Author Archives: Harish

The Form of Batesonian Abduction:

In today’s post, I am looking at Batesonian abduction through the lens of George Spencer Brown’s Laws of Form (LoF). I have written about LoF here, here and here. Spencer Brown came up with an elegant algebra mechanism to capture the thinking process using a notation called as “mark”. I welcome the reader to explore the ideas in the links given above.

Laws of Form (LoF):

I will go through the basic calculations and notations needed for this post. I am going to use parentheses to capture the notion of the mark. For example, the distinction of an idea ‘A’ can be notated as:

(A)

The first principle in LoF is the Law of Condensation. This basically means that when an idea is repeated, it condensates into the original idea itself. For example, if I make a distinction of an apple, and I repeat the distinction again, I have not added anything new if the two concepts are identical to each other. The original concept remains the same.  This is shown below:

(Apple) (Apple) → (Apple)

However, distinct ideas maintain their separation.

(Apple) (Orange) → (Apple) (Orange)

Through contrast and comparison of different ideas, we can achieve deeper understanding. This is shown below where we gain a better understanding of fruits in terms of Apples and Oranges:

(Fruits ((Apple) (Orange)))

Abduction:

With the basic notations of LoF out of the way, let us look at abduction. Abduction is a reasoning process introduced by Charles S. Peirce. It is a way of coming up with hypotheses to explain surprising or puzzling observations. It is different from induction (generalizing from observations) and deduction (deriving conclusions from general principles).

Peirce saw abduction as important in the context of discovery, the stage in science where new theories or ideas are generated. The modern notion of abduction has become more focused. Modern views of abduction often focus on finding the “best” explanation for a given observation. Peirce did not emphasize choosing the best hypothesis among many possibilities. He was more focused on generating hypotheses that could later be tested and refined. Peirce thought that while the hypothesis might be influenced by existing knowledge, abduction is still important because it leads you to consider new possibilities you have not fully explored yet.

For example, if a scientist notices that certain plants grow better near a specific type of soil, they might abduce the hypothesis that certain nutrients in the soil are helpful for growth. This hypothesis can later be tested through experiments and predictions.

Batesonian Abduction:

Gregory Bateson, the renowned anthropologist and cybernetician, developed a more nuanced interpretation of abduction. His approach emphasized understanding relationship patterns rather than linear cause-and-effect explanations. Bateson positioned abduction within the broader context of pattern recognition in networks, viewing it as a cognitive process for interpreting systemic patterns.

For Bateson, abduction was about seeing how different elements in a system relate to each other in a non-linear way. Instead of finding a single cause, Bateson was interested in contexts and feedback loops — how an element can be part of a larger dynamic pattern or system. Bateson, while acknowledging abduction as a method of forming hypotheses, placed it more broadly within the context of pattern recognition in networks. He saw abduction not just as a logical operation but as a cognitive process that helps us interpret and make sense of patterns in the world. For Bateson, abduction was related to the way humans and animals perceive and respond to relationships between elements in a ‘system’, not simply in relation to surprising observations or hypotheses.

Bateson asked in Mind and Nature:

What pattern connects the crab to the lobster and the orchid to the primrose and all the four of them to me? And me to you? And all the six of us to the amoeba in one direction and to the backward schizophrenic in another?… What is the pattern which connects all the living creatures?

His central thesis proposed that the connecting pattern is itself a metapattern—a pattern of patterns that defines the broader generalization of connectivity through patterns.

Bateson explained his take on abduction as:

Every abduction may be seen as a double or multiple description of some object or event or sequence.

The idea of double or multiple descriptions is very profound. In simple words, it is better to have multiple perspectives of a situation to have a better understanding of the situation. This represents a pluralistic framework. A simple example is the binocular vision we have. Each eye captures a slightly different image because they are located on opposite sides of the face. The brain combines these two images to create a single, three-dimensional perception of the world. Using our LoF notation, this can be described as follows:

(3-dimensional perception of the world ((Left eye image) (Right eye image)))

In terms of abduction, the brain “abductively” connects these two different descriptions (the views from each eye) to create a unified perception. The brain interprets the difference between the two flat images to infer depth – how far away objects are. This is similar to how abduction works by generating an explanation (in this case, the perception of depth) based on two related but distinct pieces of information (the two images).

The pluralistic aspect is the most important idea that I want to bring to the readers. In order to improve our understanding of a situation in complexity science or systems thinking or thinking in general, we should have epistemic humility and welcome different perspectives. Bateson also defined information as the difference that makes the difference. If the two descriptions are identical, we do not generate a new understanding. This would be very similar to being in an echo chamber. Now, this does not of course mean that you need to welcome ideas that are demonstrably absurd. The gist is that you need to be open to other perspectives and take a pluralistic approach.

Final Words:
The etymology of “abduction” means to lead away. It suggests leading away from our current knowledge to new explanations. It represents a movement away from what we already know. It is about being led away to new understanding.

A profound connection from Bateson’s Double Description suggests that real learning is not about accumulating single descriptions, but about developing the ability to see patterns across contexts. Using LoF helps us see why – the form (pattern((A)(B))) shows how understanding emerges from relationship rather than from things themselves. The Metapattern structure suggests that what we are really doing in double description is learning to recognize “patterns that connect” – metapatterns. This is why Bateson saw it as crucial for understanding complex situations like ecosystems or minds.

The LoF notation reveals something profound about abduction itself – it’s not just inference, but a leap to a new logical type. When we write (pattern ((A )(B))), we’re showing how abduction creates new knowledge by seeing across levels.

The use of LoF notation perhaps gives us a new way to look at things. I will finish with another example of improving our understanding utilizing a pluralistic approach. The paper, An update on Inuit perceptions of their changing environment, Qikiqtaaluk (Baffin Island, Nunavut) by Sansoulet, Therrien et al, offers an example of a pluralistic approach to understanding climate change, as it incorporates indigenous knowledge and perspectives alongside scientific observations. A LoF notation might be:

(climate-understanding ((scientific-models) (indigenous-knowledge) (economic-analysis)))

There are several examples in the paper that talks to the changes that the Inuit have seen as part of climate change. With respect to Inuit perceptions on climate change, including weather, climate impacts on the ice, and invasive/disappearing species, Inuit report the change in the ice as the main and most widespread change to have occurred in the last decades, with adaptation to this change being increasingly difficult and unsafe for hunters.

This integration of different ways of knowing exemplifies Bateson’s vision of abduction as a tool for understanding complex systems. It shows how the marriage of traditional knowledge and scientific observation can lead to richer, more nuanced understanding – exactly the kind of “difference that makes a difference” that Bateson emphasized. Through this lens, we see that addressing complex challenges like climate change requires not just multiple sources of data, but the ability to recognize and connect patterns across different domains of knowledge.

The application of Batesonian abduction and LoF notation thus offers not just a theoretical framework, but a practical approach to understanding and addressing complex challenges in our interconnected world. It reminds us that a nuanced and better understanding emerges from our ability to recognize and integrate the patterns that connect diverse ways of knowing.

Always Keep on Learning…

On the Presence of Complexity:

In today’s post, I am following up on the theme of complexity by drawing upon ideas from Derrida to further explore these concepts. I will start with a fundamental question regarding the basic premise- Is complexity an inherent property of a situation, independent of the observer, or does it emerge through observation and purpose? In other words, is complexity a given phenomenon in the external world or is it constructed?

This question might seem strange to some, while straightforward to others. Some might argue that this leads us down the path of solipsism, while others might contend that this approach is superior as it pushes us away from naive realism. In this article, we will examine the perspective where complexity manifests as an observer-dependent phenomenon, shaped by intention, purpose, and the limitations of presence. Through Derrida’s philosophical framework, we will explore how complexity emerges not as an absolute property, but as a relational phenomenon tied to observer intention and capability.

