From Weblogg-ed by Will Richardson
"It is the thesis of this book that change—constant, accelerating, ubiquitous—is the most striking characteristic of the world we live in and that our educational system has not yet recognized this fact. We maintain, further, that the abilities and attitudes required to deal adequately with change are those of the highest priority and that it is not beyond our ingenuity to design school environments which can help young people to master concepts necessary to survival in a rapidly changing world. The institution we call “school” is what it is because we made it that way. If it is irrelevant…if it shields children from reality…if it educates for obsolescence…if it does not develop intelligence…if it is based on fear…if it avoids the promotion of significant learnings…if it induces alienation…if it punishes creativity and independence…if, in short, it is not doing what needs to be done, it can be changed; it must be changed."
Neil Postman
Teaching as a Subversive Activity
1968
Forty two years ago. It really, really begs the question…can it?
Wednesday, September 15, 2010
Tuesday, September 14, 2010
The Reality of Complexity
This is a brief summary of two essays by Roger Lewin, The Reality of Complexity and Leading at the Edge: How Leaders Influence Complex Systems (coauthored with Birute Regine). Both of these essays refer to his two books on complexity, Weaving Complexity and Business: Engaging the Soul at Work, also coauthored with Birute Regine, and Complexity: Life at the Edge of Chaos.
In The Reality of Complexity, Lewin writes, “We argue that managers, consultants, entrepreneurs, executives, other business professionals indeed, anyone who works can take some comfort in the fact that they are not alone in riding a bucking bronco of change that demands a different understanding of the world. Science, too, is in the midst of an important intellectual shift, a true Kuhnian paradigm shift that parallels what is happening in business, or, more accurately, is the vanguard of that change. Where once the natural world was viewed as linear and mechanistic, where simple cause-and-effect solutions were expected to explain the complex phenomena of nature, scientists now realize that much of their world is nonlinear and organic, characterized by uncertainty and unpredictability. As in science, managers are discovering that their world is not linear but rather predominantly nonlinear, not mechanistic but rather organic and complex. It’s amazing how far we have been able to take the linear model for understanding the world, both in science and in business. But in the new economy, the limitations of the mechanistic model are becoming starkly apparent. A new way of thinking is required.
The realization that much of the world dances to nonlinear tunes has given birth to the new science of complexity, whose midwife was the power of modern computation, which for the first time allows complex processes to be studied. The science is still in its infancy, and is multifaceted, reflecting different avenues of study. The avenue most relevant to understanding organizational dynamics within companies and the web of economic activity among them is the study of complex adaptive systems. Simply defined, complex adaptive systems are composed of a diversity of agents that interact with each other, mutually affect each other, and in so doing generate novel behavior for the system as a whole, such as in evolution, ecosystems, and the human mind. But the pattern of behavior we see in these systems is not constant, because when a system’s environment changes, so does the behavior of its agents, and, as a result, so does the behavior of the system as a whole. In other words, the system is constantly adapting to the conditions around it. Over time, the system evolves through ceaseless adaptation.
Complexity scientists are learning about these dynamics of complex systems principally through computer models, but also through observation of the natural world. “That’s all fine and dandy for scientists and academicians,” one executive commented when we made this point, “but what’s it got to do with me and my problems?” The point is that business organizations are also complex adaptive systems. This means that what complexity scientists are learning about natural systems has the potential to illuminate the fundamental dynamics of business organizations, too. Companies in a fast-changing business environment need to be able to produce constant innovation, need to be constantly adapting, and be in a state of continual evolution, if they are to survive.”
He believes that relationships are the new bottom line. Not just who you are linked to but caring relationships driven by values. He notes, “We can restate this in the language of complexity science as follows: in complex adaptive systems, agents interact, and when they have a mutual effect on one another, something novel emerges. Anything that enhances these interactions will enhance the creativity and adaptability of the system. In human organizations this translates into agents as people, and interactions with mutual effect as being relationships that are grounded in a sense of mutuality: people share a mutual respect, and have a mutual influence and impact on each other. From this emerged genuine care. Care is not a thing but an action to be care-full to care about your work, to care for fellow workers, to care for the organization, to care about the community. We saw that genuine care enhanced the relationships in these companies, with CEOs engendering trust and loyalty in their people, and the people being more willing to contribute to the needs of the company. In the context of complexity science, care, which enhances relationships, in turn enhances companies’ creativity and adaptability.”
This is an extremely novel interpretation. We’ve had management based on science in the past with the result that people became abstracted to be a number and a replaceable cog in a machine. (Remember Charlie Chaplin’s Modern Times.) Now, complexity science may provide the justification for oft debated, human centered management.
“We can see, therefore, that management practice guided by complexity science leads us to a very human orientation, and this was a surprise, counterintuitive. Of course, there have been many human-centered approaches in management before, amongst the more notable being political scientist Mary Parker Follett’s work done in the 1920s and 1930s in the United States, in which there has been a recent resurgence of interest. For more than half a century, there has been a constant battle between human-oriented management and scientific or mechanistic management, with the latter prevailing. But it is only now, and for the first time, that there is a science behind this way of thinking that gives a legitimacy to the whole realm of human-centered management. With complexity science, we have human-oriented management practice emerging from science, a novelty.”
In Leading at the Edge, the authors write, “At the cusp of the twenty-first century, we are experiencing unprecedented structural shifts in our economy brought about by the revolutions in computation and communication technologies. Today the world is linked in ways unimaginable just a decade ago. A new kind of economy is emerging–the connected economy--a shift that rivals the onset of the Industrial Revolution in its impact on society and the way commerce is transacted. And with this shift, the business world finds itself in the throes of revolutionary change. Where once companies imagined themselves to be the master’s of their own destiny, in a connected economy companies find themselves as interdependent players in a fluid and vacillating economic web, where their fate, more than ever, is affected by the behavior of other members.
