Complexity. The new world between chance and choice
April 10, 2010
Nonlinear dynamics are concerned with complex, messy systems. Examples for these systems are the human brain, the evolution of life itself and the weather. There is not a single science of non-linearity, but there are different streams of research such as chaos theory or the theory of complex adaptive systems. The latter strand takes up an agent- and rules of interaction-based approach to modeling complexity. The first explains the behavior of systems that can be modeled by complex equations where the output of one calculation is taken as the input for the next. These equations are repetitive and iterative.
Chaos theory explains how the parameters in the equations cause patterns in time. These patterns are called attractors. A parameter might be the flow of information or the amount of energy in the system. At low rates the system moves forward displaying a repetitive, stuck behavior. This pattern is called a point attractor. At higher rates the pattern changes. At very high rates of, for example information flow, the system displays a totally random behavior. The pattern is highly unstable. However, there is a level between repetition/stability and randomness/instability. This level is called the edge of chaos. The pattern in time is called a strange attractor. The strange thing with a strange attractor is that the ongoing movement is never the same but always recognizable. The pattern is paradoxically stable and unstable, predictable and unpredictable at the same time. These patterns are spatially called fractals.
Chaos describes a dynamic that is not a synthesis of order and disorder. It is about orderly disorder or disorderly order. The very meaning of these words is transformed.
The weather is normally used as an example of a system that displays this pattern. The overall weather patterns can be (almost) predicted over short periods of time. Over long periods, the behavior cannot be predicted. The long-term behavior of a system like this is determined as much by the smallest changes in the smallest of parts of the system, as it is determined by the laws governing it. The conclusion is very clear. Predictability is always short-term. Long-term predictions would only be possible if absolutely all the variables in the system could be measured with absolutely infinite accuracy. But it is impossible to know all the variables and it is totally impossible to measure all the variables with the accuracy needed.
The smallest overlooked variable or the most minute change can escalate up by non-linear iterations into a major transformative change in the later life of the system. Another conclusion is that from a chaos theory perspective, movement towards equilibrium is always movement towards death. If a system is healthy, successful and alive, it is “at the edge of chaos” where the long-term cannot be seen.
Classical physics took individual entities and their movement (trajectories) as the unit of analysis. Chaos theorists such as Ilya Prigogine, claimed that these trajectories cannot be calculated because of the impossibility of measuring with the precision needed. But there was something even far more exciting going on. Henri Poincaré was the first scientist to identify two distinct kinds of energy. The first was the (kinetic) energy in the movement of the particle itself. The second was the energy arising from the interaction between particles. When this second energy is not there, the system is in a state of non-dynamism. When there is interactive energy, the system is dynamic and capable of novelty and renewal. Interaction creates resonance between the particles. Resonance is the result of coupling the frequencies of particles leading to an increase in the amplitude of motion. Resonance makes it impossible to identify individual movement in interactive environments because the individual’s trajectory depends more on the resonance with others than on the kinetic energy contained by the individual itself.
Every interaction of any particles is thus potentially meaningful and can lead to amplification of the slightest variation. Interactive systems with even the smallest variations take on a life of their own that is under continuous construction. The future form and direction of the system is not visible in the system at any given time. The future is not in the system and it cannot be chosen or planned by anyone.
The scientists at the Santa Fe Institute developed the other strand of research: the complex adaptive systems approach. A CAS consists of a large number of agents. Each agent behaves according to its own intentions and rules for local interaction. Local here means that no agent can interact with the whole population of agents at the same time. No individual agent can determine the pattern of behavior that the system as a whole displays. These adaptive systems display the same dynamics as the chaos theorists found: stable equilibrium at one end of the spectrum, random chaos at the other, and in-between the newly found complex dynamic of stability and instability, predictability and unpredictability, paradoxically at the same time: the edge of chaos.
The conclusions are important for us. Firstly, novelty always emerges in a radically unpredictable way. Secondly, the patterns of healthy behavior are not caused by competitive selection or independent choices made by independent agents. Instead, what is happening, happens in interaction, not by chance or by choice, but as a result of the interaction itself.