When we discuss observer-independent properties, we generally refer to physical properties of a situation that are ‘objective’. Consider the example of a termite hill. The material composition, number of tunnels, number of intersections, and other dimensional properties are indeed independent of the observer. However, I would posit that complexity is fundamentally different, and this difference can be demonstrated through three levels of analysis.

First, at the ontological level, complexity emerges as a second-order property. While first-order properties like mass, dimension, or quantity exist independently, complexity arises from the relationships between these properties. These relationships do not exist in isolation but are perceived and constructed through an observer’s cognitive framework. For instance, in our termite hill example, the mere presence of multiple tunnels does not inherently create complexity – it is the observer’s attempt to understand their interconnections, purpose, and evolutionary significance that generates the perception of complexity.

Second, at the epistemological level, complexity manifests through the limitations and capabilities of the observer. Consider two observers of the same termite hill: an entomologist and a child. The entomologist might find the structure’s organization relatively straightforward due to their understanding of termite behavior and construction patterns. The child, lacking this specialized knowledge, might perceive the same structure as overwhelmingly complex. This demonstrates that complexity is not merely about what is being observed, but about the relationship between the observer’s knowledge framework and the observed phenomenon.

Third, at the teleological level, complexity emerges through purpose and intention. When we declare something as ‘complex’, we are not making a purely objective observation. Instead, this declaration typically arises from a specific purpose or intention. This may be tied to the need to manage a situation, the desire to understand a situation, the need to solve a problem or the obligation to make decisions.

This three-tiered analysis demonstrates that the concept of complexity makes most sense when an observer is involved. As Derrida notes in “Of Grammatology” [1]– There is no outside-text. Similarly, there is no complexity outside of our purposeful engagement with situations. The very act of identifying complexity is embedded in our intentions and purposes. Complexity ’emerges’ when we try to understand something, manage something, or achieve something. It is inextricably tied to our purposes and capabilities.

The next point to consider is how différance structures our understanding of complexity. When we identify something as complex, we explain it through emergence. This emergence is further explained through various properties, which in turn point to relationships that lead us back to emergence and complexity. This pattern mirrors Derrida’s différance, where meaning is constantly deferred through a chain of references.

As he notes in “Structure, Sign, and Play in the Discourse of the Human Sciences” [2]:

The center is not the center… the concept of centered structure is in fact the concept of a freeplay based on a fundamental ground, a freeplay constituted upon a fundamental immobility and a reassuring certitude, which is itself beyond the reach of the freeplay.

In his deconstructionist approach, Derrida critiqued the traditional metaphysical idea that meaning or reality is grounded in an immediate, fully present essence—something that can be directly perceived and understood without ambiguity. This notion of “presence” suggests that there is a fundamental truth or meaning that is self-evident and immediately accessible to the mind. However, Derrida challenges this assumption, arguing that meaning is never fully present or directly available. Complexity, in this view, is never completely “present.” It is always understood in relation to other concepts, each of which itself requires further explanation and definition. In this way, complexity can never be reduced to a simple, fixed presence; instead, it is always deferred, dependent on the play of differences and relationships between terms.

Derrida’s concept of différance provides crucial insights into how complexity ‘operates’. In “Margins of Philosophy” [3], he writes:

Différance is what makes the movement of signification possible only if each so-called ‘present’ element… is related to something other than itself, thereby keeping within itself the mark of its past element and already letting itself be vitiated by the mark of its relation to the future element.

Complexity is never purely present. It carries traces of past experiences, and it points toward future implications. In this perspective, complexity exists in a network of relationships. The concept of trace is particularly relevant to understanding complexity. In “Of Grammatology” [1], Derrida explains:

The presence-absence of the trace… carries in itself the problems of the letter and the spirit, of body and soul, and of all the problems whose primary affinity I have recalled.

This suggests that complexity is both present (in our observation) and absent (in its continual deferral). Complexity carries within itself marks of our purposes and intentions. It also contains traces of our past experiences and future expectations. This leads us to a nuanced understanding of complexity as a perspective of possibilities. This is further illuminated by Derrida’s critique of ‘presence’ in “Speech and Phenomena” [4]:

The presence of the perceived present can appear as such only inasmuch as it is continuously compounded with a nonpresence and nonperception, with primary memory and expectation.

Derrida explores the idea that our perception of the present moment is inherently tied to our understanding of time, memory, and anticipation. In other words, we cannot fully experience or recognize the “present” unless it is continuously linked to what is not present—our memory of the past and our expectations for the future. This further supports the view of complexity as being grounded in our capabilities and shaped by our purposes. It is influenced by our past experiences and directed toward future actions.

Final Thoughts

Much like Berkeley’s question of whether a tree falling in the forest will make a sound if there is no one to hear it, I propose that complexity requires an observer. Complexity measures are always knowledge and purpose-relative. This means that different purposes yield different complexities. What is complex to one observer may be merely complicated to another. No absolute measure can exist independent of purpose. Consider the example of a pandemic: there may be objective properties such as transmission rate, virus size, and type, but the notion of complexity makes sense only within the network of relationships, purposes, and meanings. Here, complexity emerges through various needs such as public health management, economic considerations, and social conditions.

As Derrida’s philosophy suggests, complexity exists not as a presence but as a network of relationships, purposes, and meanings. There is no ‘ground’ for complexity as a pure property independent of an observer. This view offers a more nuanced and practical approach to understanding and managing complex situations. This perspective changes how we approach complex challenges, suggesting that effective management requires understanding not just situations, but the purposes, capabilities, and contexts that make them complex in the first place.

Managing complexity within this framework requires understanding the specific purposes of the participants, their capabilities, contextual factors, and available resources. We should appreciate multiple perspectives and not fear provisional solutions. I invite readers to check out this post that goes deeper into Derrida’s deconstruction.

I will conclude with Derrida’s words:

There are things like reflecting pools, and images, an infinite reference from one to the other, but no longer a source, a spring. There is no longer any simple origin. For what is reflected it split in itself and not only as an addition to itself of its image. The reflection, the image, the double, splits what it doubles. The origin of the speculation becomes a difference. What can look at itself is not one; and the law of the addition of the origin to its representation, or the thing to its image, is that one plus one makes at least three.

(Simply put, the above passage suggests that representation or reflection always results in a gap because they are inherently split. This gap creates a difference between the original and its image. As a result, the traditional notion of a stable origin or source is undermined. Instead, meaning emerges through a play of differences. The idea that “one plus one makes at least three” indicates that when an origin is reflected or represented, a third element, the difference or gap between them, emerges. This reveals that neither the original nor its reflection is self-contained or stable.)

Always keep on learning…

[1] Of Grammatology, Derrida. 1967

[2] Structure, Sign, and Play in the Discourse of the Human Sciences, Derrida. 1970

[3] Margins of Philosophy, Derrida. 1972

[4] Speech and Phenomena, Derrida. 1967

The Patron Saint of Complexity:

In today’s post, I am looking at the notion of a patron saint of complexity. I have had the question posed to me – why I am a fan of Ludwig Wittgenstein? In fact, I think that today’s post might get some responses similar to how overrated Wittgenstein is. The answer is simple – I have come to see Wittgenstein as the patron saint of complexity. He stands as philosophy’s patron saint of complexity, reminding us that all systems are fundamentally human constructions. While the world simply is, it’s our minds that weave the intricate web of meanings and patterns we call complexity.

I am of the school that complexity is something that we, humans, attribute to the world around us. It is a form of perspective, a form of expression. As Heinz von Foerster, a distant relative of Wittgenstein and the Socrates of Cybernetics, said – the environment as we perceive it is our invention. Wittgenstein’s point is that our understanding of the world is something we construct socially, and it is unique to our ‘human’ understanding. He sought to use philosophy as a means of therapy to find our way around the world.

