Excerpt from "Karl Weick Keeps You on Your Toes" - by Jordi Comas: "Karl Weick’s work is an influential example of the open systems approach. In grad school, it was a treat to read The Social Psychology of Organizing (still in print since 1967). Not least because he points out that organizations are never stable. They are always organizing. And because he used cartoons! Like this one.
Weick also built his understanding of organizations from the cognitive, the individual, not from the structure down. What I took from our discussion was that there were two ideas Weick covers that we wanted to describe not in conceptual terms, but in empirical terms. These were retrospective rationality and enacting the environment.
Retrospective rationality is the idea that we act in a myriad of ways and then “make sense” of our actions in cognitive and linguistic terms that attempt to make them rational. This is not because humans are dumb or lazy. We act and then think because the unending flow of activity of the world demands it of us. The ways in which we act are also due to a myriad of past reasons and contingencies. In other words, there are always more reasons we have acted or that may explain are actions than we need.
There is equivocality in the world. We don’t always know why things are. Hence retrospective rationality is about reducing equivocality; reducing the welter of contradicting reasons why we may have acted or that may explain why the world of human affairs is as it is. To be adaptive to this environment, to be open, requires tolerating some messiness, some disorder. For example, in SPofO, he writes:
…the inability of organizations to tolerate equivocal processing may well be the the most important reason they have trouble. It is the unwillingness to meet equivocality in an equivocal manner that produces failure, nonadaptation, autism, isolation form reality, psychological cost, etc. It is the unwillingness to disrupt order, ironically, that makes it impossible for the organization to create order (41).
But what about examples? In his 1995 book, Sensemaking in Organizations, Weick offers tow research-based examples (29-30). One involves asking film executives about the future of the film industry after they look at financial reports for the preceding three years. Logical approach, right? As it was reported, the exercise reflected how much variation in understanding there was about what had happened in the past. Hence, any attempt to understand the present and future was beset by equivocality. Something explained past performance? But what? Consumer tastes? Directors’ abilities? Cultural zeitgeist? A second example was a control group psychology experiment (very classic in style) where people were randomly assigned to groups that would be arbitrarily assigned low or high performance status (irrespective of actual results). Those in high performance groups reported that in most areas of group function, guess what, they scored higher than low performing groups."
"Retrospective Rationality" plays an important role in "sense-making":
Interview with Gregory Chaitin and links about Algorithmic Information Dynamics
"It seems to me that the most important discovery since Gödel was the discovery by Chaitin, Solomonoff & Kolmogorov of the concept called Algorithmic Probability which is a fundamental new theory of how to make predictions given a collection of experiences & this is a beautiful theory, everybody should learn it, but it’s got one problem, that is, that you cannot actually calculate what this theory predicts because it is too hard, it requires an infinite amount of work. However, it should be possible to make practical approximations to the theory that would make better predictions than anything we have today. Everybody should learn all about that and spend the rest of their lives working on it." - Marvin Minsky (2014)
One day, Alfred Korzybski was giving a lecture to a group of students, and he interrupted the lesson suddenly in order to retrieve a packet of biscuits, wrapped in white paper, from his briefcase. He muttered that he just had to eat something, and he asked the students on the seats in the front row if they would also like a biscuit.
A few students took a biscuit. “Nice biscuit, don’t you think,” said Korzybski, while he took a second one. The students were chewing vigorously. Then he tore the white paper from the biscuits, in order to reveal the original packaging.
On it was a big picture of a dog’s head and the words “Dog Cookies.” The students looked at the package, and were shocked. Two of them wanted to vomit, put their hands in front of their mouths, and ran out of the lecture hall to the toilet. “You see,” Korzybski remarked, “I have just demonstrated that people don’t just eat food, but also words, and that the taste of the former is often outdone by the taste of the latter.” (via)
"The map is not the territory, the world is not the thing it describes. Whenever the map is confused with the territory, a 'semantic disturbance is set up in the organism. The disturbance continues until the limitation of the map is recognized." - A.Korzybski
"General semantics is a philosophy that deals with how people react to things that happen around them based on meaning. It was created by Alfred Korzybski during the 1920s. The goal of general semantics is for people to know that when we simplify something, either mentally or in language, that simplification is not the same thing as the thing simplified. How people understand reality is not the same as what reality is because people do not know everything about reality. General semantics teaches that there is always more to something than what is seen, heard, felt, or believed." (via)
AGORA-Net - a Computer-Supported Collaborative Argument Visualization (CSCAV) tool. An argument is defined here as a set of statements—a claim and one or more reasons—where the reasons jointly provide support for the claim, or are at least meant to support the claim.
#Comment: If you have advanced "sensemaking" infrastructure, but in praxis predominately use it to advance the narrow interests of the military industrial complex ("kill, surveil, control"), shouldn't it be called "nonsensemaking" instead?
Exploring Abductive Reasoning - The Logic of Maybe
Abductive reasoning is a form of logical inference which starts with an observation or set of observations then seeks to find the simplest and most likely explanation for the observations. This process, unlike deductive reasoning, yields a plausible conclusion but does not positively verify it. Abductive conclusions are thus qualified as having a remnant of uncertainty or doubt, which is expressed in retreat terms such as "best available" or 'most likely.
Put differently, Abduction is drawing a conclusion using a heuristic that is likely, but not inevitable given some foreknowledge.e.g., I observe sheep in a field, and they appear white from my viewing angle, so sheep are white. Contrast with the deductive statement: "Some sheep are white on at least one side". To simplify and summaries: Deductive = Top down logic - Inductive = Bottom up logic - Abductive = What seems most probably?