The Internet changes the patterns of connectivity and makes possible new enriching variety in interaction. The changed dynamics we experience every day through social media have the very characteristics of the edge of chaos.
The sciences of complexity change our perspective and thinking. Perhaps, as a result we should, especially in management, focus more attention on what we are doing than what we should be doing. Following the thinking presented by the most advanced scientific researchers, the important question to answer is not what should happen in the future, but what is happening now?
Our focus should be on the communicative interaction creating the continuously developing pattern that is our life.
Thank you Stu Kauffman and W Brian Arthur. Based on Ralph Stacey and Doug Griffin.
Responsiveness, emergence and self-organization
March 21, 2010
I gave keynote speeches at two conferences this week. The organizers of the events did not suggest a (#) hashtag to be used by the delegates. There wasn’t any backchannel Twitter discussion going on in the audience. I felt strange.
I wasn’t able to listen and respond to real-time feedback. I was missing the self-regulation and self-organizing that social media make possible. This is what I have grown so accustomed to. I started to ponder on two questions: Is it becoming more common for responsiveness to be the missing ingredient in many communities? And can there be rules for responsiveness that help to create viable communities?
I know that there are problems with two-way communication. There are the people with a pre-set interpretative model. We all know the people who are grinding their axe at the back of the room. They are the know-alls and the one-point-of-view evangelists, the people who insist on bringing all conversations round to their particular issue.
I know that there are even bigger issues: All participants are never visible. Any given conversation on the Web may have a few active participants and several silent ones. This creates a fundamental imbalance in the system and gives the oddballs the opportunity to dominate the space in a way that would be much harder to do off-line.
What I felt at the conferences was a crucial disparity: they hear me talking, but I don’t hear them. The audience was both present and absent at the same time. A conference with a Twitter backchannel creates inputs from the official speakers and responses coming from the audience that is present, but also the online audiences elsewhere. The most important thing is that the primary inputs can then be further adjusted on the basis of the responses from the group. There is real-time emergent self-organizing going on.
Information flows are far too often unidirectional. The audience is present but in a passive, invisible way. The tyranny of the hatemonger results from this one-way flow and scarcity of feedback.
The volume is too high for any single individual to filter out the useless or plain repulsive. There are, however, ways to filter out the irrelevant and the obnoxious, but it requires people to respond. If you are a participant, you are also a moderator.
The quality control has to be handed to the community itself without any single individual being in control. The solution is fairly simple in theory. It is about responsiveness and a mix of negative and positive feedback.
You always rate what you see. The ratings coalesce algorithmically into something that is called karma in Slashdot. If your contributions are highly rated you get karma points. The karma you have earned means that your subsequent posts begin life at a higher level than posts by others. Your ratings also have a higher value than ratings given by people with fewer karma points. Dynamic rating is to posts what links are to websites.
The people worth following, the leaders, raise bottom up. Hierarchies in network architectures are natural and dynamic heterarchies. In fact this is the only way that there can be leaders in democratic systems.
One algorithm tracks the value of contributions; the other tracks the value of contributors.
The Web 2.0 gave the audience a voice. What is happening at the moment is much more radical. It is not about representation but gestures and responses leading to emergence and self-organization. It is not about the message or the media any more. It is more about the rules of responsiveness. In a simplified way, you can express those rules as positive and negative feedback moving the whole system towards a particular direction based on the behaviour of the participants.
The definition of what is quality and what is crap is a result of the responsive interaction. It is not groupthink however, because the ratings of people with high karma points weigh more than the assessments of the average members. The huge problem is that the majority viewpoints get amplified, while minority opinions get silenced.
This is why we need a new category to support quality. It is diversity.
Changing the algorithm to reward diversity of opinion means the emergence of a system that looks totally different. Instead of highlighting posts with high average ratings, the system could highlight posts that have triggered a high divergence of ratings. There are many +5 responses, but also many -5 responses. The posts that inspire strong responses either way, both positive and negative, could then rise to higher visibility. The system can thus reward controversial voices, not only popular ones.