Complexity emerges not as an inherent property of a ‘system’ but through how an observer interacts with and frames it. Wittgenstein’s insights suggest that the ‘complexity’ of a situation depends on the observer’s language games and forms of life. This perspective aligns with several key ideas from his later work. I encourage the reader to explore these ideas here.

Language games emphasize that meaning arises from context and use within specific activities. Just as words mean different things in different contexts, a situation’s complexity depends on the framing and engagement of the observer. These meanings are tied to the practices and ‘forms of life’ of a community – our background, values, and experiences shape how we perceive and interpret complexity. Wittgenstein’s rejection of fixed structures supports the idea that ‘systems’, and therefore, complexity, are emergent and non-linear, defying reductionist interpretations. His shift to examining ordinary language and everyday practices focuses on the dynamics of interaction. There is no universal viewpoint – only perspectives grounded in specific contexts.

A Thought Experiment:
I invite the reader to engage in a thought experiment – Imagine a world without language. How would that impact the complexity around us?

Without language, much of our socially constructed complexity would disappear. ‘Systems’ like economics, politics, and science – built on linguistic frameworks – would dissolve, leaving only direct, lived experience. A ‘market’ as we understand it, with its web of transactions, expectations, and regulations, would reduce to immediate barter or interaction, lacking the social conceptual scaffolding of ‘value’ or ‘profit’.

Yet paradoxically, individual perception of complexity might increase because the interpretive burden would shift entirely to the individual. Every interaction or phenomenon would need to be understood in real-time, without the benefit of shared categories or explanations. Consider how a pre-linguistic human might experience a tree – they would see its shape, feel its bark, notice its movement in the wind, and understand functionally that it provides shelter and fruit. But they couldn’t categorize it within abstract concepts like ‘ecosystem’ or ‘life cycle’.

This suggests something interesting – Language does not just describe complexity, it also generates complexity. Through language, we create nested layers of abstraction, build shared conceptual frameworks, accumulate and transmit knowledge across generations.

Without language, the world would be both simpler and more ineffable – but not necessarily less complex. We wouldn’t experience this as “simplicity” because the very concept of “simple vs. complex” is itself a linguistic construct. Like a wolf in the forest, we would simply experience raw reality without the mediating layer of linguistic abstraction.

We can see that language is both a magnifier and a creator of complexity. It allows us to construct shared realities that vastly exceed the sum of our individual experiences. Without it, the world would likely feel simpler in its structure but more intricate in its immediacy. This reminds us that complexity is not just ‘out there’, but also deeply entangled with how we communicate and make sense of the world.

The world would continue in all its intricate interactions – weather patterns would still form, ecosystems would still function, quantum particles would still behave in their strange and mysterious ways. We just wouldn’t have the linguistic frameworks to model and discuss these phenomena. Perhaps this reveals our linguistic bias – the assumption that the world must be either ‘more complex’ or ‘more simple’. Without language, such distinctions wouldn’t exist. The world would just be.

I will finish with an apt quote from Wittgenstein:

The sense of the world must lie outside the world. In the world everything is as it is, and everything happens as it does happen: in it no value exists—and if it did exist, it would have no value.

Always Keep Learning…

The ‘Form’ of Complexity:

In today’s post, I am exploring complexity through the lens of George Spencer Brown’s “Laws of Form”. This philosophical and mathematical treatise explores the foundations of logic and mathematics via a unique symbolic system. Spencer Brown introduces a primary algebra based on a simple mark and the act of drawing a distinction. The mark itself is a fundamental concept that represents both the act of drawing a boundary and the boundary itself. I welcome the reader to explore the main concepts here and here.

Spencer Brown wrote the following in Laws of Form:

A universe comes into being when a space is severed or taken apart. The skin of a living organism cuts off an outside from an inside. So does the circumference of a circle in the plane. By tracing the way we represent such a severance, we can begin to reconstruct, with an accuracy and coverage that appear almost uncanny, the basic forms underlying linguistic, mathematical, physical, and biological science, and can begin to see how the familiar laws of our own experience follow inexorably from the original act of severance.

Imagine a blank sheet of paper, and now imagine drawing a line anywhere on it. Perhaps you drew a vertical line or a horizontal line. Perhaps you drew it near the left edge, or perhaps in the middle. No matter where the line was drawn, you have now created two sides that were not there before. Now select one side. The side you chose might be the left side, or perhaps the smallest of the two sides, or the largest. It could be on your dominant side or the one with a black speck on it. As you can see, there are numerous ways to define the distinction you just made. All this depends on the observer.

The form of the mark is shown below:

The side that you chose is the marked state, and the side that was not chosen is called the unmarked state. The line is called the distinction. The curious thing about the line is that it contains the marked state and yet is no part of the content itself. Consider the name of an object. The name is a word that refers to the object yet is not the object itself. Similar to a fence or a wall around a property, it marks the boundary while not being the property itself. The property is what is contained inside the boundary. It is neither part of the inside nor the outside. The boundary is what allows the observer to see the possibilities of the contained. The mark simultaneously separates and connects.

The reader might now be reminded of Gibson’s ‘affordances’. Affordances lie in the realm of the mark. They are not properties exclusive to the object or the subject. Affordances are action potentials identified by the subject or the person making the distinction. According to Gibson, affordances are opportunities for action that the environment offers to an organism, but these opportunities are defined in relation to the capabilities of the organism.

Let’s use the example of a door. The mark identifies action potentials such as the ability to provide an opening when the door handle is rotated, to hang a wreath on it, or to add a means to peek at the external world through the door. These action potentials are the various possibilities recognized by the observer. They are reliant on the observer’s previous interactions. This points to an important idea in Cybernetics called ‘variety’. Variety refers to the number of distinct states identified by an observer of a ‘system’ constructed by the observer. Variety is also used as a measure of complexity.

Spencer Brown said that the mark provides perfect continence. This means the mark perfectly contains what is inside without any leaks. It creates a boundary that separates the inside from the outside. From this perspective, what is inside the mark is internally coherent since it is perfectly contained by the mark. The observer can hold multiple distinctions within a mark. A door and a window are both framed openings for a building. The observer has distinguished between the two, yet they can be combined into a new grouping – framed openings for a building. A door is an internally coherent concept, as is a window. Both are internally coherent when taken as framed openings for a building. The concept of framed openings for a building is also an internally coherent concept.

In the example above, the reader can see the ‘nestedness’ of various marks. This brings up the next important idea. The boundaries are recursive. What is contained inside the boundary or the mark is self-contained and can contain further marks or be positioned inside a larger mark. We have been discussing the notion of internal coherence. Another way to look at it is through the idea of viability. The various marks drawn that contain and are contained inside larger marks should be viable. When an observer is drawing a boundary around a whole, the whole should be a viable entity. This is also the basis for Stafford Beer’s Viable System Model. VSM offers a framework to diagnose the viability of a given ‘system’. I welcome the reader to explore this further here.

The last concept I want to introduce is the ‘Markovian’ nature of complexity. We have seen that complexity refers to the action possibilities of a situation reliant on the observer and the distinctions made that are internally coherent. The various distinctions go together, yielding new possibilities while maintaining the internal coherence of the larger whole. The action possibilities of a situation are entirely based on the current state – the different possibilities made available and identified by the observer at a given time. In other words, future possibilities are based on the current state only – where we are right now determines where we can go next. It does not depend on previous states. This can seem confusing since where we are right now depended on our past actions. But if you think about it, our next set of actions are made possible through our current states only.

Historical context and path dependency in many fields—from ecology to economics—seemingly suggest that past states fundamentally shape future potentials. While conventional wisdom argues that our trajectory is deeply rooted in historical conditions, this perspective oversimplifies the dynamic nature of complex ‘systems’. The current state is not merely a passive recipient of historical momentum, but an active generative point of emergence.