The change is not only real, but it is also accelerating, driven by rapid technological innovation, the globalization of business, and, not the least of it, the arrival of the Internet and the new domain of Internet commerce. Change–the pace of innovation, of forming and reforming alliances among companies, of corporate mergers, emerging markets–all driven by this connected economy, creates an environment of urgency in the workplace and a need to respond, adapt, anticipate that is unprecedented in the world of business as we knew it. Consequently, business leaders are preoccupied with change itself–how to generate it, how to respond to it, how to avoid being overcome by it. But, as Intel’s Andy Grove indicates, change is not exactly a welcome guest in business: "With all the rhetoric about change, the fact is that we managers hate change, especially when it involves us."
During these changing times, leaders and managers are finding many of their background assumptions and time-honored business models inadequate to help them understand what is going on, let alone how to deal with it. Where managers once operated with a Tayloresque mechanistic model of their world, which was predicated on linear thinking, control, and predictability, they now find themselves struggling with something more nonlinear, where limited control and a restricted ability to predict outcomes are the order of the day.
Consequently, many managers and executive professionals are uneasy and eagerly seeking new ways of dealing with change in their organizations, as the current $17 billion-a-year management consulting business would indicate. In the new connected economy, the limitations of the mechanistic model are becoming starkly apparent and a different mode of thinking is needed. In the connected economy of the twenty-first century, leaders cannot afford to try to succeed with management methods that were developed in a different age and for a different type of business environment.”
The authors conducted a study of organizations that exhibited some of the fundamental characteristics of a complexity science informed organization – “organizationally flat, have fewer levels of hierarchy, and promote open and plentiful communication and diversity. Complexity science argues that these properties enhance a system’s capacity for adaptability, thus, in the case of business, giving them a cutting edge in these fast-changing times. The companies we chose for our study therefore shared the properties of being organizationally flat and having rich, open communication. But we had no idea what we would find in the realm of organizational dynamics, of leadership and management style, and people’s work experience.
What we discovered was a style of leadership that unleashed enormous human potential in these organizations. We saw similar patterns among the leaders–CEOs, executive directors, chairmen, senior executives, managers–in how they worked with their business as a complex system. Because these patterns in leadership style emerged in companies of very different sizes and very different economic sectors, we infer that we are seeing something fundamental in how to lead change in organizations so that it is more adaptable and how to cultivate a culture in the workplace that is better able to embrace and create change.”
They found a way of leading change--an organic approach that is informed by complexity principles; and a style of leadership, paradoxical leadership that cultivates conditions for constructive change in organizations.
Later, the authors explain, “These elements of an organic approach for leading change are a different way of doing things in that these leaders didn’t make changes, they cultivated conditions for change to occur. Instead of implementing strategies or plans, they generated ambiguity and uncertainty, encouraged risks, attended to relationships which allowed the organization to rearrange itself. They engaged the whole person and forged connections between people which in turn made their organization more whole and connected.
If organizations are complex systems, leading in an interconnected, dynamic system requires a different way of being a leader. Leading in a dynamic system is more like an improvisational dance with the system rather than a mechanistic imperative of doing things to the system, as if it were an object that could be fixed. This casts the meaning of leadership itself in a different light that dispels certain beliefs and myths about what it means to be a leader in a traditional sense.”
The three myths of leadership that a complexity view dispels are autonomy, control, and omniscience.
The authors write, “What we have done is identify an intellectual framework, a scientific understanding of organizational dynamics that puts these behaviors under one umbrella of complexity, which shows why these behaviors are effective. We can see that these behaviors, such as mutuality and care, are efficacious in the business environment, not because being "nice" to people is a good and human thing to do, which, of course, it is; but because we are positively engaging the agents and the dynamics of the complex adaptive system, and moving the system toward the zone of creative adaptability.”
In The Reality of Complexity, Lewin writes, “We argue that managers, consultants, entrepreneurs, executives, other business professionals indeed, anyone who works can take some comfort in the fact that they are not alone in riding a bucking bronco of change that demands a different understanding of the world. Science, too, is in the midst of an important intellectual shift, a true Kuhnian paradigm shift that parallels what is happening in business, or, more accurately, is the vanguard of that change. Where once the natural world was viewed as linear and mechanistic, where simple cause-and-effect solutions were expected to explain the complex phenomena of nature, scientists now realize that much of their world is nonlinear and organic, characterized by uncertainty and unpredictability. As in science, managers are discovering that their world is not linear but rather predominantly nonlinear, not mechanistic but rather organic and complex. It’s amazing how far we have been able to take the linear model for understanding the world, both in science and in business. But in the new economy, the limitations of the mechanistic model are becoming starkly apparent. A new way of thinking is required.
The realization that much of the world dances to nonlinear tunes has given birth to the new science of complexity, whose midwife was the power of modern computation, which for the first time allows complex processes to be studied. The science is still in its infancy, and is multifaceted, reflecting different avenues of study. The avenue most relevant to understanding organizational dynamics within companies and the web of economic activity among them is the study of complex adaptive systems. Simply defined, complex adaptive systems are composed of a diversity of agents that interact with each other, mutually affect each other, and in so doing generate novel behavior for the system as a whole, such as in evolution, ecosystems, and the human mind. But the pattern of behavior we see in these systems is not constant, because when a system’s environment changes, so does the behavior of its agents, and, as a result, so does the behavior of the system as a whole. In other words, the system is constantly adapting to the conditions around it. Over time, the system evolves through ceaseless adaptation.
Complexity scientists are learning about these dynamics of complex systems principally through computer models, but also through observation of the natural world. “That’s all fine and dandy for scientists and academicians,” one executive commented when we made this point, “but what’s it got to do with me and my problems?” The point is that business organizations are also complex adaptive systems. This means that what complexity scientists are learning about natural systems has the potential to illuminate the fundamental dynamics of business organizations, too. Companies in a fast-changing business environment need to be able to produce constant innovation, need to be constantly adapting, and be in a state of continual evolution, if they are to survive.”