A viable system needs to reward perspectives that deviate from the mainstream.
We need perspectives that don’t aim to please everyone. The oddballs would still be marginalized but the thoughtful minorities who attract both admirers and critics would have a visible place in the ongoing process of creating the future in responsive collaboration.
Thank you Steven Johnson
The Google lesson for management
February 13, 2010
Eugene Garfield founded the Institute for Scientific Information in 1960. His pioneering work was in citation indexing. This allows a researcher to identify which articles have been cited most frequently and who has cited them. Garfield’s studies demonstrated that the number of citable items, i.e. the number of papers, together with the frequency of their citation, meaning how many scientists link to the paper, is a good measure of scientific success. Nobel laureates write more papers than other scientists and these papers are more linked to than other papers. The system effectively measures quantity and quality at the same time.
Links on the Web are also citations, or votes, as the founders of Google realized. The whole Web is a densely interconnected network of references. It is no different to the age-old practice of academic publishing and citation indexing.
The observation of Larry Page and Sergey Brin that links are citations seems commonplace today, but it was a breakthrough at the time Google started on September 7, 1998.
What Google did was essentially the same as had been done in academic publishing by Eugene Garfield. At this time, relevance and importance were measured through counting the number of other sites linking to a Web site, as well as the number of sites linking to those sites. The PageRank algorithm includes other variables as well, but the measurement of links is still the core functionality of the system.
What Google has proved to managers is that people’s individual actions, if those actions are performed in a transparent way, and if those actions can be linked, are capable of managing unmanageable tasks.
Collaboration and collective work are best expressed through transparency and emergent, responsive linking. The mainstream business approach to value creation is still a predictive process designed and controlled by the expert/manager. This is based on the presuppositions that we know (1) all the linkages that are needed beforehand, and (2) what the right sequential order in linking and acting is. Neither of these beliefs is correct any more. The variables of creative work have increased beyond systemic models of process design.
It is time to learn from the Web.
By relying on the uncoordinated actions of millions of people instead of experts/managers to classify content on the net, Google democratized scientific citation indexing. To be able to manage the increasingly complex organizations of today, the same kind of democratization needs to take place in the corporate world. Companies are transforming themselves from industrial mass production to creating value in wide area networks of mass communication. The transparency of tasks is the corporate equivalent of publishing academic articles. Responsive linking, rather than predictive linking, acts as a measure of relevance and is the guarantee of quality. This has served the academic community well. It made Sergey Brin and Larry Page billionaires. Now is the time to do the same in the corporate world. Complex, creative, knowledge-based work requires new approaches. The Google lesson for management is, that the more work is based on responsive processes of relating and the more organizing is an ongoing process in time, the more value we create!
Thank you Jeff Howe and Ralph Stacey
On the importance of the Tweet
February 12, 2010
Eli Whitney invented the cotton gin to replace the laborious hand cleaning of cotton in 1794. James Watt invented the steam engine in 1769 to solve the problem of pumping water out of British coal mines. Most inventions however, are not responses to voiced needs. In many cases the work of the inventors produce a solution that needs to seek a problem.This is still the case today. Inventions in search of a use are the norm when it comes to most technological breakthroughs. When Thomas Edison built his first phonograph in 1877, he suggested ten uses to which his invention would be suited. At the top of the list were preserving the last words of dying people and announcing the time of the day.
Music was not on his first list of uses. As historians write, It took twenty years for Edison to reluctantly admit that the main use of his phonograph was to record and play music.
It is almost impossible to know beforehand where the primary use for an invention is going to be in the long run. The inventor has in many cases, been totally wrong in his early assessments of where the best combination of a solution to a problem might be. Although James Watt had originally put his steam engine to work in the coalmines, the true revolution of steam power began only after steam had started to be used to propel trains and ships, which he never thought of.
James Watt did not see the future but he saw the past. Researchers claim that Watt actually got the idea for his version of the steam engine while repairing an engine designed by Thomas Newcomen, who had invented it almost sixty years earlier. Over one hundred of these had already been manufactured. Newcomen’s engine was based in turn on the patent awarded to Thomas Savary in 1689. The chain of discovery of the steam engine goes back further to Denis Papin in France, Christian Huygens in Holland and others. Similar histories can be seen in all modern inventions that are well documented.