This means that every moment contains an infinite landscape of possibilities, yet these possibilities are simultaneously constrained and enabled by our present configuration. The past does not directly determine future states. Instead, it provides a contextual substrate from which current possibilities arise. Our current state is a complex compression of historical interactions, not a linear continuation of them.

In complex ‘systems’, the relationship between past and present is not deterministic but probabilistic. In this view, the current state acts as a filter, transforming historical conditions into immediate possibilities. These possibilities are not predetermined but emerge through the intricate interactions of the system’s current elements. The past provides context, but the present provides agency.

This understanding reveals a profound generative principle: potential is fundamentally a property of the present moment. While historical interactions create the conditions for current possibilities, these possibilities are activated and defined solely by the current state’s unique configuration. The past whispers, but the present speaks.

Moreover, this perspective invites a more dynamic understanding of complexity. Instead of viewing systems as predetermined trajectories, we can see them as constantly emerging landscapes of possibility, where each moment represents a unique point of potential transformation. The current state is not bound by historical determinism but is a creative threshold of becoming.

This approach does not negate the importance of historical context but reframes it. Historical interactions are not chains that bind future potential, but rather the rich, complex background from which new possibilities continuously emerge. The present moment is always more than the sum of its historical parts—it is a generative interface where past, present, and potential converge.

Final words:

This viewpoint invites us to see boundaries not as rigid divisions, but as dynamic interfaces of possibility. The concept of affordances and variety provides a rich framework for exploring how systems emerge, interact, and evolve. The true power of this perspective lies in its invitation to reimagine boundaries—not as limitations, but as generative spaces of potential. Whether in scientific inquiry, organizational design, or personal understanding, the act of drawing distinctions becomes a creative process of world-making.

I will finish with a wonderful quote from Spencer Brown:

Thus, we cannot escape the fact that the world we know is constructed in order to see itself. This is indeed amazing. Not so much in view of what it sees, although this may appear fantastic enough, but in respect of the fact that it can see at all. But in order to do so, evidently it must first cut itself up into at least one state which sees, and at least one other state which is seen.

Always keep learning.

Rethinking Efficiency- The Human Element in Systems Thinking:

In today’s post, I am exploring the notion of efficiency. The emergence of a new government agency in the US focused specifically on efficiency in the public sector intrigues and challenges me as a cybernetician and systems thinker. I want to examine two critical aspects of this concept.

1) The Delicate Balance of Systemic ‘Fat‘:

The first idea aligns with the principle of Lean, which was developed after Toyota’s Production System (TPS). For those curious about my use of “Toyota’s” instead of Toyota, I invite you to check out a previous post.

TPS was developed by Taiichi Ohno. While the name Lean implies “without fat,” Ohno did not advocate for complete elimination of excess. In a previous post, I explained this nuance further. Instead, Ohno understood the critical importance of carefully planned buffers—what might be called “fat”—to ensure production system resilience. The right amount of redundancy becomes an ally—what in Cybernetics is termed as having the “good” kind of variety to manage external world complexity.

When one fails to understand the nuances of a complex network like the public sector, the idea of efficiency becomes dangerous. Managing high levels of complexity requires maintaining variety at the points where the external environment intersects with the system. Most often, this critical information remains opaque at the executive level—where the rubber meets the road. There is no more perilous individual than one who believes they fully comprehend the complexity of the world around us. Variety engineering in Cybernetics offers an excellent approach to navigating these challenges. Improving our understanding of complexity requires humility and adaptability.

2) The Humans in the ‘System’:

The second idea is perhaps the most important of all. A focus on efficiency alone is a dangerous idea. I will lean on the ‘Socrates of Systems Thinking’, Russel Ackoff for this. Ackoff was a brilliant man with wonderful insights. Ackoff believed that one of the main functions of leadership is an aesthetic function. Leadership in his eyes is fundamentally about creating meaning, beauty and possibility, rather than technical efficiency. [1] Efficiency measures resource utilization in a value-neutral manner, while effectiveness weights these resources against the values of achieved outcomes.

The difference between efficiency and effectiveness is important to an understanding of transformational leadership. Efficiency is a measure of how well resources are used to achieve ends; it is value-free. Effectiveness is efficiency weighted by the values of the ends achieved; it is value-full.

He gave an example to clarify this:

For example, a men’s clothing manufacturer may efficiently turn out suits that do not fit well. Another less efficient manufacturer may turn out suits that do fit well. Because “fit” is a value to customers, the second manufacturer would be considered to be the more effective even though less efficient than the first. Of course, a manufacturer can be both efficient and effective.

Ackoff on another occasion offered this gem about being careful when pursuing efficiency:

The more efficient you are at doing the wrong thing, the wronger you become. It is much better to do the right thing wronger than the wrong thing righter. If you do the right thing wrong and correct it, you get better.

In our metrics-driven world, we reduce everything to measurable data—even human experiences become quantifiable units. Ackoff challenged this reductive approach, emphasizing that the value of an action is inherently personal and subjective.

The efficiency of an act can be determined without reference to those affected by it. Not so for effectiveness. It is necessarily personal. The value of an act may be, and usually is, quite different for different individuals.

Every system is fundamentally a human system, created as a mental construct to make sense of our complex world. Complexity itself is not an objective measure, but a perspective shaped by human values and purposes. Wisdom, as Ackoff eloquently explained, requires expanding our consideration of consequences—both in scope and time. It involves consciously inserting values into decision-making, preventing the sacrifice of long-term potential for short-term gains.

He further elaborated on the value-based approach:

Values are the concern of ethics and aesthetics. Therefore, they are necessarily involved in the conversion of efficiency into effectiveness. The production of data, information, knowledge, and understanding are primarily functions of science. The production of wisdom, which presupposes all four, is primarily a function of ethics and aesthetics because it involves the conscious insertion of values into human decision making and evaluation of its outcomes.

Effectiveness is a product of wisdom which enlarges both the range of consequences considered in making a decision and the length of time over which the decision is believed to have possible consequences. By taking long- as well as shortrun consequences into account, wisdom prevents sacrificing the future for the present… Wisdom is required for the effective pursuit of ideals, and therefore is required of leadership. Leaders must also have a creative and recreative role in the pursuit of ideals, and these are aesthetic functions.

The pursuit of effectiveness is an art form—requiring wisdom, empathy, and a profound understanding of human complexity. It demands that we look beyond the numbers, recognize the subjective nature of value, and create systems that serve not just productivity, but human potential. In an age obsessed with efficiency, our greatest leadership skill may be the capacity to see beyond the metrics—to understand that the most meaningful progress is rarely the most measurable.

I will conclude with another memorable quote from Ackoff:

A good deal of the corporate planning I have observed is like a ritual rain dance; it has no effect on the weather that follows, but those who engage in it think it does. Moreover, it seems to me that much of the advice and instruction related to corporate planning is directed at improving the dancing, not the weather.

Always keep on learning.

[1] A Systemic View of Transformational Leadership – Russell L. Ackoff

Applying Second Order Cybernetics to Voting:

On November 5th, it’s Election Day in the United States! If you are eligible, please go and vote. Whether you vote in person or by mail, participating in our democracy is crucial. Don’t miss this opportunity to shape the future of our community and country. Remember, every vote counts! Visit vote.gov for more information.

In today’s post, I will explore voting through the lens of cybernetics. In the United States, the president is elected based on the number of electoral votes, which are allocated by each state. This means that a candidate can win the popular vote yet fail to become president if they lack sufficient electoral votes. This often leads to the feeling that my vote doesn’t count, particularly if I’m not from a swing state. A swing state typically fluctuates between the two major political parties. Voting is our means of expressing our voices and participating in democracy. In today’s post, I am highlighting the importance of voting and hope to persuade readers that every vote truly matters.