He believes that relationships are the new bottom line. Not just who you are linked to but caring relationships driven by values. He notes, “We can restate this in the language of complexity science as follows: in complex adaptive systems, agents interact, and when they have a mutual effect on one another, something novel emerges. Anything that enhances these interactions will enhance the creativity and adaptability of the system. In human organizations this translates into agents as people, and interactions with mutual effect as being relationships that are grounded in a sense of mutuality: people share a mutual respect, and have a mutual influence and impact on each other. From this emerged genuine care. Care is not a thing but an action to be care-full to care about your work, to care for fellow workers, to care for the organization, to care about the community. We saw that genuine care enhanced the relationships in these companies, with CEOs engendering trust and loyalty in their people, and the people being more willing to contribute to the needs of the company. In the context of complexity science, care, which enhances relationships, in turn enhances companies’ creativity and adaptability.”
This is an extremely novel interpretation. We’ve had management based on science in the past with the result that people became abstracted to be a number and a replaceable cog in a machine. (Remember Charlie Chaplin’s Modern Times.) Now, complexity science may provide the justification for oft debated, human centered management.
“We can see, therefore, that management practice guided by complexity science leads us to a very human orientation, and this was a surprise, counterintuitive. Of course, there have been many human-centered approaches in management before, amongst the more notable being political scientist Mary Parker Follett’s work done in the 1920s and 1930s in the United States, in which there has been a recent resurgence of interest. For more than half a century, there has been a constant battle between human-oriented management and scientific or mechanistic management, with the latter prevailing. But it is only now, and for the first time, that there is a science behind this way of thinking that gives a legitimacy to the whole realm of human-centered management. With complexity science, we have human-oriented management practice emerging from science, a novelty.”
In Leading at the Edge, the authors write, “At the cusp of the twenty-first century, we are experiencing unprecedented structural shifts in our economy brought about by the revolutions in computation and communication technologies. Today the world is linked in ways unimaginable just a decade ago. A new kind of economy is emerging–the connected economy--a shift that rivals the onset of the Industrial Revolution in its impact on society and the way commerce is transacted. And with this shift, the business world finds itself in the throes of revolutionary change. Where once companies imagined themselves to be the master’s of their own destiny, in a connected economy companies find themselves as interdependent players in a fluid and vacillating economic web, where their fate, more than ever, is affected by the behavior of other members.
The change is not only real, but it is also accelerating, driven by rapid technological innovation, the globalization of business, and, not the least of it, the arrival of the Internet and the new domain of Internet commerce. Change–the pace of innovation, of forming and reforming alliances among companies, of corporate mergers, emerging markets–all driven by this connected economy, creates an environment of urgency in the workplace and a need to respond, adapt, anticipate that is unprecedented in the world of business as we knew it. Consequently, business leaders are preoccupied with change itself–how to generate it, how to respond to it, how to avoid being overcome by it. But, as Intel’s Andy Grove indicates, change is not exactly a welcome guest in business: "With all the rhetoric about change, the fact is that we managers hate change, especially when it involves us."
During these changing times, leaders and managers are finding many of their background assumptions and time-honored business models inadequate to help them understand what is going on, let alone how to deal with it. Where managers once operated with a Tayloresque mechanistic model of their world, which was predicated on linear thinking, control, and predictability, they now find themselves struggling with something more nonlinear, where limited control and a restricted ability to predict outcomes are the order of the day.
Consequently, many managers and executive professionals are uneasy and eagerly seeking new ways of dealing with change in their organizations, as the current $17 billion-a-year management consulting business would indicate. In the new connected economy, the limitations of the mechanistic model are becoming starkly apparent and a different mode of thinking is needed. In the connected economy of the twenty-first century, leaders cannot afford to try to succeed with management methods that were developed in a different age and for a different type of business environment.”
The authors conducted a study of organizations that exhibited some of the fundamental characteristics of a complexity science informed organization – “organizationally flat, have fewer levels of hierarchy, and promote open and plentiful communication and diversity. Complexity science argues that these properties enhance a system’s capacity for adaptability, thus, in the case of business, giving them a cutting edge in these fast-changing times. The companies we chose for our study therefore shared the properties of being organizationally flat and having rich, open communication. But we had no idea what we would find in the realm of organizational dynamics, of leadership and management style, and people’s work experience.
What we discovered was a style of leadership that unleashed enormous human potential in these organizations. We saw similar patterns among the leaders–CEOs, executive directors, chairmen, senior executives, managers–in how they worked with their business as a complex system. Because these patterns in leadership style emerged in companies of very different sizes and very different economic sectors, we infer that we are seeing something fundamental in how to lead change in organizations so that it is more adaptable and how to cultivate a culture in the workplace that is better able to embrace and create change.”
They found a way of leading change--an organic approach that is informed by complexity principles; and a style of leadership, paradoxical leadership that cultivates conditions for constructive change in organizations.
Later, the authors explain, “These elements of an organic approach for leading change are a different way of doing things in that these leaders didn’t make changes, they cultivated conditions for change to occur. Instead of implementing strategies or plans, they generated ambiguity and uncertainty, encouraged risks, attended to relationships which allowed the organization to rearrange itself. They engaged the whole person and forged connections between people which in turn made their organization more whole and connected.
If organizations are complex systems, leading in an interconnected, dynamic system requires a different way of being a leader. Leading in a dynamic system is more like an improvisational dance with the system rather than a mechanistic imperative of doing things to the system, as if it were an object that could be fixed. This casts the meaning of leadership itself in a different light that dispels certain beliefs and myths about what it means to be a leader in a traditional sense.”
The three myths of leadership that a complexity view dispels are autonomy, control, and omniscience.
The authors write, “What we have done is identify an intellectual framework, a scientific understanding of organizational dynamics that puts these behaviors under one umbrella of complexity, which shows why these behaviors are effective. We can see that these behaviors, such as mutuality and care, are efficacious in the business environment, not because being "nice" to people is a good and human thing to do, which, of course, it is; but because we are positively engaging the agents and the dynamics of the complex adaptive system, and moving the system toward the zone of creative adaptability.”
