 19 of 22

These motors and other parts cost less than a trillionth of a dollar apiece. They can be quite reliable, and good design can make systems work smoothly even if 10 percent of a trillion motors burn out. Likewise for motor controlling computers and the rest. The resulting machines can be very smart and flexible, compared to those of today, and inexpensive, too. When materials can be full of motors and controllers, whole chunks of materials can be made flexible and controllable. The applications should be broad. Now, when considering America, the development of this country is not a Machiavellian invention of capitalists, but rather a mechanism which all viable social systems must evolve spontaneously in order to protect themselves from instability. Many people believe that Marx was doing science, or Max Weber or Lewis Mumford or Bruno Bettelheim or Carl Jung or Margaret Mead or Arnold Toynbee. What these people were doing—and Stanley Milgram was doing—is documenting the behaviour and feelings of people as they confront problems posed by their culture. Their work is a form of storytelling. Science itself is, of course, a form of storytelling too, but its assumptions and procedures are so different from those of social research that it is extremely misleading to give the same name to each. In fact, the stories of social researcher are much closer in structure and purpose to what is called imaginative literature; that is to say, both a social researcher and a novelist give unique interpretations to a set of human events and support their interpretations with examples in various forms. Their interpretations cannot be proved or disproved but will draw their apparel from the power of their language, the depth of their explanations, the relevance of their examples, and the credibility of their themes. And all of this has, in both cases, an identifiable moral purpose. #RandolphHarris 20 of 22

The words “true” and “false” do not apply here in the sense that they are used in mathematics or science. For there is nothing universally and irrevocably true or false about these interpretations. There are no critical tests to confirm or falsify them. There are no natural laws from which they are derived. They are bound by time, by situation, and above all by the cultural prejudices of the researcher or writer. A novelist—for example, D.H. Lawrence—tells a story about the particulars of a woman’s life which involved pleasures of the flesh—Lady Chatterley—and from it we may learn things about the secrets of some people, and wonder if Lady Chatterley’s secrets are not more common than we had thought. Lawrence did not claim to be a scientist, but he looked carefully and deeply at the people he knew and concluded that there is more hypocrisy in Heaven and Earth than is dreamt of in some of our philosophies. Alfred Kinsey was also interested in the lives of women. His particular interest was also involving pleasures of the flesh, and so he and his assistants interviewed thousands of them in an effort to find out what they believed their pleasures of the flesh was like. Each woman told her story, although it was a story carefully structured by Kinsey’s questions. Some of them told everything they were permitted to tell, some only a little, and some probably lied. However, when all their tales were put together, a collective story emerged about a certain time and place. #RandolphHarris 21 of 22

It was a story more abstract than D. H. Lawrence’s, largely told in the language of statistics and, of course, without much psychological insight. However, it was a story nonetheless. One might call it a tribal tale of one thousand and one nights, told by a thousand and one women, and its theme was not much different from Lawrence’s namely, that the life involving pleasures of the flesh of some women is a lot stranger and more active than some other stories, particulary Dr. Freud’s, had led us to believe. I do not say that there is no difference between Lawrence and Kinsey. Lawrence unfolds his story in a language structure called a narrative. Kinsey’s language structure is called exposition. These forms are certainly different, although not so much as we might suppose. It has been remarked about the brothers Henry and William James that Henry was the novelist who wrote like a psychologist, and William the psychologist who wrote like a novelist. Certainly, in my meaning of the word “story,” exposition is as capable of unfolding one as is narrative. Of course, Lawrence’s story is controlled entirely by the limits of his own imagination, and he is not obliged to consult any social facts other than those he believed he knew. His story is pure personal perception, and that is why we call it fiction. Kinsey’s story comes from the mouths of others, and he is limited by what they answered when he asked his questions. Kinsey’s story, therefore, we may call a documentary. However, like all stories, it is infused with moral prejudice and sociological theory. It is Kinsey who made up the questions, and chose who would be interviewed, the circumstances of the interview, and how the answers would be interpreted. All of this gives shape and point to his story. Indeed, we may assume that Kinsey, like Lawrence, knew from the outset what the theme of hist story would be. Otherwise, he probably would not have care to tell it. #RandolphHarris 22 of 22