The term ‘Cybernetics’ is derived from the Greek word for ‘steersman.’ Cybernetics focuses on goal-oriented processes and error correction through feedback loops. In a cybernetic system, a controller establishes the goal, while a control mechanism uses a comparator to measure deviations and an actuator to modify the course as needed. The field distinguishes between first and second order cybernetics. First order cybernetics is the cybernetics of observed systems. In this, we have the observer who is separated from the system they are observing. Here, there is a clear distinction between the subject and the object. Second order cybernetics, on the other hand, is the cybernetics of cybernetics. The self-referential nature means that the observer is now part of the system they are observing.

This distinction becomes crucial when we consider voting. Through first order cybernetics, we might simply ask, “Does my vote really matter?” But second order cybernetics prompts us to ask, “How am I part of what makes my vote matter or not?” The first order view sees the voting system as fixed and unchangeable. The second order perspective recognizes that we are part of the system we’re observing – the patterns exist because of how people (including ourselves) act. We construct this reality, and by understanding our role in this construction, we can identify opportunities to break cycles.

When we choose not to vote based on a first order view, we actively maintain the status quo, fulfilling our own prophecy about votes not mattering. Our belief in the system’s immutability contributes to its rigidity. Conversely, by voting, we participate in collective construction – not predicting outcomes, but helping to create them. This shift from seeing the voting system as external (first order) to recognizing our role in shaping it (second order) empowers voters as active participants rather than passive bystanders.

This type of thinking does not just promote voting; it offers a framework for thinking about participation in any system where individual and collective actions feed back into the system itself. It encourages a dynamic, participatory outlook which can potentially lead to a change from the current stable state.

Second order cybernetics promotes ethical considerations. Heinz von Foerster, the Socrates of Cybernetics, developed the ethical imperative. This states that “I shall act always so as to increase the total number of choices.” I am responsible for my own actions as well as inactions. Not voting reduces the possible states of the future. The future is yet to be determined. By voting, we are ensuring that the future has the capacity for more options. By voting, we are not just being observers; we are actively creating it with other participants. My actions are creating possibilities for myself and others. We are all connected in creating choices. My choices should promote kindness and the wellbeing of all. Everyone should be able to make choices for themselves, and this includes bodily autonomy. I am reminded of the following quote from one of my favorite TV characters, Doctor Who:

“Human progress isn’t measured by industry. It’s measured by the value you place on a life… an unimportant life… a life without privilege. The boy who died on the river, that boy’s value is your value. That’s what defines an age. That’s… what defines a species.”

Von Foerster also said, “If you desire to see, learn how to act.” By this, he meant that observation is not passive. We can only understand a situation by actively engaging with it. Action and perception are circularly linked. To understand the political system, we must participate in it. Not participating in it reduces our ability to see possibilities. Acting in it creates new ways to see and understand. If we do not engage by not voting, we allow ourselves to have cognitive blind spots. We cannot see how the political system can be different because we are not acting within it. We cannot understand the situation from the outside alone. Our actions create new ways of seeing.

We should exercise our civic duty of voting in all elections, including local elections. This allows us to notice the small changes within our community. We learn how close elections can be. The local elections elect individuals who can, in turn, have a large impact on our community. We are not trying to predict whether our vote matters; instead, we are making it matter through consistent participation.

Another important idea in second order cybernetics is that of recursion. No election cycle is independent. Each builds upon the previous cycles. Stable patterns can emerge from recursive operations. The current voting patterns emerge from historical patterns, but those patterns persist only because people continue to act based on the very same patterns. These patterns can be broken when enough people challenge their assumptions about what is possible. The observer (voter) is circularly connected to the observed. The voter’s perception of the system’s responsiveness is part of the system. The belief in the futility of voting is itself a crucial system component. Breaking this circular belief can lead to moving away from the current stable pattern. These stabilities are products of recursive operations and not some fixed laws.

I will finish with this wonderful quote attributed to Margaret Mead, whose 1968 paper inspired Heinz von Foerster to develop “Cybernetics of Cybernetics”:

“Never doubt that a small group of thoughtful, committed citizens can change the world; indeed, it’s the only thing that ever has.”

Always keep on learning.

Cybernetics of the Systems Approach:

In today’s post, I am looking at the idea of “sweeping-in” in Systems Approach. “Sweeping-in” can be described as the process of opening up the inquiry of a system by expanding its boundaries. Churchman discussed sweeping-in in several works, including “Thought and Wisdom” [1] and “The Design of Inquiring Systems” [2]. Churchman credited his teacher, E. A. Singer, for the concept of sweeping-in.

The “sweeping-in” process was introduced as a method for incorporating diverse concepts and variables from various sciences to resolve inconsistencies in measurements or observations. Churchman wrote:

the problems we humans face are so closely interconnected so that the only way we can study a system is to recognize the need to be comprehensive. [1]

there are no simple questions and the process of addressing a specific question will eventually require answers to more and more questions, i.e., require the “sweep-in” process. [1]

The sweeping-in process consists of bringing concepts and variables… into the model to overcome inconsistencies… [2]

In Systems Approach, sweeping-in requires us to expand our inquiry to incorporate a wide range of perspectives and variables. It demands that we examine the larger system and understand the ethical implications of our approach. This is a continual process that necessitates a cross-disciplinary approach. When addressing a situation, we must bring in knowledge and perspectives from multiple stakeholders and look at broader contexts. This means looking beyond the immediate problem to understand the larger systems and contexts in which our system exists.

Singer argued against the idea of simple and directly knowable facts from observation. He thought that there are no simple facts of nature that we can know directly, and that even seemingly simple observations are actually complex. In this regard, when we set out to find an answer to any question of fact, we realize that we must learn more and more about the situation. The original question becomes increasingly complicated, not simpler. Singer advocated not trying to reduce observations to simple elements, but instead following a sweeping-in process where our inquiry expands to include more context and interconnected systems.

The sweeping-in process is anti-reductionistic. Churchman explained this when he wrote about the strategies of inquiry [2]:

Which is better, to reduce the system to its elements or to expand the system? A system-science reply would be that since there are no simple, elementary questions, the first strategy is based on illusion and the second is the one to be followed.

The sweeping-in process requires us to embrace the complexity of the situation at hand. This demands epistemic humility. Reality is already complex, which means that our initial framing of the situation is often too narrow, resulting in premature solutions that are not effective and may cause more harm than good in the long run. We may ignore important interactions and relationships, leading to unintended consequences.

Sweeping-in involves examining our current system from the perspective of the larger systems it is part of. This is one of the basic ideas in systems approach – to understand the function of a part, we must look at it from the standpoint of the larger whole. There is a hint of Godelian thinking here. A great example from Russell Ackoff, a renowned Systems Thinker and student and friend of Churchman, is that of the automobile. No matter how much we understand an automobile and its parts, we will never understand why we drive on the right side of the road in the U.S. unless we consider the larger context—the historical, social, and cultural norms that shape American driving practices.

The reader might now wonder about the use of cybernetics in the title of the post. Churchman wrote that sweeping-in is a process of adding in and adjusting the results to improve our understanding of a problem [1]. This is a means to perform error correction in our understanding. This will be a never-ending process since we lack the variety to completely understand the external world.

Sweeping-in cautions against over-simplification. This does not mean that we need to make a situation artificially more complex for the sake of it. As I mentioned before, reality is already complex. We need to acknowledge our limitations and account for enough perspectives and variety to match the variety of the situation at hand. In Cybernetics, complexity is explained via variety. To achieve a requisite understanding of the situation, we need to have requisite variety. One of the most important ideas in cybernetics is Ross Ashby’s law of requisite variety. I welcome the reader to explore this further here.

The complexity that we are “adding” through sweeping-in is not arbitrary. We are attempting to include aspects that are needed but might not have been considered in the initial framing. This could include perspectives from other stakeholders, longer-term consequences, ethical considerations, or the influence of broader contexts such as social, political, or environmental factors.

