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Hierarchy Theory
This basic guide introduces the relationships between observation, perception, and learning that form the substance of hierarchy theory. This theory aims to answer the question of whether there is a basic structure to nature, comprising discreet levels of organization within an overall pattern.
- GenresPhilosophyScience
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First published August 15, 1996
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May 27, 2013
Ahl and Allen's work is a monumental work that tackles the issue of observing and interpreting complex patterns not by focusing on the acquisition of data itself, but by focusing on how the observer gathers data and, in the process, affects the data itself. A system has "complexity" when its several sub-systems can be examined on different levels of granularity, some of which do not correlate well with others within the same system because of problems of physical or temporal scale.
For example, whale migration might be viewed at the level of the pod, the individual whale, or even the individual cells of a whale. Tornadoes might be viewed at the climatological level, the meteorological level, or as a series of millions of molecular vectors in space. The questions asked, data gathered, and conclusions one gathers from the data might all be valid, but might not agree with each other in a meaningful way. This is not because of any naturally-occurring essence of the observed itself, but because of the way in which it is observed. Hierarchy theory attempts to at least alert the practitioner (of whatever observational school - biology, chemistry, physics, philosophy, mathematics) to the fact that their observations must affect what is being observed. To quote the authors:
Since complexity comes from the relationships between levels, it is to be expected that complexity is not a feature of the external world. Complexity does not exist independently of an observer's questions. Instead, complexity is the product of asking questions in a certain way.
In essence, then, an observer-free observation is meaningless.
Beyond this mere proposition, Hierarchy Theory goes on to provide insights into how the observer might order observations by ordering hierarchical levels, considering necessary changes to observation levels in a nested hierarchy, filtering information, and defining the whole with surfaces.
It's been some time since I've applied these principles, in practice, but when I studied African History as a graduate student, I found these guidelines extremely helpful in determining scope and the appropriate level of temporal and/or geographical granularity for the examination of historical processes and events. This was particularly true for my Master's Thesis, which was a study of the colonial response to the Mau Mau rebellion in British East Africa. I won't bore you with the details, but suffice it to say that whenever I started to experience scope-creep, the principles I learned from Hierarchy Theory kicked in and brought me back to square one. I had to examine my examinations and "reset" to an appropriate scale.
While many of the ideas in Hierarchy Theory seem obvious to anyone who has undertaken serious academic research, Ahl and Allen's presentation collates many of the methods on which one might have accidentally stumbled in the course of observation and presents to the reader a step-by-step approach to assessing the observer's assumptions vis-a-vis observed data.
Fun for the whole family! Recommended for those who love to observe observation and observing the observation of observation.
My most sincere hope is that someone much more intelligent than I am will "diff" this book against the Copenhagen interpretation of quantum mechanics. It seems to me that the dovetailing of hierarchy theory and the Copenhagen interpretation would provide some interesting grist for scaling quantum observations "up" into the classical realm or even further up into the cosmological realm. I have a hunch that such an exercise might provide great insight into the workings of the universe at the borders between the quantum, classical, and cosmological scales. Again, this would require the brains and time of someone much better endowed with both than I am. Any takers?
For example, whale migration might be viewed at the level of the pod, the individual whale, or even the individual cells of a whale. Tornadoes might be viewed at the climatological level, the meteorological level, or as a series of millions of molecular vectors in space. The questions asked, data gathered, and conclusions one gathers from the data might all be valid, but might not agree with each other in a meaningful way. This is not because of any naturally-occurring essence of the observed itself, but because of the way in which it is observed. Hierarchy theory attempts to at least alert the practitioner (of whatever observational school - biology, chemistry, physics, philosophy, mathematics) to the fact that their observations must affect what is being observed. To quote the authors:
Since complexity comes from the relationships between levels, it is to be expected that complexity is not a feature of the external world. Complexity does not exist independently of an observer's questions. Instead, complexity is the product of asking questions in a certain way.
