(P2): Weak Signals as Weak Constraints

Drawn picture of black slaves fighting off white slavers trying to recapture them.

  • I think frugality drives innovation, just like other constraints do. One of the only ways to get out of a tight box is to invent your way out.
    -Jeff Bezos
  • The more constraints one imposes, the more one frees one’s self. And the arbitrariness of the constraint serves only to obtain precision of execution.
    -Igor Stravinsky 
  • Problems are hidden opportunities, and constraints can actually boost creativity.
    Martin Villeneuve

So, how do we use weak signals as a basis for changing Complex Adaptive Systems (CAS)? We must look carefully at the weak signal to understand how or if this signal represents a weak constraint, and what the constraint means to the Target CAS.

Earlier I pointed out that weak links buffer the wildness of CAS. This buffering is a form of constraint, and that’s why buffering works. The buffer acts a bit like the banks on a river, constraining the flow of the river without dictating the movement of individual water molecules.

Our usual understanding of system constraints mimics the beliefs of the homeless community and uber-rich communities. Constraints are barriers to the safety or freedom of these communities, and so they are eliminated. Successful elimination of such weak constraints makes those social communities brittle and hyper-responsive to small disturbances.

The image above is a drawing of the effect of the Underground Railroad during and around the Civil War. The Underground Railroad functioned as a weak constraint on the Southern Slave System It was largely ignored when it was small but was attacked (ineffectively) when it expanded and began to operate as a sign of the weakness of that Southern Slave System.

The Underground Railroad was more than a simple barrier. It actively forced the Southern Slave System to respond to it. In the same way, weak constraints do more than provide simple barriers to the system of which they are a part.

Target systems for our advocacy have many weak constraints that are a normal expected part of their day-to-day experience. They are usually ignored or tolerated because the behavior of the weak constraint is a small local cycle that doesn’t threaten the larger system’s normal behaviors. If the weak constraint begins to expand its impact on the larger system, it will trigger a response of some kind from the larger CAS.

In Part Three, I’ll talk more clearly about how we use weak constraints (and sometimes strong constraints) to produce advocated change in CAS.

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(P2): Activism as Bricolage

Theatre showing Tosca with a phrase projected onto the screen curtain, 'Power is always temporary'

Bricolage is rightly viewed as one of the “Powers of the Weak”. Elites typically view power as something exerted by a predictable machine of propaganda, sanctions, and punishments, and they view insurgents trying to change this as working to replace their machine of power with some other one.

So, bricolage, used as a tool of subversion, misdirection, or organizing, is hard for elites to see, or target. This is especially true if the bricolage is used to solve a local problem.

The point of using bricolage rather than using the system is to avoid having the problem-solving bricolage subjected to the services logic of the system.  This system services logic includes assumptions of:

  • Spending scarce resources to detect fraud
  • Using “failure demand” as a tool for managing system work rather than actually providing the service
  • After an initial period of seeking out persons eligible for the support, gradually turning the point of the system increasingly toward denial of supports.
  • Etc.

Bricolage allows a more coherent connection between support purpose and behavior. This coherence is lost once the support is subjected to the support logic of the system.

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(P2): Tinkering and Bricolage

A room full of various unexpected things for you to play with and make something new

Tinkering is standard behavior for anyone who is curious. Bricolage is a French word defining tinkering as finding a solution to a problem with whatever is in your immediate environment. Bricolage makes problem-solving local and personal and is more than just playing. Bricolage reliably produces solutions that are inexpensive, easier than managed solutions to implement, and well matched to the actual reality of the problem rather than the “planned” reality of the problem. In fact, in modern life, bricolage is a common response to solutions that are imposed by organized management.

I suspect bricolage was a primary way our hunter-gatherer ancestors engaged the problems of their daily lives. Adequate solutions would become part of a multi-generational exploration of what possibilities these solutions held, a kind of socially organized exaptive process. Bricolage speaks to the personal “engineering” drive we all have.

My father was an extremely capable chemical engineer who worked for Dow Chemical for 45 years. His primary focus over the course of his career was something called “process engineering”. His task was to take a reasonably successful research project and find out if the project had commercial potential. Researchers tend to think that you scale their successful research by simply making it a bigger version of what they used as their research methodology.

In reality, designing and building a commercial pilot that is a million times larger than the research process, respecting the physical environment of seasonal temperature changes, the length of pipes, the delivery of chemical components at the right temperature and with the catalysts and pre-product components at the right time, so the next step in the process can be successfully initiated, and so on. Process Engineering is a particularly large form of bricolage, and the difference between ideology (research) and engineering (bricolage) has many lessons for any attempt to change any CAS.

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(P2): Environmental Scanning

Wildly diverse images of pollen types in black and white

Environmental scanning is not monitoring. It is a deliberate activity designed to increase the possibility of surprise. It assumes you already have a commitment to changing your current view of reality by exposing yourself to what you couldn’t anticipate.

So, having a rigid procedure for environmental scanning won’t work. Over time, you’ll find less and less novelty and more and more repetition. You need an approach that has enough noise in its scan to produce stuff you didn’t expect or even know might exist.