Our basic instinct is to simplify when faced with situations that seem complex. This process is known as attenuating external variety in cybernetics. While simplification can effectively achieve requisite variety, excessive attenuation signals ignorance, which in cybernetics is referred to as the “lethal attenuator.” Our attempts to simplify can often create blind spots, causing us to overlook less obvious but influential factors. Therefore, sweeping-in serves as a reminder to deliberately resist oversimplification.

Having epistemic humility and being aware of our cognitive blind spots are important notions in second-order cybernetics. Second-order cybernetics reminds us that any system’s functioning includes the observer and their interactions with the system. Here, the feedback loops include the observer as a participant, influencing the dynamics and adding new layers of complexity to the situation. This recursive process highlights the interdependence of the system and the observer, making it illogical to separate the two.

This reflexive approach means that reality is constructed on an ongoing basis through the interaction between the observer and the system. Most importantly, this approach incorporates ethics, one of the key points of Systems Approach, by recognizing that the observer’s involvement in a system carries responsibility. Since observers influence systems and construct reality through their interactions, they must be aware of the consequences of their actions. This promotes a constructivist view, where knowledge and reality are not discovered as objective facts but are constructed through interaction in a social realm. Observers are responsible for the realities they help construct. This practical aspect challenges the implications of relativism. While multiple perspectives may exist, the ethical responsibility of observers grounds our understanding of “truth” and “reality”, emphasizing that our participation in systems has meaningful consequences.

Churchman used the examples of a prison and a hospital to explain the ethical considerations further[1]:

The planner should search not for ways to make the prison or the hospital run more smoothly, but for the reasons why we have things like badly run prisons and hospitals. The reasons turn out to be political, as much as economic; hence, the planner needs to “sweep-in” the causes of the existence of the troubled organization, and these causes like in other systems.

Another notion in sweeping-in is the need for challenging assumptions. Here we should ask questions such as WHO defines the system, WHOSE perspectives are included or excluded, and WHAT ethical considerations should be taken into account etc. The path forward, as advised by Churchman, is to utilize idealistic thinking. We must look at what an ideal solution would look like, not just accepting the current “realities”.

There are no final solutions in this approach, only provisional solutions. There is only continuous feedback and adaptation. This is also an important aspect of second-order cybernetics. The emphasis is on “less wrong” solutions rather than correct solutions. Each action taken informs the next round of understanding and action. Thus, the emphasis is on improving our understanding, or “understanding understanding”, another notion in second-order cybernetics.

Churchman was a pragmatist. From this perspective, the practical payoff comes from improving the depth and quality of decision making by acknowledging our limitations and inherent complexity of the situation. The goal is better informed action. I will finish with a great passage from Churchman that shows his true pragmatist spirit [2]:

When all is going well, and data and hypothesis are mutually compatible, then is the time to rock the boat, upset the apple cart, encourage revolution and dissent. Professors with well-established theories should encourage their students to attack them with equally plausible counter-theories. This is the only pathway to reality: whenever we are confident that we have grasped reality, then begins the new adventure to reveal our illusion and put us back again in the black forest.

But the process is dialectical, which means that two opposing processes are at work… One is the process of defending the status quo, the existing “paradigm” of inquiry, with its established methods, data, and theory. The other is the process of attacking the status quo, proposing radical but forceful paradigms, questioning the quality of the status quo.

Singer… called the “real” an “ideal” and we can see why. The idealist is a restless fellow who sees evil in complacency; he regards the realist as a hypocrite at times because his realism is unrealistic. The realist, on the other hand, accuses the idealist of being impractical, because his insistence on destroying the value of the present way of life precludes positive action. The Singerian inquiring system does not seek to resolve the philosophical dispute, but, on the contrary seeks to intensify it.

Always keep on learning.

[1] Thought and Wisdom, C. West Churchman (1982)

[2] The design of inquiring systems, C. West Churchman (1971)

On Alethic Unfolding in Systems Thinking:

In today’s post, I am exploring the concept of alethic unfolding, drawing upon ideas from the controversial German philosopher, Martin Heidegger. “Aletheia” is a Greek word often interpreted as truth. Heidegger used it to mean uncovering or unconcealment. In Greek mythology, Aletheia is the goddess of truth. The word originates from “lethe,” which means “concealment” or “forgetfulness.” According to myth, the dead were required to drink from the Lethe river to forget everything about their earthly life. Thus, a-letheia stands for un-covering or un-concealment.

Heidegger employed this word to describe how things are revealed to us in a given context. For instance, when we interact with an object such as a hammer, its properties, previously hidden, become unconcealed to us. These properties are what define a hammer for us. In everyday life, we don’t think about objects theoretically; we simply use them. A hammer makes sense to us as something for hammering, not as an abstract concept.

Another example Heidegger provides is that of a picture hanging askew on a wall. When we encounter the askew picture, its misalignment is uncovered to us. We may not notice the contents of the picture itself, but what becomes apparent is its askewness. This stems from our general understanding that pictures on walls should remain straight. This example also highlights another important aspect of aletheia according to Heidegger – aletheia, or unconcealment, is a happening or an event, not a static phenomenon. Moreover, when something is unconcealed, something else becomes concealed. In the case of the picture, as its askewness is revealed, other aspects such as the content of the picture or the color of the wall recede from our attention.

To expand further on the interplay between concealment and unconcealment in the case of the askew picture, as the misalignment becomes unconcealed, our normal, unthinking relationship with the room becomes concealed. We’re no longer just inhabiting the space; we’re now consciously observing and analyzing it. The functionality of the picture as an artwork or decorative piece becomes concealed as its status as a physical object that can be misaligned comes to the forefront. Our habitual ways of perceiving become unconcealed to us (we realize we expect pictures to be straight), while in normal circumstances, these expectations remain hidden.

We make sense of things through an ongoing interplay of unconcealment and concealment. Finding meaning in this regard is entirely contextual. It is an ongoing process and will always remain incomplete. Reality, in this sense, is a tease. Things are covered and uncovered in a dynamic interplay. This requires us to interact with the phenomenon. It is not an abstract exercise completed from afar, but rather an experiential activity. The phenomenological approach emphasizes that our experience of reality is always from a particular perspective, necessarily limiting what we can perceive at any given moment. Heidegger’s concept of unconcealment suggests that reality is not a static, fully accessible entity, but rather a dynamic process of revealing and concealing.

Heidegger wrote:[1]

The unconcealment of beings (entities) is never a merely existent state, but a happening. Unconcealment (truth) is neither an attribute of factual things in the sense of beings, nor one of propositions.

This quote encapsulates Heidegger’s view of aletheia as an active process of revelation rather than a static state. It emphasizes that unconcealment is a “happening” or an event, highlighting the dynamic nature of the emergence of meaning. Heidegger’s concept suggests that as certain aspects of a phenomenon are revealed (unconcealed), others necessarily recede (become concealed). This ongoing process of revealing and concealing is central to how we understand and interact with the world around us.

Reality, or making sense of reality, for Heidegger has some dependence on the observer and their context surrounding the phenomenon in question. The sense of the phenomenon emerges in the interaction between the observer and the phenomenon. In this sense, reality or depiction of reality requires an observer who provides the context and has practical engagement with the world. Here, reality unfolds itself gradually but not wholly. Heidegger’s view of aletheia as an event challenges us to think beyond traditional notions of truth as correspondence or coherence, and to consider how our understanding of the world is shaped by an ongoing process of revealing and concealing. It’s crucial to understand that for Heidegger, the way we encounter and understand entities is always contextualized within our being-in-the-world. Entities/objects aren’t just neutral, present things, but are enmeshed in a web of significance and practical engagement.