In essence, then, an observer-free observation is meaningless.
Beyond this mere proposition, Hierarchy Theory goes on to provide insights into how the observer might order observations by ordering hierarchical levels, considering necessary changes to observation levels in a nested hierarchy, filtering information, and defining the whole with surfaces.
It's been some time since I've applied these principles, in practice, but when I studied African History as a graduate student, I found these guidelines extremely helpful in determining scope and the appropriate level of temporal and/or geographical granularity for the examination of historical processes and events. This was particularly true for my Master's Thesis, which was a study of the colonial response to the Mau Mau rebellion in British East Africa. I won't bore you with the details, but suffice it to say that whenever I started to experience scope-creep, the principles I learned from Hierarchy Theory kicked in and brought me back to square one. I had to examine my examinations and "reset" to an appropriate scale.
While many of the ideas in Hierarchy Theory seem obvious to anyone who has undertaken serious academic research, Ahl and Allen's presentation collates many of the methods on which one might have accidentally stumbled in the course of observation and presents to the reader a step-by-step approach to assessing the observer's assumptions vis-a-vis observed data.
My most sincere hope is that someone much more intelligent than I am will "diff" this book against the Copenhagen interpretation of quantum mechanics. It seems to me that the dovetailing of hierarchy theory and the Copenhagen interpretation would provide some interesting grist for scaling quantum observations "up" into the classical realm or even further up into the cosmological realm. I have a hunch that such an exercise might provide great insight into the workings of the universe at the borders between the quantum, classical, and cosmological scales. Again, this would require the brains and time of someone much better endowed with both than I am. Any takers?
February 16, 2020
Sometimes one wonders why certain, ostensibly very simple phenomena take so long to be recognised and formalised. Take the mechanism of circular causation, or feedback loops. Humanity has been confronted with these phenomena for ages. Engineers and craftsmen from all eras have worked with these mechanisms, without however understanding their wider import. It was only at the end of World War II that Norbert Wiener codified it as a feedback phenomenon and thereby established the new discipline of Cybernetics.
Hierarchy Theory is the result of a similar, belated discovery. It was Herbert Simon who pointed out, in the 1960s, that many complex living and non-living systems featured a hierarchical structure. By 'hierarchic' he meant "a system that is composed of interrelated subsystems, each of the latter being in turn hierarchic in structure until we reach some lowest level of elementary subsystem." For instance, an animal includes several organs; the organs include lots of tissues; the tissues include zillions of cells, etc. Simon wondered how the prevalence of these hierarchic structures could be explained. It turned out that systems that included loosely coupled subsystems (or 'intermediate stable forms') could evolve faster in the process of natural selection. In other words: if we would start with a population of systems of comparable complexity, some of them hierarchical and others not, but all being subjected to similar frequencies of mutation, the hierarchical systems would increase their fitness through evolutionary processes much faster than the remaining systems, and would soon come to dominate the entire population. Simon's famous parable on the two watchmakers made this clear in a very intuitive fashion.
This insight put in place the foundation for Hierarchy Theory. Also the present book by Ahl and Allen takes its cue from Simon's point. As an aside: the ideas expounded in it are basically Allen's, a botanist and ecologist by training. Valerie Ahl, a clinical psychologist, presumably lent her husband a more fluid pen to produce a relatively short and more accessible book than Allen's original 1982 tome (co-authored with T. Starr) on the same subject.
The contribution of this book is twofold. It explains how relationships between sub-entities (or sublevels) in hierarchical systems can be understood and it does so from an emphatically non-realist, constructivist perspective. It is the interaction between these two elements that makes for an arduous read (don't be fooled by the book's numerous, sometimes droll illustrations).