Simplicity is Highly Overrated
Don Norman has written a provocative essay on his blog. His reports that research shows that people will purchase a product that has more controls and indicators on it than one with fewer. Humans seem to think that if the product looks complicated it must have more function and be more powerful.
He writes, "...it is the apparent complexity that drives the sale. And yes, it is the same complexity that frustrates those same people later on. But by then, it is too late: they have already purchased the product."
At the end of his essay her comments, "Logic is not the way to answer these issues: human behavior is the key. Avoid the engineer's and economist's fallacy: don't reason your way to a solution -- observe real people. We have to take human behavior the way it is, not the way we would wish it to be. So, of course I am in favor of good design and attractive products. Easy to use products. But when it comes time to purchase, people tend to go for the more powerful products, and they judge the power by the apparent complexity of the controls. If that is what people use as a purchasing choice, we must provide it for them. While making the actual complexity low, the real simplicity high. That's an exciting design challenge: make it look powerful while also making it easy to use. And attractive. And affordable. And functional. And environmentally appropriate. Accessible to all."
My only concern with his essay is that he uses complexity to mean complicated. I will write later on the taxonomy of simplicity and complexity.
He writes, "...it is the apparent complexity that drives the sale. And yes, it is the same complexity that frustrates those same people later on. But by then, it is too late: they have already purchased the product."
At the end of his essay her comments, "Logic is not the way to answer these issues: human behavior is the key. Avoid the engineer's and economist's fallacy: don't reason your way to a solution -- observe real people. We have to take human behavior the way it is, not the way we would wish it to be. So, of course I am in favor of good design and attractive products. Easy to use products. But when it comes time to purchase, people tend to go for the more powerful products, and they judge the power by the apparent complexity of the controls. If that is what people use as a purchasing choice, we must provide it for them. While making the actual complexity low, the real simplicity high. That's an exciting design challenge: make it look powerful while also making it easy to use. And attractive. And affordable. And functional. And environmentally appropriate. Accessible to all."
My only concern with his essay is that he uses complexity to mean complicated. I will write later on the taxonomy of simplicity and complexity.
Thursday, September 9, 2010
The Science of Cooperation
Utne Readers, Sept. - Oct. 2010
"Elinor Ostrom was an unusual choice for the 2009 Nobel Memorial Prize in Economic Sciences. She is the first woman to receive the prize, and her doctorate is in political science, not economics (though she considers herself a political economist). And while standard economics focuses on competition, her work is about cooperation.
Ostrom’s influential book Governing the Commons: The Evolution of Institutions for Collective Action was published in 1990. But her research on common property goes back to the 1960s, when she wrote her dissertation on groundwater in California. In 1973 she and her husband, Vincent Ostrom, founded the Workshop in Political Theory and Policy Analysis at Indiana University, which has produced hundreds of studies of the ways in which communities self-organize to solve common problems.
Fran Korten, Yes! magazine’s publisher, interviewed Ostrom shortly after Ostrom received the Nobel Prize.
Many people associate “the commons” with Garrett Hardin’s famous essay “The Tragedy of the Commons.” He says that if, for example, you have a pasture that everyone in a village has access to, then each person will put as many cows on that land as he can to maximize his own benefit, and pretty soon the pasture will be overgrazed and become worthless. What’s the difference between your perspective and Hardin’s?
I don’t see the human as hopeless. There’s a tendency to presume people act just for short-term profit. But anyone who knows about small-town businesses and how people in a community relate to one another realizes that many decisions are not made just for profit, and that humans do try to organize and solve problems.
If you are in a fishery or have a pasture and you know that not destroying it is to your family’s long-term benefit, and if you can talk with the other people who use that resource, then you may well figure out rules that fit that local setting and organize to enforce them. But if community members don’t have a good way of communicating with each other or the costs of self-organization are too high, then they won’t organize, and there will be failures."
Read the Article
"Elinor Ostrom was an unusual choice for the 2009 Nobel Memorial Prize in Economic Sciences. She is the first woman to receive the prize, and her doctorate is in political science, not economics (though she considers herself a political economist). And while standard economics focuses on competition, her work is about cooperation.
Ostrom’s influential book Governing the Commons: The Evolution of Institutions for Collective Action was published in 1990. But her research on common property goes back to the 1960s, when she wrote her dissertation on groundwater in California. In 1973 she and her husband, Vincent Ostrom, founded the Workshop in Political Theory and Policy Analysis at Indiana University, which has produced hundreds of studies of the ways in which communities self-organize to solve common problems.
Fran Korten, Yes! magazine’s publisher, interviewed Ostrom shortly after Ostrom received the Nobel Prize.
Many people associate “the commons” with Garrett Hardin’s famous essay “The Tragedy of the Commons.” He says that if, for example, you have a pasture that everyone in a village has access to, then each person will put as many cows on that land as he can to maximize his own benefit, and pretty soon the pasture will be overgrazed and become worthless. What’s the difference between your perspective and Hardin’s?
I don’t see the human as hopeless. There’s a tendency to presume people act just for short-term profit. But anyone who knows about small-town businesses and how people in a community relate to one another realizes that many decisions are not made just for profit, and that humans do try to organize and solve problems.
If you are in a fishery or have a pasture and you know that not destroying it is to your family’s long-term benefit, and if you can talk with the other people who use that resource, then you may well figure out rules that fit that local setting and organize to enforce them. But if community members don’t have a good way of communicating with each other or the costs of self-organization are too high, then they won’t organize, and there will be failures."
Read the Article
Education is a self organizing system, where learning is an emergent phenomenon.
Education scientist Sugata Mitra tackles one of the greatest problems of education -- the best teachers and schools don't exist where they're needed most. In a series of real-life experiments from New Delhi to South Africa to Italy, he gave kids self-supervised access to the web and saw results that could revolutionize how we think about teaching.
Sugata Mitra's "Hole in the Wall" experiments have shown that, in the absence of supervision or formal teaching, children can teach themselves and each other, if they're motivated by curiosity.