There are very few isolated geniuses. But there are many bright people who have continued and improved the work of others. There is a need for a new vocabulary for the creative era: all capable people have capable predecessors, who should get the credit they deserve. The key concept in the knowledge-based future is acknowledgment, giving credit, beyond what we have been used to. In a sense, creative people are more remixers of other peoples’ ideas, than inventors. Technology and development are not isolated acts by great independent thinkers, but a complex storyline, where the storytellers, the developers and remixers, are more important than the heroic inventors, if there ever were any. We never know how the story develops, but it cannot develop unless it continues. The new challenge for the creative economy is to understand the importance of attribution and giving credit. The first thing is to acknowledge the vital role of the curator/messenger and the huge importance of the tweet and the retweet.
Thank you @euan @oscarberg @venessamiemis @Lessig and Jared Diamond
We share feelings much more than we share information
February 10, 2010
There is one universally agreed-upon feature of a good life: enriching relationships. Researchers claim that we take stock of the people in our lives and the “flourishing” we get through being with them. The strategy people normally follow, mostly unconsciously though, is to try to spend more time with the people we resonate with, and less time with the people we don’t resonate with that well. Beyond this obvious solution, an even better possibility would be to create, and re-create, our relationships to make them more mutually nourishing. Emotional contagion is a fact of life. It means that our moods and even physical health are created in interaction with other people. We tilt either to the positive or tilt to the negative as a result of our relations, and the further relations, the people that we relate with have. It is a chain of contagion that goes far beyond the horizon.
We could, in theory, make an inventory that evaluates the “richness” of our relationships. My dear friend Marcial Losada has made breakthrough findings on interaction. The thought provoking model he has created, which is based on decades of research, has three variables and three parameters. The variables are inquiry-advocacy, positivity-negativity, and other-self or external-internal orientation. The three parameters are connectivity, which is the critical control parameter, negativity bias and resistance to change.
According to Marcial, people are most successful when they are well connected, and are able to balance external vs. internal orientation as well as inquiry and advocacy. The relationship should keep a positivity/negativity ratio within the “Losada Zone”, meaning greater than or equal to about 3:1 and not more than about 11:1.
John Gottman on the other hand, has found that in a happy marriage, a couple experience five times more positivity than negativity in interaction. If we take the work of Losada and Gottman seriously, as we should, it would mean that there is a golden mean for any ongoing relationship in our lives, both private and corporate. If the positivity/negativity ratio is below 3:1 it would mean that there is a need for urgent mending. In situations like this, the way we intuitively behave is to end the relationship. But perhaps we should not. Do we know how WE affect the lives of the people close to us? How do WE impact on others? Do we help others to flourish? If not, should they leave us?
The critical success factor of Enterprise 2.0, is to understand that we share feelings much more than we share information.
The unfortunate reality in enterprises is that there is a negativity bias in most in-house communication. Communication is often about solving problems and giving negative feed-back. Organizations are also optimized for repetition. There is an in built systemic resistance to changing communication patterns. It is very safe to assume to start with, that the positivity/negativity ratio is in the red. Thus, the most important corporate process today is enriching interaction and the most important management process is enriching the interaction.
Thank you @pekkahimanen and @ Esa Saarinen for meaningful discussions
Complexity and uncertainty
February 9, 2010
Our lives are increasingly complex, whether we consider our private lives, our families, or the organizations we relate to. It is impossible to know for sure what will happen when we make changes in our lives. Whenever we make a decision or take some action, there will be consequences. These consequences are extremely seldom under our control, although we would like to think this is not so.
One of the most common practices in management is planning. Yet organizational reality often turns out to be different from the plans that are made. Unpredictability is a property of all complex, nonlinear interaction. As this corresponds with all human interaction, organizations could well be characterized by intrinsic unpredictability that cannot be removed.