Heidegger didn’t believe we needed an internal “model” of reality in the way cognitive scientists might describe it. Instead, he believed we’re always already involved in the world, making sense of it through our interactions and practical engagements. Reality for Heidegger is not a fixed set of things, but a process of unfolding or revealing. We don’t need an internal “model” of reality; we’re always already involved in the world, understanding it through our practical engagements. Our understanding is shaped by our cultural context and prior experiences. We primarily make sense of things by using them and dealing with them, not by abstract thinking. Heidegger’s view challenges us to think about reality not as something “out there” to be modeled, but as something we’re always already a part of and engaged with. Reality is understood or made sense of in a space of possibilities.

With this, I would like to present the idea of alethic unfolding in Systems Thinking. We have seen that we make sense of the world as a space of possibilities. We interact with the world around us, and reality unfolds to us in a dynamic interplay of concealment and unconcealment. The world discloses differently to different people because reality is multidimensional and dependent on the observer. But this does not mean that anything goes from a relativistic standpoint. It is still weighed down by the actuality of the possibilities from a practical standpoint. This aligns more closely with pragmatic philosophy.

Alethic unfolding is making sense of the world around us as a communal activity. It refers to understanding the world as a process that emerges within specific contexts, rather than merely corresponding to isolated facts. This aligns with the principles of soft systems thinking, where knowledge is collectively constructed through dialogue and collaboration among diverse stakeholders. By acknowledging and integrating multiple perspectives, we can navigate complex human situations more effectively, leading to a richer and more practical understanding of the “system” we engage with.

We can look at an example to further illustrate the idea of alethic unfolding. This will combine Heidegger’s concepts of concealment and unconcealment with systems thinking, focusing on the role of perspectives. We’ll use the example of a city’s transportation system. Imagine a busy urban environment with various modes of transportation such as cars, buses, bicycles, and pedestrians. The alethic unfolding in this context involves the revelation and hiding of different aspects of the transportation system as various perspectives come into play. There are of course more perspectives in play than what is explored here.

1. Car Driver’s Perspective:

   – Unconcealment: The efficiency or lack thereof of road networks, traffic flow, and parking availability become apparent.

   – Concealment: The experiences of pedestrians, cyclists, and public transport users remain hidden or secondary.

2. Cyclist’s Perspective:

   – Unconcealment: The presence (or absence) of bike lanes, air quality, and the physical effort required for commuting come to the forefront.

   – Concealment: The concerns of car drivers about parking or long-distance travel fade into the background.

3. Urban Planner’s Perspective:

   – Unconcealment: The complexities of their work – interconnectedness of various transportation modes, long-term sustainability, and social equity issues in transportation access are revealed.

   – Concealment: Individual daily experiences of commuters might be obscured by numbers and long-term projections of complicated models.

4. Environmental Scientist’s Perspective:

   – Unconcealment: The environmental impact of different transportation modes, air quality data, and carbon emissions become prominent.

   – Concealment: The economic benefits of certain transportation industries might be less visible.

5. Public Health Official’s Perspective:

   – Unconcealment: The health impacts of active transportation (walking, cycling) and air pollution from vehicles come to light.

   – Concealment: The economic necessities driving certain transportation choices might be less apparent.

The alethic unfolding occurs as these different perspectives interact and shift. A systems thinking approach might reveal (unconceal) the interconnectedness of these perspectives, showing how changes in one area affect others. For example:

  • When a city decides to implement more bike lanes, it brings forth (unconceals) the needs of cyclists and environmental concerns. This decision might conceal the preferences of car drivers who lose road space.
  • A public health campaign highlighting the benefits of walking might unconceal the city’s walkability issues, leading to improvements in pedestrian infrastructure. This could conceal other priorities, like rapid transit development.

In this example, the truth of the city’s transportation system is never fully revealed or fully hidden. Instead, it unfolds through the interplay of different perspectives, each bringing certain aspects to light while obscuring others. This alethic process is ongoing, with new unconcealment leading to new forms of concealment, and vice versa.

The key insight from a systems thinking perspective is that no single viewpoint can capture the entire truth of the transportation system. The “truth” emerges through the dynamic interplay of these various perspectives, constantly shifting between concealment and unconcealment. This alethic unfolding helps us understand the complexity of the system and the importance of considering multiple viewpoints in decision-making and analysis.

Always keep on learning.

[1] The Origin of the Work of Art, Martin Heidegger (1950)

Beyond the Elephant – On Churchman’s Systems Approach:

I have been revisiting Churchman’s writings on Systems Thinking recently. In today’s post, I am looking at his book, The Systems Approach. It is a wonderful book that examines the systems approach from multiple viewpoints and walks the reader through Churchman’s thinking on the subject. Churchman was heavily inspired by philosophy and was considered to be a pragmatist. This shows up in his writings.

He notes that:

Systems are made up of sets of components that work together for the overall objective of the whole. The systems approach is simply a way of thinking about these total systems and their components.

He notes that there are several systems approaches. He considered four such advocates to these approaches.

  1. The advocates of efficiency – they claim that the best approach to a system is to identify the trouble spots, and especially the places where there is waste, e.g., unnecessarily high costs, and then proceed to remove the inefficiency.
  2. The advocates of the use of science in approaching a system – they claim that there is an objective way to look at a system and to build a “model” of the system that describes how it works. The science that is used is sometimes mathematics, sometime economics, sometimes “behavioral”.
  3.  The advocates of the use of human feelings, i.e., the humanists – they claim that systems are people, and the fundamental approach to systems consists of first looking at the human values; freedom, dignity, privacy. Above all, they say the systems approach should avoid imposing plans, i.e., intervention of any kind.
  4. The anti-planners – who believe that any attempt to lay out specific and “rational” plans is either foolish or dangerous or downright evil. The correct “approach” to systems is to live in them, to reach in terms of one’s experience, and not to try to change them by means of some grandiose scheme or mathematical model. Most of them believe that experience and cleverness are hallmarks of good management.

In the following chapters, Churchman discusses the problems with these approaches.

In one of the chapters, Churchman utilizes the age-old story of the group of blind men and an elephant to slowly poke holes in the idea of systems thinking itself. He noted:

There is a story often told in logic texts about a group of blind mean who are assigned the task of describing an elephant. Because each blind man was located at a different part of the body, a horrendous argument arose in which each claimed to have a completed understanding of the total elephantine system.

What is interesting about this story is not so much the fate of the blind men but the magnificent role that the teller had given himself – namely, the ability to see the whole elephant and consequently observe the ridiculous behaviors of the blind systems describers. The story is in fact a piece of arrogance. It assumes that a very logically astute wise man can always get on top of a situation, so to speak, and look at the foolishness of people who are incapable of seeing the whole.

 Churchman challenges the whole notion of what is meant by a system, and what is considered to be its parts, environment, and objectives. He challenges the notion of how we claim to measure the performance of a system. One example he gives is that of a medical laboratory that tests specimens which doctors send in. He asks – what is the objective of the laboratory? He states that the obvious answer might be to make the test results as accurate as possible. Then he points out that the test results being accurate may not actually improve the accuracy of the doctor’s diagnosis. Another example he gives is that of a student trying to achieve the highest grade possible in a course as if the measure of that system’s performance is the grade achieved. He points out that their stated purpose is to learn, but their real measure of performance is the grade.

Churchman also challenges the notion of environment for a system. The environment of the system is what lies “outside” of the system. This also is no easy matter to determine. When we look at an automobile we can make a first stab at estimating what’s inside the automobile and what’s outside of it. We feel like saying what lies beyond the paint job is the environment of the automobile. But is this correct? Is it correct to say, for example, that what lies beyond the paint job of a factory is necessarily outside of the factory as a system? The factory may have agents in all parts of the country who are purchasing raw materials or selling its products. These are surely “part” of the total system of the factory, and yet they are not usually within its walls. In a more subtle case, the managers of the factor may belong to various political organizations through which they are capable of exerting various kinds of political pressures. Their political activities in this case certainly “belong” to the system, although again they hardly take place within the “shell” of the system. And, returning to the automobile and considering what it is used for, we can doubt whether its paint is the real boundary of its system.