This is a very interesting and insightful body of work. He starts with the following premise: There are places on Earth, in every country, where, for various reasons, good schools cannot be built and good teachers cannot or do not want to go.
Then with technology and the Internet, he lets students find there own way to learn, sometimes without any problem to work and sometimes with a problem. He uses very little instructions and no actual "teaching". In some cases he uses what he calls "grandmothers" to encourage the kids.
The results are striking and counter intuitive.
His explanation is that he has created a complex system with emergent properties.
He defines two characteristics of the system:
Self organizing system: A self organizing system is one where the system structure appears without explicit intervention from outside the system.
Emergence: The appearance of a property not previously observed as a functional characteristic of the system.
He then concludes with what I think is a very powerful observation:
Education is a self organizing system, where learning is an emergent phenomenon.
Sugata Mitra's "Hole in the Wall" experiments have shown that, in the absence of supervision or formal teaching, children can teach themselves and each other, if they're motivated by curiosity.
This is a very interesting and insightful body of work. He starts with the following premise: There are places on Earth, in every country, where, for various reasons, good schools cannot be built and good teachers cannot or do not want to go.
Then with technology and the Internet, he lets students find there own way to learn, sometimes without any problem to work and sometimes with a problem. He uses very little instructions and no actual "teaching". In some cases he uses what he calls "grandmothers" to encourage the kids.
The results are striking and counter intuitive.
His explanation is that he has created a complex system with emergent properties.
He defines two characteristics of the system:
Self organizing system: A self organizing system is one where the system structure appears without explicit intervention from outside the system.
Emergence: The appearance of a property not previously observed as a functional characteristic of the system.
He then concludes with what I think is a very powerful observation:
Education is a self organizing system, where learning is an emergent phenomenon.
Often Wrong, But Never in Doubt
Richard Thaler, New York Times, 8/22/10
"Businesses in nearly every industry were caught off guard by the Great Recession. Few leaders in business — or government, for that matter — seem to have even considered the possibility that an economic downturn of this magnitude could happen.
What was wrong with their thinking? These decision-makers may have been betrayed by a flaw that has been documented in hundreds of studies: overconfidence.
Most of us think that we are “better than average” in most things. We are also “miscalibrated,” meaning that our sense of the probability of events doesn’t line up with reality. When we say we are sure about a certain fact, for example, we may well be right only half the time."
This is a really interesting article about how bad we are at forecasting the future.
"...chief financial officers of major American corporations are not very good at forecasting the future. The authors’ investigation used a quarterly survey of C.F.O.’s that Duke has been running since 2001. Among other things, the C.F.O.’s were asked about their expectations for the return of the Standard & Poor’s 500-stock index for the next year — both their best guess and their 80 percent confidence limit. This means that in the example above, there would be a 10 percent chance that the return would be higher than the upper bound, and a 10 percent chance that it would be less than the lower one.
It turns out that C.F.O.’s, as a group, display terrible calibration. The actual market return over the next year fell between their 80 percent confidence limits only a third of the time, so these executives weren’t particularly good at forecasting the stock market. In fact, their predictions were negatively correlated with actual returns. For example, in the survey conducted on Feb. 26, 2009, the C.F.O.’s made their most pessimistic predictions, expecting a market return of just 2.0 percent, with a lower bound of minus 10.2 percent. In fact, the market soared 42.6 percent over the next year."
One of the interesting omissions of this article is that it never mentions the complexity of the future. It blames the failures on "mis-calibration" and "hubris".
Read the Article
"Businesses in nearly every industry were caught off guard by the Great Recession. Few leaders in business — or government, for that matter — seem to have even considered the possibility that an economic downturn of this magnitude could happen.
What was wrong with their thinking? These decision-makers may have been betrayed by a flaw that has been documented in hundreds of studies: overconfidence.
Most of us think that we are “better than average” in most things. We are also “miscalibrated,” meaning that our sense of the probability of events doesn’t line up with reality. When we say we are sure about a certain fact, for example, we may well be right only half the time."
This is a really interesting article about how bad we are at forecasting the future.
"...chief financial officers of major American corporations are not very good at forecasting the future. The authors’ investigation used a quarterly survey of C.F.O.’s that Duke has been running since 2001. Among other things, the C.F.O.’s were asked about their expectations for the return of the Standard & Poor’s 500-stock index for the next year — both their best guess and their 80 percent confidence limit. This means that in the example above, there would be a 10 percent chance that the return would be higher than the upper bound, and a 10 percent chance that it would be less than the lower one.
It turns out that C.F.O.’s, as a group, display terrible calibration. The actual market return over the next year fell between their 80 percent confidence limits only a third of the time, so these executives weren’t particularly good at forecasting the stock market. In fact, their predictions were negatively correlated with actual returns. For example, in the survey conducted on Feb. 26, 2009, the C.F.O.’s made their most pessimistic predictions, expecting a market return of just 2.0 percent, with a lower bound of minus 10.2 percent. In fact, the market soared 42.6 percent over the next year."
One of the interesting omissions of this article is that it never mentions the complexity of the future. It blames the failures on "mis-calibration" and "hubris".
Read the Article
Wednesday, September 8, 2010
Complexity/Chaos Stories: Butterflies, Keystones and Climbers
Cynthia Kurtz, Story Colored Glasses, 9/3/10
This is an interesting and insightful blog entry (although somewhat long). Cynthia Kurtz describes herself as a “researcher, writer, and programmer who works on the ‘listening side’ of organizational and community narrative.”
In this essay, she looks at the subject of complexity through the lens of narrative, and apologizes to her readers. “Since I posted some thoughts about complexity a while back, I've been surprised both by the number of people who have been interested in what I said (and encouraged me to write more), and by the degree to which I find myself wanting to write more. I still have much to write about narrative, but I also seem to want to write more about complexity as it relates to sensemaking and decision support. Since this blog is supposed to be about narrative, I keep feeling a need to apologize whenever I write about complexity.