And if that is the case, then it is perfectly understandable that our plans are never materialized exactly as we thought. Traditional management science has however tried to build on certainty through a strong belief in rationality and the capability for optimization.
Empirical evidence is making it very clear that this is not so, pointing to the conclusion that we can never know anything with certainty. Nonlinear interaction always yields unpredictable change. If we wanted to create an alternative to mainstream economic theory and leadership/management, it should then be based on “bounded rationality”, uncertainty and complexity.
When encountering a problem, or developmental challenge, we often ask the question: “What should we do?” But if plans seldom produce what is planned, creating a new plan, to substitute for the one that did not produce what was planned, might not be the cleverest thing to do. One of the things that people get asked to do in management development programmes is to identify the three new behaviors that they are going to adopt on Monday morning. If we really want to change things, we should instead ask the question: “What is it that we are doing here, now?”
Thank you Ralph Stacey, Doug Griffin, Herbert Simon and Henry Mintzberg
Complexity and the importance of links
February 4, 2010
The structures of the brain and the Internet look the same. In the brain there are neurons that link as a result of being active at the same time. This firing together creates a connection, “a wiring together“, that increases the strength of their connection. On the Internet there are servers and people that are linked in temporal interaction, sometimes as a result of being inspired and interested in the same topic, “firing together”. This short-term communication sometimes leads to a relationship increasing the strength of the connection. No neuron links with all the other neurons at the same time. No server links with all the servers at the same time, and no one interacts with all the other people at the same time. So all interaction is always local, whether in the brain, in an organization, or on the Internet. However, local here does not mean spatially local. The nodes in local interaction can be physically located in different parts of the world.
We often think of individuals as independent and self-contained. The view suggested here sees individuals as nodes of the complex networks they form when interacting with others, co-creating themselves and the reality in which they participate.
A complex system consists of a large number of agents/nodes behaving according to their own principles of local, self-organizing interaction. No one agent, or, a group of agents determines how the system as a whole behaves. Self-organization here means the agents interacting locally, following their own principles, rules and intentions, without any steering from outside that interaction. All influence takes place in the local interaction. No one agent in the brain or on the Internet, or in an organization, can be in control of the whole system and how it develops, as it develops as a global pattern.
There is control and there is development, all the time. Both control and development are emergent phenomena of local interaction. The interaction itself constrains and enables the people in the interaction. People cannot just do whatever they want in a relationship. Relationships create stability just because relationships always impose constraints. Relationships that are based on diversity and difference may enable development to take place without a plan for development. There cannot be novelty if people in a relationship are alike. Consensus leads to stagnation. What happens is a complex ongoing process of people relating to each other. This places links, or relationships, at the center of understanding life in organizations. The number of nodes comes third, if even that. The second most important thing is the diversity/quality of the nodes. The most important things are the links; the process of linking: wiring together as a result of firing together, in the brain, on the Internet, or in an organization.
One of the biggest promises of Internet-based work is the way it redefines local interaction, as Doug Griffin puts it. Global participation is possible, beyond anything we have experienced before. Mass production is giving away to short-term mass participation based on mass communication.
The human brain has more than 100 billion neurons. There are around 1.8 billion Internet users at the moment. So we are still far away from the potential of the brain when it comes to possible link combinations of local firing together. But it is high time to visit our beliefs. There can be control without somebody controlling. There can be development without a development goal and a plan as to how to reach the goal on a global level. This is how the brain works. And this is how we work!
Let’s fire together!
Thanks @venessamiemis for being the inspiration for this post. Thank you Doug Griffin for thinking together with me
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The agile organization
January 14, 2010
The management approach to getting something done is to create an organization. If something new and different needs to be done, a new and different kind of organizational form needs to be put into effect. Changing the lines of accountability and reporting is the epitome of change in firms. When a new manager enters the picture, the organizational outline is very often changed into a “new” organization. But does changing the organization really change what is done? Does the change actually change anything?
An organization is metaphorically a picture of walls defining who is inside and who is outside a particular box. Who is included and who is excluded. Who we are and who they are. This way of thinking was fine in repetitive work where it was relatively easy to define what needed to be done and by whom as a definition of the quantity of labour and quality of capabilities. As a result, communication design created two things: the process chart and reporting lines.