I use a variety of ways of accessing information, including ones that I am uncomfortable with, or frankly disagree with, in order to maximize the possibility of surprise. This approach requires scanning a lot of useless crap. But I’ve gotten faster and more accurate in my scanning for crap over the years, so I still get a fair amount of surprise. I also add and subtract sources regularly to maintain the surprise. I use the criterion that a particular source is no longer surprising to me.

Since anybody’s experience of surprise is conditioned by the personal path they have followed in all its eccentricity and uniqueness, a useful environmental scanning approach will be customized to that anybody.  The vagaries and dynamic of our personal purpose and meaning will also influence what we find surprising, and that will change over time as we change. Our ecosystem always includes ourselves.

The way that this kind of environmental scanning helps us detect weak signals is best understood as similar to a kind of process called stochastic resonance. Stochastic resonance happens when you add noise to a weak signal. That part of the noise that matches some part of the signal will boost the “volume” of the signal. That part that doesn’t match will cancel out through interaction with other parts of the noise.

We often try to remove noise if we are dealing with a weak signal because we believe that will make the signal clearer. So it is surprising to find out that noise can help us understand weak signals. This reality is an interesting metaphor/framework for interaction with any CAS.

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(P2): Surprise and Weak Signals

A goldfish with a look of surprise on the face.

  • Learning By Surprise
  • What is the Adjacent Possible?
  • The Hindsight Bias
  • “I wanted a perfect ending. Now I’ve learned, the hard way, that some poems don’t rhyme, and some stories don’t have a clear beginning, middle, and end. Life is about not knowing, having to change, taking the moment and making the best of it, without knowing what’s going to happen next. Delicious Ambiguity.”
    ― Gilda Radner

Instead of glossing over surprises as failures of understanding, we should focus on them until we have grasped their novelty and how that novelty needs to change our view of reality. We need to avoid abstracting from surprise to make it only another example of what we already know to be true.

Novel occurrences are novel for us, but they are also typically some “next step” from that with which we are already familiar. They are often called the “adjacent possible” because once they have occurred, it is fairly easy to see how they came about. This is true even if no one anticipates them. It is important to remember that in a Complex Adaptive System, there are always many adjacent possibilities for the future.

There is another common problem that results from rationalizing surprises. We look back on the surprise and try to figure out who accurately anticipated it. We think this will improve our prediction capability in the future.

Looking back does improve our understanding of the current situation. It doesn’t improve our ability to predict any genuinely novel future. If we examine what people thought about the future before the novel occurrence, we will see a very large number of ideas about what might happen.  The particular idea about the future that turned out to be accurate had no more or less information about its likelihood than many of the other ideas. The novelty tells us something useful about the current state of the CAS we are in and where it might evolve in the short term. It doesn’t improve our ability to foresee the genuinely new.

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(P2): Perceiving Weak Signals Overview

A woman with bruising injuries on her face from partner abuse, holding a sign that says 'Did you notice me?'

  • Great things are done by a series of small things brought together – Van Gogh
  • Even the largest avalanche is triggered by small things –Vernor Vinge
  • You’ve got to think about big things while you’re doing small things so that all the small things go in the right direction –Alvin Toffler
  • Men don’t pay attention to small things – Katherine Johnson

Because our usual habits make us ignore weak signals, we need to cultivate new habits that make it more likely we will notice them. These new habits can’t be automatic. They must involve reflective attention-not just attention to something that is there, but consideration of it’s meaning. Below is a list of techniques and concepts that I hope will aid you in seeing what is important, but almost not there:

  • Surprise Can Point to Weak Signals
  • Environmental Scanning for Weak Signals
  • Tinkering and Bricolage to find Weak Signals Right Around You
  • Learning About Weak Signals Through Safe-to-Fail Experiments
  • Thinking of Weak Signals as Insurgencies

I’ll try to amplify each of these in the posts below.

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(P2): So What Do We Do with Those Weak Signals

WhatToDoWithWeakSignals

First, we have to actually pay attention to them. Our default is to ignore them as unimportant. That means we have to have a way of making them stand out.  Most importantly, we have to conserve the meaning in the story of any weak signal instead of homogenizing that meaning or averaging it or abstracting it through ordinary statistical analysis. That is one of the strengths of SenseMaker. Its function is, first of all, to make raw weak signals stand out in a number of ways. We need to do the same.

Then, we have to ask ourselves about the value of the narratives we have acquired to support or undermine positive change. This isn’t simple to do. But our first order goal with these signals is to increase the ones that support positive change and decrease the ones that undermine it. Because these are weak signals, it is feasible for us to try out ways to do both of these in time frames that let us change our approach as we learn which weak signals we can effectively increase and decrease, and when we need to look at different initiatives to produce these outcomes.

The reason why this works at all in trying to change a CAS is that the cycle of experiment and evaluation is short. Such an approach respects the dispositional nature of CAS and doesn’t require us to use prediction and mechanical outcomes as the signs of progress.