But really there is nothing to be sorry for. My work on the "listening side" of narrative centers on the place where stories and patterns come together. Narrative incorporates complexity because stories self-organize into emergent patterns, and complexity incorporates narrative because complex systems are historical systems. I remember when I first realized this, and what a rush it was to discover synergy between two fields I had come to love. Thus, dear reader, henceforth I resolve to stop apologizing for combining these topics!”
The metaphor (story) about the butterfly in Brazil and the tornado in Texas came from Lorenz. “Lorenz's first talk on the topic in 1972 was titled ‘Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?’ His answer was not ‘yes’ but an emphatic ‘impossible to say’.” Kurtz shows how this correct interpretation of the impact of minor perturbations in the weather morphed into predictability, linking cause and effect.
She gives a selection of excerpts and then points out, “These excerpts, and almost all popular and business interpretations of the butterfly effect, transform a statement about uncertainty to one about certainty. The second story changes the butterfly effect from tiny actions piling up in unpredictable ways to tiny actions having predictable and controllable impacts. I have taken to calling this second story the "underbutterfly effect," because the butterfly in these versions is a powerful underdog who changes the world, not one of millions of other butterflies (not to mention innumerable more powerful creatures) whose feeble flaps are lost in the sea of uncertainty in which we live.”
Kurtz examines two other narratives that have morphed into stories we want to believe in. We changed the story of the butterfly because we can’t seem to accept that a large part of our world exists without cause and effect in play. Causality is deeply ingrained in our world view.
“In 1969 Robert T. Paine introduced the idea of a keystone species to ecology”, she writes. “Paine discovered this phenomenon in an experiment during which he removed a single species of sea star from a small area of shoreline and found that it had far-reaching effects on species diversity. Most importantly, the effect produced by its removal was out of proportion to its relative abundance in the community.” Like the butterfly narrative, this story morphed driven by our desire for certainty. The keystone became what she calls a topstone. “As with the underbutterfly story, the topstone story began to surface soon after Paine started publishing papers about his concept. What seems to have happened is that people involved in wildlife conservation started trying to identify keystone species in order to wisely use limited conservation budgets. Political, cultural and special-interest complexities joined the mix, and the keystone species concept widened and weakened as a result. For environmental study, retrospective discovery might suffice, but for environmental action, people wanted certainty.”
Her last narrative is about the adaptive landscape. “I first encountered Sewall Wright's adaptive landscape metaphor in college, and as a visual thinker I found it useful right away. Even though the metaphor is severely limited, many evolutionary theorists use it as a visual shorthand for thinking about genetic change. The way the metaphor works is this. Populations are located in X and Y dimensions to describe their genetic makeup (in a radically simplified way). They exist on a landscape where the height of each point describes the fitness of the population with that particular XY combination of genetic variables.” By describing fitness as a peak, the metaphor conveyed a lot of uncertainty. A small nudge could send the species down in any direction into a valley. Physicists tend to look at this type of metaphor in the opposite direction where potential energy increase in the peaks and valleys are lower potential energy.
I have to admit that with my physics background I had trouble with section of her discussion because when I first saw the metaphor, I thought to my self that it was upside down. The trend would be for the species to always roll down the hill into the “genetic valley of death.”
Kurtz writes, “One more and then I'm really done, I promise. This is from The Quark and the Jaguar by Murray Gell-Mann:
Biologists conventionally represent fitness as increasing with increasing height, so that maxima of fitness correspond to the tops of hills and minima to the bottom of pits; however, I shall use the reverse convention, which is customary in many other fields, and turn the whole picture upside-down.
Gell-Mann then gets into the difficulties of this flip, seemingly without realizing it:
If the effect of evolution were always to move steadily downhill -- always to improve fitness -- then the genotype would be likely to get stuck at the bottom of a shallow depression and have no opportunity to reach the deep holes nearby that correspond to much greater fitness. At the very least, the genotype must be moving in a more complicated manner than just sliding downhill.
That is precisely the problem with flipping the landscape: that when you do so, things that are in reality very complicated seem simple, and certain.”
This desire to correct uncertainty runs strong in us. She writes, “If you think about it, this is not at all surprising. We have been conditioned since an early age to believe in this equation:
uncertainty + science = certainty
When we meet an equation like this:
uncertainty + science = more uncertainty
We react, and a second story arises. That can't be right. There must be another explanation. That's what Edward Lorenz said when his computer generated a new weather system based on what he thought were the same inputs. He called in the hardware engineers to find the broken vacuum tube.”
She summarizes her essay in a section titled “A Generation, or Two Or Three, to Sink In. “If people tell second stories about complexity because we aren't ready for the first stories, I think our children are ready. In many of my narrative projects I ask people to rate the predictability of events in stories -- it's useful to map perceptions of stability and instability across conceptual space. I've noticed a pattern across several projects that older people are more likely to associate instability with negative outcomes in stories. Younger people are more likely to mark stories as both unstable and positive.
I was thinking about all this the other day while playing with my son, and two things happened that gave me food for thought. The first was that we watched the movie Clifford's Really Big Movie. It's a great movie, and it's in our pantheon now and will probably be watched many more times. One of my favorite parts of the movie is this lovely song, which my six-year-old understood and liked immediately. It goes, in part:
You've gotta get lost if you wanna get found
Gotta wind up to get unwound
Things only look up from down below
And I can't come home until I go
It only gets better after it gets worse
Happy ever after needs a scary part first
You've gotta fall down to get back on
And I can't come home until I'm gone.”
Later, she writes, “According to my surely-biased reading, there are three ways the authors of business books about complexity and chaos provide reassurance to those in charge. One is to drain the power out of the major discoveries by highlighting the second stories, which do exist in science and so can be called scientific: the underbutterfly, the topstone, and the easy roller. The first stories can be waved away as "internal disputes" that don't matter.