Mainly, levels in hierarchies can be ordered based on scalar characteristics - in space and time - of the entities included in them. This leads to higher levels operating more slowly and at a lower frequency than lower levels; and higher levels also exhibiting a constraining influence on lower levels. This applies to systems of all sorts. In an ecological system layers can be identified that show different spatio-temporal dynamics, ranging from slow biome-scale phenomena to high-frequency changes at the level of a patch. The US Federal Supreme Court is a hierarchically superior, stable institution by virtue of the vast professional experience invested in the nine justices, their life tenure, the relative independence from political pressures, and the judicial restraint they are expected to observe. It has been designed to have a dampening, constraining influence on institutions at lower levels.
Now, the point forcefully made by Allen is that the choices that determine these scalar characteristics are observer-dependent. The temporal and spatial limits of our observations are, consciously or unconsciously, defined by us as a result of the kinds of questions that we dream up as scientists. "Observing is an active process. To make an observation one must search but cannot begin without an idea of what it is one might find. (...) As soon as the question is formulated, certain constraints immediately follow. The question directs and structures the observation process by posing hypothetical entities and their roles."
As a result, Hierarchy Theory in Allen's conception presents itself as an epistemological (meta-)theory that emphatically brings in the role of the observer in any formal study of complex systems. We don't have access to the real world. We are confronted with a material world that is blind, purposeless, active, ever-changing. The best we can do is to be very explicit and transparent about the vantage point that we construct for ourselves to give us a handle on this complexity.
But why on earth would we want to make our lives so difficult? Wouldn't it be easier to simply assume that what we see is really what is out there? According to Allen the problem is that we will run into paradoxes (or, as others would say, into 'errors of logical typing'), and because we don't understand where these inconsistencies come from, we will find ways to 'save the appearances' rather than to improve our predictive theories. Biologists are particularly skillful in developing new vocabulary in response to observed mismatches between what they a priori define and what they see. For instance, when large organisms meet large numbers of very small organisms the concept of 'parasitism' is invoked to define away the inconsistency with a conventional hierarchy that puts organism above population. Hence, "biology has rich typology but a poor record of prediction in new situations because it is slow to identify observed empirical entities and associated levels of observation."
So, complexity does not exist independently of an observer's questions. Instead, complexity is the product of asking questions in a certain way. In this book, Allen offers a conceptual framework, not to ask better questions, but to help us articulate the observational implications of a given question and to separate out the contributions of observer and observed in the generation of data.
Having said that, while I am ready to acknowledge the cogency of these ideas, in this book they don't really gel into a practicable approach. And I'm not sure Allen is interested in that. In a videotaped interview he gave a rather cavalier response to the question how hierarchy theory was used in policy development: "I am just a theorist who dumps ideas on my peers who then need to find out how they can put them into practice." Frankly, it is a missed opportunity.
A second point of criticism is the structure of the book's argument. The main thrust is clear: the first three chapters explain Allen's epistomological stance, the next four introduce a basic framework to think about hierarchies (revolving around core concepts such as levels, constraints, nestedness, filters and surfaces), and the final chapter explores the the dynamics of hierarchical systems. But on that journey I got confused at numerous junctures by plethoric jargon, lots of conditional statements, frequent iterations on familiar points and by scattered and superficially treated examples. In my humble opinion, stricter editorial oversight might have produced a better book.
Finally, and this is a more general point with a bearing on the stature and relevance of hierarchy theory, I wonder whether it is appropriate to narrow the perspective on complex systems to a hierarchical template, to the exclusion of other and equally potent architectural principles. I am thinking more particularly on the notion of networks (or meshworks). It is not unreasonable to hypothesise that combining (vertical) hierarchies and (horizontal) networks would provide us with much more leverage in explaining the dynamic behaviour of complex systems. (Manuel DeLanda did something of the sort in his materialist version of the last Thousand Years of Nonlinear History) Freeing itself of this observational blind spot would perhaps unholster Hierarchy Theory from the theoretical niche in which it has been confined up to the present day.