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Part Two: Detecting and Using Weak Signals (Cynefin)

A Specimen Cynefin Diagram (not the newest, not the oldest).  Simple / Obvious: The simple/obvious domain represents the 'known knowns'. This means that there are rules in place (or best practice), the situation is stable, and the relationship between cause and effect is clear. Complicated: The complicated domain consists of the 'known unknowns'. The relationship between cause and effect requires analysis or expertise; there are a range of right answers. The framework recommends 'sense–analyze–respond': assess the facts, analyze, and apply the appropriate good operating practice. Complex: The complex domain represents the 'unknown unknowns'. Cause and effect can only be deduced in retrospect, and there are no right answers. 'Instructive patterns ... can emerge,' write Snowden and Boone, 'if the leader conducts experiments that are safe to fail.' Cynefin calls this process 'probe–sense–respond'. Chaotic: In the chaotic domain, cause and effect are unclear.[e] Events in this domain are 'too confusing to wait for a knowledge-based response'. managers 'act–sense–respond': act to establish order; sense where stability lies; respond to turn the chaotic into the complex. Disorder / Confusion: The dark disorder domain in the centre represents situations where there is no clarity about which of the other domains apply.

Cynefin is a body of knowledge and tools to assist in changing CAS, among other things. Cynefin, as an enterprise intervention, also has developed a “narrative access and analysis tool” called SenseMaker™. Sensemaker allows the intervenors to accurately access raw views by the participants as short narratives without groupthink or homogenization. It is this ability that allows for the detection of weak signals.

Because SenseMaker has developed an app, it is possible for its users to engage huge numbers of people in a very short time. The example that had the most impact on my understanding of its capacities was an effort to work around the unwillingness of local citizens to say what they actually thought to US civil and military personnel in SE Asia.

The system was used to ask children to relate a story from their grandparents about the most important lesson that the grandparents had learned in their lives. Then the children sent the stories using the SenseMaker app. This project got 50,000 stories in four days.  There is simply nothing else that supports authentic narrative by real participants with the speed of SenseMaker.

Unfortunately for our community, SenseMaker is an enterprise tool and is priced that way. I have been exploring ways we might be able to use this system in our community, but I am some distance from a genuine solution.

That doesn’t mean that we can’t make use of the idea if we can come up with ways to assure fidelity to SenseMaker’s ability to easily access real raw narratives from participants.

I’ll discuss some ideas for using this general framework to get meaningful narratives in our community in later posts. For now, I hope you can see the importance of weak signals in the development and use of our FutureStrategy.

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(P1): Why Are Weak Signals Ignored?

A slide: Weak Signals Detection with Social media-No surprise at all? Theory: In contemporary future studies the term weak signals refers to an observed anomaly in the known path or transformation that surprises us somehow. (Kuosa, 2014 p, 22) Our Experiences; Are We Alone? Possible Explanations:  #1 Noisy social media and other limits #2 Filters #3 Customers are Experts #4 Epistemological Limits

Most of the ways we have of finding signals in CAS make us ignore the weak signals.

Surveys, focus groups, social media scans, and almost all the paraphernalia of social studies research homogenize signals to allow the “provable” detection of the Big Signals, the ones that represent larger trends in the CAS. And statistics, as it is usually used in these studies, is designed to relegate weak signals (at best) to a distant periphery where it can be ignored.  Think about what you were taught about the bell-shaped curve, and what you believe is meaningful about the data.

This approach to detecting signals is a framework that our social and profit-driven CAS imposes on us as the meaning of “worthwhile pursuit”.  Weak signals are seen as useless in this framework and, thus, meaningless.

To find weak signals, we have to access the raw narrative that the signal creates once it comes into existence. We have to deliberately prevent the homogenization and loss of the weak signal through our usual methods of assigning meaning to the information. We have to learn to pay attention to the small, weak, and powerless.

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(P1): Weak Signals

A network diagram with a large hub (strong links) and many smaller hubs (weak links)

One way to think about weak signals is through network modeling.

It is intuitive to view strong links in a network as the important ones and the weak links as unnecessary details or random defects in the network that don’t contribute to the purpose or function of the network. But in complex adaptive systems, strong links generate volatile unpredictable behavior. Weak links buffer the volatility of the activity of these strong links and are largely responsible for the stability of the network, even as the CAS goes about its merry way.

Interestingly, there are two communities that deliberately eliminate weak links from their social lives:

  • People who are homeless and desperate, I suppose because they believe that persons they don’t know very well are persons they can’t trust.
  • Very rich people, I suppose because they believe that those who aren’t their peers can’t be trusted and are after their money.

Both of these communities are largely right in their loss of trust for weak links, which says something about their location in the current CAS and their personal futures in the CAS.

Note that authoritarian regimes and cults both eliminate weak links in the belief that their survival only depends on the strong links that produce (in their view) their power and wealth. These kinds of “strong” CAS are notoriously volatile and readily suffer collapse if any insurgency can disturb the control.

This framework maps to the basic CAS change concept that powerful system trends are very difficult to control for positive change (even if they might support our change). The best opportunity for change lies in the weak links, because they are small now, but can grow to have much greater influence.

But identifying the weak links that might be the best support for CAS change efforts remains difficult because those links aren’t poking us in the face.

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