The second method of making complexity palatable to those in charge is to make it seem magical. That is why the phrase "order for free" is so wildly attractive in these books, and why people love to throw around terms like "strange attractor" and "fitness landscape" and "coevolution" -- because they are magic words of power that seem to promise something for nothing. Even "nonlinear" effects are spoken of mainly for the idea of something small going in and something big (and beneficial to the reader) coming out. I see this rose-colored view of complexity in most (but not all) business writings about complexity. Consider for example the way people talk about coevolution: nearly every treatment of business coevolution I have read has talked about it like nothing can possibly go wrong. But in real coevolution things can and do go horribly wrong at times. It is these sorts of distortions that not only give complexity concepts a bad name (because rarely can such wild claims of magical power be justified) but also spread confusion about the true utility of complexity and chaos based approaches.
And finally, the third and most used tool in the business complexity writer's toolkit is that the sky is falling. You need this, say the business books, because the world has changed in such dramatic ways that you can't possibly survive without it. People who use this tool ramp up the fear quotient by making claims such as that "an organization is a complex adaptive system" -- the implication being, and you had better find out what that means, and quick. But organizations are not complex adaptive systems! More precisely, they are not only complex adaptive systems. An organization is a lot of people. Those people interact with each other in many ways, some of which are complex and emergent, and some of which are not. Organization and self-organization, hierarchy and meshwork are inextricably bound up together in organizations, and saying an organization "is" one without the other is sheer nonsense and is probably meant to entice rather than inform. There are no only-complex social groupings in human life. Every gathering of ten huts has a path through it. Every lunch meeting has a leader. Every subway car has a social structure, if even only for the two minutes the same people are in it. That's what we do. There may be such things as only-complex systems in the lives of social insects, but even there some hierarchy (in the form of central pheromonal control) is usually mixed in.”
She concludes with, “My advice, if anyone wanted it, would be this. First, stop saying everything is complex, and start talking about how complexity and hierarchy can work to mutual benefit.”
“When you don't fear complexity, when you see it as a part of reality but not a ‘whole new world’ dominated by a falling sky, you don't have to muzzle it. The underbutterfly and the topstone and the easy roller can go plague other people. You can take the butterfly and the keystone and the steadfast climber as they come to you, in stride. You can learn to recognize them, deal with them, work with them and even in time welcome them as old friends. You'll just know better than to hand over your car keys to them.”
As it turns out, this is the conclusion I had recently reached intuitively. She has done all the work that suggests that this is correct. I was drawing from my experience with physics and squaring Newtonian, Quantum and Relativistic physics. All are present in everything. It’s just in certain conditions one view works best. But you have to know when you are in what type of physics. To complicate matters, there are at least three different types of “messy” complexity and one type more tractable. For example in the behavior of markets there are trends, cycles and complexity. Complexity is in the fine structure of the behavior of the market.
Read Her Blog
This is an interesting and insightful blog entry (although somewhat long). Cynthia Kurtz describes herself as a “researcher, writer, and programmer who works on the ‘listening side’ of organizational and community narrative.”
In this essay, she looks at the subject of complexity through the lens of narrative, and apologizes to her readers. “Since I posted some thoughts about complexity a while back, I've been surprised both by the number of people who have been interested in what I said (and encouraged me to write more), and by the degree to which I find myself wanting to write more. I still have much to write about narrative, but I also seem to want to write more about complexity as it relates to sensemaking and decision support. Since this blog is supposed to be about narrative, I keep feeling a need to apologize whenever I write about complexity.
But really there is nothing to be sorry for. My work on the "listening side" of narrative centers on the place where stories and patterns come together. Narrative incorporates complexity because stories self-organize into emergent patterns, and complexity incorporates narrative because complex systems are historical systems. I remember when I first realized this, and what a rush it was to discover synergy between two fields I had come to love. Thus, dear reader, henceforth I resolve to stop apologizing for combining these topics!”
The metaphor (story) about the butterfly in Brazil and the tornado in Texas came from Lorenz. “Lorenz's first talk on the topic in 1972 was titled ‘Predictability: Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?’ His answer was not ‘yes’ but an emphatic ‘impossible to say’.” Kurtz shows how this correct interpretation of the impact of minor perturbations in the weather morphed into predictability, linking cause and effect.
She gives a selection of excerpts and then points out, “These excerpts, and almost all popular and business interpretations of the butterfly effect, transform a statement about uncertainty to one about certainty. The second story changes the butterfly effect from tiny actions piling up in unpredictable ways to tiny actions having predictable and controllable impacts. I have taken to calling this second story the "underbutterfly effect," because the butterfly in these versions is a powerful underdog who changes the world, not one of millions of other butterflies (not to mention innumerable more powerful creatures) whose feeble flaps are lost in the sea of uncertainty in which we live.”
Kurtz examines two other narratives that have morphed into stories we want to believe in. We changed the story of the butterfly because we can’t seem to accept that a large part of our world exists without cause and effect in play. Causality is deeply ingrained in our world view.
“In 1969 Robert T. Paine introduced the idea of a keystone species to ecology”, she writes. “Paine discovered this phenomenon in an experiment during which he removed a single species of sea star from a small area of shoreline and found that it had far-reaching effects on species diversity. Most importantly, the effect produced by its removal was out of proportion to its relative abundance in the community.” Like the butterfly narrative, this story morphed driven by our desire for certainty. The keystone became what she calls a topstone. “As with the underbutterfly story, the topstone story began to surface soon after Paine started publishing papers about his concept. What seems to have happened is that people involved in wildlife conservation started trying to identify keystone species in order to wisely use limited conservation budgets. Political, cultural and special-interest complexities joined the mix, and the keystone species concept widened and weakened as a result. For environmental study, retrospective discovery might suffice, but for environmental action, people wanted certainty.”
Her last narrative is about the adaptive landscape. “I first encountered Sewall Wright's adaptive landscape metaphor in college, and as a visual thinker I found it useful right away. Even though the metaphor is severely limited, many evolutionary theorists use it as a visual shorthand for thinking about genetic change. The way the metaphor works is this. Populations are located in X and Y dimensions to describe their genetic makeup (in a radically simplified way). They exist on a landscape where the height of each point describes the fitness of the population with that particular XY combination of genetic variables.” By describing fitness as a peak, the metaphor conveyed a lot of uncertainty. A small nudge could send the species down in any direction into a valley. Physicists tend to look at this type of metaphor in the opposite direction where potential energy increase in the peaks and valleys are lower potential energy.