In creative, knowledge based work it is increasingly difficult to know the best mix of capabilities and tasks in advance. In many firms reporting routines are the least important part of communication. Much more flexibility than the process maps allow is needed. Interdependence between peers involves, almost by default, crossing boundaries. The walls seem to be in the wrong position or in the way making work harder to do. What then is the use of the organizational theatre when it is literally impossible to define the “organization” before we actually do something?
What if the organization really should be an ongoing process of emergent self-organizing? Instead of thinking about the organization let’s think about organizing. If we take this view we don’t think about walls but we think about what we do and how groups are formed around what is actually going on or what should be going on. The role of management is then to define tasks and outcomes but not to say who does what. The new task for managers is to make possible a very easy and very fast emergent formation of groups and to make it as easy as possible for the best contributions from the whole network to find the applicable tasks, without knowing beforehand who knows.
The focal point in organizing is not the organizational entity one belongs to, or the manager one reports to, but the reason that brings people together. What activities and tasks unite us? What is the cause for interdependence and group formation? My friend Jyri Engeström calls this a social object. My understanding of “social object” as an idea is more derived from the work of George Herbert Mead and my friend and mentor Doug Griffin. Because of this different background, a social object, in my vocabulary, is more often called a context or even an attractor. Although the word attractor has a different and very specific meaning in the sciences of complexity, I like the picture of an organization without walls, rather like magnetic fields defined by gradually fading rings of attraction.
These contexts create transparent, permeable boundaries between them, not walls. Instead of the topology or organizational boxes that are often the visual representation of work, the architecture of work is a live social graph of interdependence and accountability. Our thinking about organizations is very much based on the old expensive and low-quality communication. The reality today is very different. Communication as the key driver in organizing is both high-quality and cheap. One of the biggest promises of social media is easy and efficient group formation! It is just our thinking that is in the way of bringing down the walls.
Mobile phones, high definition and complexity
January 10, 2010
The future for mobile phone companies and telecoms industries lies in leveraging HD-audio and HD-video as the new primary media for knowledge work. The implementation of high-definition voice and high-definition video utilizing mobile broadband and mobile handsets is going to make the mobile phone a useful alternative in contexts that presently require getting together in a meeting room. I believe that voice and video derivatives for many to many communication are going to be the main ingredients of the office suites of tomorrow. The computing power of a modern high-end mobile phone makes it a viable alternative to a laptop as the primary tool of a knowledge worker. A mobile phones is no longer a phone. It’s now a mobile, internet-enabled device that also (occasionally) works as a phone.
There is a change going on at the moment from document centric thinking to communications centric thinking. It is only one of the results of the newer findings derived from the sciences of complexity. Organizations are about complex, wide-area interactions. The scientific modeling of these interactions demonstrates the possibility that efficient local communication between large numbers of people, with each participant responding to others on the basis of her own local goals and organizing principles, can produce coherent patterns on the global, organizational level.
The process of richly connected interaction has the capacity to produce coherence in itself, without organization-level goals and process maps. This suggests that high-quality interaction is sufficient to create coherent actions and development. The approach sees the organization as a process of ongoing organizing and construction of the future with the potential for both continuity and transformation at the same time. More interaction and more divergent and richer local interaction increase the potential for novelty just as repetitive, narrow communication keeps people stuck.
The criticism of mediated interaction has been based on the fact that people communicate with each other not only with words, but through a conversation of gestures: movement, tone of voice and visual representation. This can be achieved through HD-video utilizing mobile devices in a much more efficient and faster manner than through high transaction cost office practices and document-centricity. The knowledge-based organization is a responsive, temporal process of iterations in continuous cycles of interaction. To enable this, IT today should not stand for information technologies but interaction technologies.
All conversations involve more than information; communication is full of feelings. When we communicate we share feelings much more than we share information. With the new HD and mobile approaches to communication these feelings can be as alive in mediated communication as in face-to-face interaction.