3 1/2 stars
Hierarchy Theory is the result of a similar, belated discovery. It was Herbert Simon who pointed out, in the 1960s, that many complex living and non-living systems featured a hierarchical structure. By 'hierarchic' he meant "a system that is composed of interrelated subsystems, each of the latter being in turn hierarchic in structure until we reach some lowest level of elementary subsystem." For instance, an animal includes several organs; the organs include lots of tissues; the tissues include zillions of cells, etc. Simon wondered how the prevalence of these hierarchic structures could be explained. It turned out that systems that included loosely coupled subsystems (or 'intermediate stable forms') could evolve faster in the process of natural selection. In other words: if we would start with a population of systems of comparable complexity, some of them hierarchical and others not, but all being subjected to similar frequencies of mutation, the hierarchical systems would increase their fitness through evolutionary processes much faster than the remaining systems, and would soon come to dominate the entire population. Simon's famous parable on the two watchmakers made this clear in a very intuitive fashion.
This insight put in place the foundation for Hierarchy Theory. Also the present book by Ahl and Allen takes its cue from Simon's point. As an aside: the ideas expounded in it are basically Allen's, a botanist and ecologist by training. Valerie Ahl, a clinical psychologist, presumably lent her husband a more fluid pen to produce a relatively short and more accessible book than Allen's original 1982 tome (co-authored with T. Starr) on the same subject.
The contribution of this book is twofold. It explains how relationships between sub-entities (or sublevels) in hierarchical systems can be understood and it does so from an emphatically non-realist, constructivist perspective. It is the interaction between these two elements that makes for an arduous read (don't be fooled by the book's numerous, sometimes droll illustrations).
Mainly, levels in hierarchies can be ordered based on scalar characteristics - in space and time - of the entities included in them. This leads to higher levels operating more slowly and at a lower frequency than lower levels; and higher levels also exhibiting a constraining influence on lower levels. This applies to systems of all sorts. In an ecological system layers can be identified that show different spatio-temporal dynamics, ranging from slow biome-scale phenomena to high-frequency changes at the level of a patch. The US Federal Supreme Court is a hierarchically superior, stable institution by virtue of the vast professional experience invested in the nine justices, their life tenure, the relative independence from political pressures, and the judicial restraint they are expected to observe. It has been designed to have a dampening, constraining influence on institutions at lower levels.
Now, the point forcefully made by Allen is that the choices that determine these scalar characteristics are observer-dependent. The temporal and spatial limits of our observations are, consciously or unconsciously, defined by us as a result of the kinds of questions that we dream up as scientists. "Observing is an active process. To make an observation one must search but cannot begin without an idea of what it is one might find. (...) As soon as the question is formulated, certain constraints immediately follow. The question directs and structures the observation process by posing hypothetical entities and their roles."
As a result, Hierarchy Theory in Allen's conception presents itself as an epistemological (meta-)theory that emphatically brings in the role of the observer in any formal study of complex systems. We don't have access to the real world. We are confronted with a material world that is blind, purposeless, active, ever-changing. The best we can do is to be very explicit and transparent about the vantage point that we construct for ourselves to give us a handle on this complexity.
But why on earth would we want to make our lives so difficult? Wouldn't it be easier to simply assume that what we see is really what is out there? According to Allen the problem is that we will run into paradoxes (or, as others would say, into 'errors of logical typing'), and because we don't understand where these inconsistencies come from, we will find ways to 'save the appearances' rather than to improve our predictive theories. Biologists are particularly skillful in developing new vocabulary in response to observed mismatches between what they a priori define and what they see. For instance, when large organisms meet large numbers of very small organisms the concept of 'parasitism' is invoked to define away the inconsistency with a conventional hierarchy that puts organism above population. Hence, "biology has rich typology but a poor record of prediction in new situations because it is slow to identify observed empirical entities and associated levels of observation."
So, complexity does not exist independently of an observer's questions. Instead, complexity is the product of asking questions in a certain way. In this book, Allen offers a conceptual framework, not to ask better questions, but to help us articulate the observational implications of a given question and to separate out the contributions of observer and observed in the generation of data.