In the book, Churchman wisely notes that we are deceived by our ideas of the system. We come to believe that what we perceive is the reality and get deceived by our model of the system. But these models seldom capture the basic human values. These models also deceive us by hiding our own inability to truly understand all the aspects of what we call a system, and the complexity of its internal politics. At the same time, Churchman also remarks that each of these solutions may also make improvements. He notes:

And yet when one looks at the solution and sees its wrongness, one is also deceived, because, in searching for the wrongness, one misses the progressive aspect of the solution. We have to say that the advocate of the solution both deceives and perceives. We have to say that the solution is ridiculous and serious. We have to maintain the contradiction or else we allow ourselves to be overwhelmed by the consistent.

The ultimate meaning of the systems approach, therefore, lies in the creation of a theory of deception and in a fuller understanding of the ways in which the human being can be deceived about his world and in an interaction between these different viewpoints… What is in the nature of systems is a continuing perception and deception, a continuing re-viewing of the world, of the whole system, and of its components. The essence of the systems approach, therefore, is confusion as well as enlightenment.

With this, Churchman parts us with his four principles for his systems approach:

  1. The systems approach begins when first you see the world through the eyes of another.
  2. The systems approach goes on to discovering that every world view is terribly restricted.
  3. There are no experts in the systems approach.
  4. The systems approach is not a bad idea.

Churchman is asking us to welcome multiple perspectives. Our notion of the system is provisional. So is everyone else’s. It is based on our worldviews and value systems. When we blame the system, we engage in a fictional undertaking. What we call a system is entirely our creation and is very limited. Every system is based on a terribly restricted worldview. There are no experts who can see the whole and “fix” the system. There is no whole system since every system is embedded in an even larger system. Even with all this, the systems approach is not a bad idea. We need to utilize empathy and perspective-taking when it comes to the systems approach. We need to have epistemic humility by understanding that our viewpoints are limited. Churchman’s ideas promote a humble, inclusive, and multifaceted approach to understanding and addressing complex problems. He wanted ethics to be an important part of systems approach.

Always keep on learning.

On the Monty Hall Problem:

The Monty Hall problem has to be one of the most fascinating probability problems. The problem was first posed to Marilyn vos Savant in her column, “Ask Marilyn,” in Parade magazine:

Suppose you’re on a game show, and you’re given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the doors, opens another door, say No. 3, which has a goat. He then says to you, “Do you want to pick door No. 2?” Is it to your advantage to switch your choice?

Her response was that the player should switch. This caused an uproar among her readers. Several readers, including PhDs in Mathematics, wrote back to her saying that she was absolutely wrong. One response read:

“You are utterly incorrect about the game-show question, and I hope this controversy will bring some public attention to the serious national crisis in mathematical education. If you can admit your error, you will have contributed constructively toward the solution of a deplorable situation. How many irate mathematicians are needed to get you to change your mind?”

Another response said:

“You’re wrong, but look at the positive side. If all those Ph.D.’s were wrong, the country would be in very serious trouble.”

The intuition here is to focus on the two remaining choices and then assume that they are equally likely, therefore saying that the probability is 50% or ½. However, this is incorrect.

Let’s look at this in another way. If you have three doors (A, B, C), and there is a car behind one of the doors, the probability that you would choose that door at random is 1/3. Let’s say that you chose Door A. p(A) = 1/3

The probability that the car is behind one of the other two doors is (1/3 + 1/3) = 2/3. This can also be viewed as the car being behind door B or door C.

p(B) + p(C) = 2/3

Now, the host knows which door has the car. Therefore, the host can open the door without the car. Let’s say he opens door B and shows that the door does not contain a car (goat door). This means that once the host opens door B and shows it is empty, p(B) = 0. Therefore, p(C) is now 2/3. Thus, it would be logical for you to switch so that you can increase your probability from 1/3 to 2/3.

Here is another example to explain this. Let’s say that a “bad” magician shuffles a deck of playing cards, spreads the cards out, and asks you to pick the Ace of Spades from the spread-out cards. The cards are all facing down. You then focus on the cards and choose one at random, placing it in your pocket without looking. The probability that you chose the Ace of Spades is 1/52 (assuming there are 52 cards). The probability that the Ace of Spades is in the remainder of the deck is 51/52. Now the magician slowly turns over each card and shows that it is not the Ace of Spades. The magician is using a marked deck, so he knows the card by looking at the back. Finally, one card remains face down. Should you switch?

Of course, you should. The probability that the remaining card is the Ace of Spades is 51/52. Note that I started this problem by saying it is a “bad” magician. If it is a good magician, you should stick to your original choice.

I have created a simulator program that the reader is welcome to play around with. This is an executable file and was coded in Python. Please do verify that there is no virus. I ran 10 billion simulations, and the end result was that the player won 0.6667 times when they switched. This aligns with the theoretical probability.

The ‘Monty’ from the problem is based on the TV host Monty Hall, who was the host for the game show, Let’s Make a Deal. He never did offer the player to switch the door. This formulation was from vos Savant’s reader. A version of this problem was originally posted by Martin Gardner, Three Prisoners Problem.

The Monty Hall problem can be generalized for N doors, where Monty opens M doors. The probability of winning by switching is given by the formula:

p(win by switching) = (N-1)/(N* (N-M-1))

Where:

N = total number of doors

M = number of doors Monty Opens

In the classic problem, we have 3 doors in total, and Monty opens 1 door.

p(win by switching) = (3-1)/(3*(3-1-1)) = 2/3

All probabilities are conditional probabilities:

Now let’s get back to the classic problem and say that Monty does not know which door has the car. This means that Monty is going to randomly open one of two doors. And further, let’s say that the door Monty opens does not contain a car. In the scenario, should the player switch?

In the scenario, the player is not going to gain by switching the door since the probability is a 1/2. What gives? Let’s look at this further:

  1. Initial Setup: As in the classic problem, the player has a 1/3 chance of initially picking the car and a 2/3 chance of picking a goat.
  2. Host’s Random Choice: Unlike the classic problem, the host doesn’t know what’s behind the doors. This is the information that is critical here.
  3. Possible Outcomes:
    • If the player picked the car (1/3 chance), the host will always reveal a goat.
    • If the player picked a goat (2/3 chance), there’s a 50% chance the host reveals the car (ending the game) and a 50% chance he reveals the other goat.
  4. Conditional Probability: We’re only considering the scenario where the game continues (i.e., a goat was revealed). This happens in two ways:
    • The player picked the car (1/3 chance) and the host revealed a goat (100% chance given the player’s choice)
    • The player picked a goat (2/3 chance) and the host revealed the other goat (50% chance given the player’s choice)
  5. Probability Calculation:
    • P(car behind player’s door | goat revealed) = (1/3) / (1/3 + 1/3) = 1/2
    • P(car behind other closed door | goat revealed) = (1/3) / (1/3 + 1/3) = 1/2

The key difference from the classic problem is that the host’s lack of knowledge introduces a possibility of the game ending early (if they reveal the car). This changes the conditional probabilities when we know the game has continued.

In essence, the host’s random choice acts as a filter that equalizes the probabilities. If a goat is revealed, it’s equally likely that it happened because the player initially chose the car or because the player chose a goat and got lucky with the host’s random choice.

This scenario demonstrates how crucial the host’s knowledge and behavior are to the probabilities in the Monty Hall problem. This leads to the following core ideas of Bayesian statistics:

  • All probabilities are conditional probabilities. It is always in the form of p(an event | the information we have on hand).
  • In light of new information, we should update our prior probability.

Always keep on learning…