I have to admit that with my physics background I had trouble with section of her discussion because when I first saw the metaphor, I thought to my self that it was upside down. The trend would be for the species to always roll down the hill into the “genetic valley of death.”
Kurtz writes, “One more and then I'm really done, I promise. This is from The Quark and the Jaguar by Murray Gell-Mann:
Biologists conventionally represent fitness as increasing with increasing height, so that maxima of fitness correspond to the tops of hills and minima to the bottom of pits; however, I shall use the reverse convention, which is customary in many other fields, and turn the whole picture upside-down.
Gell-Mann then gets into the difficulties of this flip, seemingly without realizing it:
If the effect of evolution were always to move steadily downhill -- always to improve fitness -- then the genotype would be likely to get stuck at the bottom of a shallow depression and have no opportunity to reach the deep holes nearby that correspond to much greater fitness. At the very least, the genotype must be moving in a more complicated manner than just sliding downhill.
That is precisely the problem with flipping the landscape: that when you do so, things that are in reality very complicated seem simple, and certain.”
This desire to correct uncertainty runs strong in us. She writes, “If you think about it, this is not at all surprising. We have been conditioned since an early age to believe in this equation:
uncertainty + science = certainty
When we meet an equation like this:
uncertainty + science = more uncertainty
We react, and a second story arises. That can't be right. There must be another explanation. That's what Edward Lorenz said when his computer generated a new weather system based on what he thought were the same inputs. He called in the hardware engineers to find the broken vacuum tube.”
She summarizes her essay in a section titled “A Generation, or Two Or Three, to Sink In. “If people tell second stories about complexity because we aren't ready for the first stories, I think our children are ready. In many of my narrative projects I ask people to rate the predictability of events in stories -- it's useful to map perceptions of stability and instability across conceptual space. I've noticed a pattern across several projects that older people are more likely to associate instability with negative outcomes in stories. Younger people are more likely to mark stories as both unstable and positive.
I was thinking about all this the other day while playing with my son, and two things happened that gave me food for thought. The first was that we watched the movie Clifford's Really Big Movie. It's a great movie, and it's in our pantheon now and will probably be watched many more times. One of my favorite parts of the movie is this lovely song, which my six-year-old understood and liked immediately. It goes, in part:
You've gotta get lost if you wanna get found
Gotta wind up to get unwound
Things only look up from down below
And I can't come home until I go
It only gets better after it gets worse
Happy ever after needs a scary part first
You've gotta fall down to get back on
And I can't come home until I'm gone.”
Later, she writes, “According to my surely-biased reading, there are three ways the authors of business books about complexity and chaos provide reassurance to those in charge. One is to drain the power out of the major discoveries by highlighting the second stories, which do exist in science and so can be called scientific: the underbutterfly, the topstone, and the easy roller. The first stories can be waved away as "internal disputes" that don't matter.
The second method of making complexity palatable to those in charge is to make it seem magical. That is why the phrase "order for free" is so wildly attractive in these books, and why people love to throw around terms like "strange attractor" and "fitness landscape" and "coevolution" -- because they are magic words of power that seem to promise something for nothing. Even "nonlinear" effects are spoken of mainly for the idea of something small going in and something big (and beneficial to the reader) coming out. I see this rose-colored view of complexity in most (but not all) business writings about complexity. Consider for example the way people talk about coevolution: nearly every treatment of business coevolution I have read has talked about it like nothing can possibly go wrong. But in real coevolution things can and do go horribly wrong at times. It is these sorts of distortions that not only give complexity concepts a bad name (because rarely can such wild claims of magical power be justified) but also spread confusion about the true utility of complexity and chaos based approaches.
And finally, the third and most used tool in the business complexity writer's toolkit is that the sky is falling. You need this, say the business books, because the world has changed in such dramatic ways that you can't possibly survive without it. People who use this tool ramp up the fear quotient by making claims such as that "an organization is a complex adaptive system" -- the implication being, and you had better find out what that means, and quick. But organizations are not complex adaptive systems! More precisely, they are not only complex adaptive systems. An organization is a lot of people. Those people interact with each other in many ways, some of which are complex and emergent, and some of which are not. Organization and self-organization, hierarchy and meshwork are inextricably bound up together in organizations, and saying an organization "is" one without the other is sheer nonsense and is probably meant to entice rather than inform. There are no only-complex social groupings in human life. Every gathering of ten huts has a path through it. Every lunch meeting has a leader. Every subway car has a social structure, if even only for the two minutes the same people are in it. That's what we do. There may be such things as only-complex systems in the lives of social insects, but even there some hierarchy (in the form of central pheromonal control) is usually mixed in.”
She concludes with, “My advice, if anyone wanted it, would be this. First, stop saying everything is complex, and start talking about how complexity and hierarchy can work to mutual benefit.”
“When you don't fear complexity, when you see it as a part of reality but not a ‘whole new world’ dominated by a falling sky, you don't have to muzzle it. The underbutterfly and the topstone and the easy roller can go plague other people. You can take the butterfly and the keystone and the steadfast climber as they come to you, in stride. You can learn to recognize them, deal with them, work with them and even in time welcome them as old friends. You'll just know better than to hand over your car keys to them.”
As it turns out, this is the conclusion I had recently reached intuitively. She has done all the work that suggests that this is correct. I was drawing from my experience with physics and squaring Newtonian, Quantum and Relativistic physics. All are present in everything. It’s just in certain conditions one view works best. But you have to know when you are in what type of physics. To complicate matters, there are at least three different types of “messy” complexity and one type more tractable. For example in the behavior of markets there are trends, cycles and complexity. Complexity is in the fine structure of the behavior of the market.
Read Her Blog
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