Having said that, while I am ready to acknowledge the cogency of these ideas, in this book they don't really gel into a practicable approach. And I'm not sure Allen is interested in that. In a videotaped interview he gave a rather cavalier response to the question how hierarchy theory was used in policy development: "I am just a theorist who dumps ideas on my peers who then need to find out how they can put them into practice." Frankly, it is a missed opportunity.
A second point of criticism is the structure of the book's argument. The main thrust is clear: the first three chapters explain Allen's epistomological stance, the next four introduce a basic framework to think about hierarchies (revolving around core concepts such as levels, constraints, nestedness, filters and surfaces), and the final chapter explores the the dynamics of hierarchical systems. But on that journey I got confused at numerous junctures by plethoric jargon, lots of conditional statements, frequent iterations on familiar points and by scattered and superficially treated examples. In my humble opinion, stricter editorial oversight might have produced a better book.
Finally, and this is a more general point with a bearing on the stature and relevance of hierarchy theory, I wonder whether it is appropriate to narrow the perspective on complex systems to a hierarchical template, to the exclusion of other and equally potent architectural principles. I am thinking more particularly on the notion of networks (or meshworks). It is not unreasonable to hypothesise that combining (vertical) hierarchies and (horizontal) networks would provide us with much more leverage in explaining the dynamic behaviour of complex systems. (Manuel DeLanda did something of the sort in his materialist version of the last Thousand Years of Nonlinear History) Freeing itself of this observational blind spot would perhaps unholster Hierarchy Theory from the theoretical niche in which it has been confined up to the present day.
3 1/2 stars
October 6, 2019
This book explores the idea that science solves complex problems by building conceptual models made up of levels of objects in different scales rather than only observations and 'reduction logic'. It explores the relationship between conceptual models and observations using the psychological theory of objects. ( How humans see the world as objects)
Interestingly, artificial intelligence ( such as Siri) use object theory, not only logic. Scientists ( and many other university-educated professions) are often 'naive realists'. They believe they have direct access to the material world and only have to use logic to understand complex issues which is not true. We can only observe one perspective (our own) and only observe objects that are defined. ( In object theory to observe a new object; we must define it first). In complex systems, no one can observe the totality of the system. To answer a specific question, we combine different perspectives by building conceptual models.
Hierarchy theory organises these objects into levels based on the object's characteristics, temporal and spatial frequencies (what objects can be oberved together). The larger-scale levels provide context and constraints to smaller-scale levels, and smaller-scale levels explain how the larger scale work. Levels are bounded by surfaces that filter the flow of information between levels so the the flow between objects in the same level is less impeded and has more integrity than the flow of information between that level and the next higher level that pass through a surfaces. One problem with this book is that it is tough to find other reading material on this topic.
Interestingly, artificial intelligence ( such as Siri) use object theory, not only logic. Scientists ( and many other university-educated professions) are often 'naive realists'. They believe they have direct access to the material world and only have to use logic to understand complex issues which is not true. We can only observe one perspective (our own) and only observe objects that are defined. ( In object theory to observe a new object; we must define it first). In complex systems, no one can observe the totality of the system. To answer a specific question, we combine different perspectives by building conceptual models.
Hierarchy theory organises these objects into levels based on the object's characteristics, temporal and spatial frequencies (what objects can be oberved together). The larger-scale levels provide context and constraints to smaller-scale levels, and smaller-scale levels explain how the larger scale work. Levels are bounded by surfaces that filter the flow of information between levels so the the flow between objects in the same level is less impeded and has more integrity than the flow of information between that level and the next higher level that pass through a surfaces. One problem with this book is that it is tough to find other reading material on this topic.
November 13, 2012
Professor Tim Allen is also an amazing, passionate teacher - he inspires, he challenges, he makes you laugh and most importantly, he'll make you think.
May 10, 2013
Essential book.
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