The American philosopher Charles Sanders Peirce (1839–1914) introduced abduction into modern logic. Over the years he called such inference hypothesis, abduction, presumption, and retroduction. He considered it a topic in logic as a normative field in philosophy, not in purely formal or mathematical logic, and eventually as a topic also in economics of research. (wikipedia)
In later years his view came to be:
Abduction is guessing. It is "very little hampered" by rules of logic. Even a well-prepared mind's individual guesses are more frequently wrong than right. But the success of our guesses far exceeds that of random luck and seems born of attunement to nature by instinct (some speak of intuition in such contexts).
Abduction guesses a new or outside idea so as to account in a plausible, instinctive, economical way for a surprising or very complicated phenomenon. That is its proximate aim.
Its longer aim is to economize inquiry itself. Its rationale is inductive: it works often enough, is the only source of new ideas, and has no substitute in expediting the discovery of new truths.
Pragmatism is the logic of abduction. Upon the generation of an explanation, the pragmatic maxim gives the necessary and sufficient logical rule to abduction in general. The hypothesis, being insecure, needs to have conceivable implications for informed practice, so as to be testable and, through its trials, to expedite and economize inquiry. The economy of research is what calls for abduction and governs its art.
"The interest in the use of abductive, analogic and intuitive problem-solving has major roots in the “design studies” movement of the late 1960’s & 1970’s.
This movement started in the UK, primarily thanks to the work of Leslie Martin and Lionel March at the Cambridge Centre at the Cambridge School of Architecture.March and Martin were at the head of a generation of scholars seeking to systematise and understand how architects and designers thought about the world. This paralleled research into cybernetics & AI in the states by Herbert Simon, but for some reason it seems that there was a critical confluence of design thinkers in the UK at that time, and most of the literature around induction, abduction, etc. seems to come from this period.
The key ideas: The original intention of this group was to understand and document the design process. The hope was that if you understood how architects and designers perceived the world, you could replicate this in computer or expert-systems (and then do away with or “improve” the designer). Because replicability was one of the key goals, a natural sciences approach was taken to observing designers. A lot of controlled experiments were set up in laboratories to test “design problem solving”, most of which failed miserably. This led to a more ethnographic approach, including some of the first anthropological approaches to knowledge elicitation that I’ve ever seen.
What they found was that:
“Scientists adopt a problem-focused strategy and architects a solution-focused strategy.” (Lawson, 1979)
“The scientific method is a pattern of problem-solving behaviour employed in finding out the nature of what existis, whereas the design method is a pattern of behaviour employed in inventing things of value which do not yet exists. Science is analytic, design is constructive.” (Gregory, 1966)
This places a heavy emphasis on action, testing, and observation, in that order, and highlights the essentially creative nature of design. Nigel Cross, who is still teaching at the Open University, suggests that design is “a process of pattern-synthesis, when the solution is not simply ‘lying there in the data’ but has to be actively constructed by the designer’s own efforts.”. You can see how this relates to the notion of abduction. Peirce suggests that, “the whole fabric of our knowledge is one matted felt of pure hypothesis confirmed and refined by induction.” This is very similar to design. In other words,
“[Architects] learn about the nature of the problem largely as a result of trying out solutions, whereas the scientists set out specifically to study the problem.” (Lawson, 1980)
Schum notes that if Peirce is correct, “new ideas emerge as we combine, marshal or organize thoughts and evidence in different ways.” Because the design method is fundamentally exploratory, it is about hypothesis generation based on the most uncertain and sketchy forms of data. It uses both abductive and constructive reasoning to show “what might be”, instead of deductive reasoning to show “what is”." Read more..
In recent decades, Abductive Logic and Reasoning has been extensively studied in the context of Artificial Intelligence and Machine Learning research. A few links, old & new:
Related Ideas by Abductive Logic pioneer Charles Sanders Peirce, on Semiotics:
"The essence of belief is the establishment of a habit; and different beliefs are distinguished by the different modes of action to which they give rise." - Charles Sanders Peirce
BASED ON TRUE EVENTS: "I have been teaching Geometry this year,and trying my best to explain logic,deduction vs induction, and the ever present, always faulty, always useful, abductive “reasoning.”Without abductive reasoning, life itself would not be possible for humans. Induction and deduction? Entirely optional. Our car, (which only had 3 out 4 cyliders working) started to turn itself off, at apparently random intervals. There you’d be, changing lanes, in what you thought was a car,and poof no car, just a large metal box that looked like a car,with a seat belt, a driver’s seat, and a silent engine,rolling to a final velocity of zero. I drove the box / car to five dealerships in town,while searching for the best replacement for the box.I can now say, what others have noted before;
“Pure logic, when considering a car, (or any thing else other than numbers) does not exist.”
“Human beings, viewed as behaving systems, are quite simple. The apparent complexity of our behavior over time is largely a reflection of the complexity of the environment in which we find ourselves.” ― Herbert A. Simon, The Sciences of the Artificial
“It is true that humanity is faced with many problems. It always has been but perhaps not always with such keen awareness of them as we have today. We might be more optimistic if we recognized that we do not have to solve all of these problems. Our essential task—a big enough one to be sure—is simply to keep open the options for the future or perhaps even to broaden them a bit by creating new variety and new niches. Our grandchildren cannot ask more of us than that we offer to them the same chance for adventure, for the pursuit of new and interesting designs, that we have had.” ― Herbert A. Simon, The Sciences of the Artificial
“An artifact can be thought of as a meeting point—an “interface” in today’s terms—between an “inner” environment, the substance and organization of the artifact itself, and an “outer” environment, the surroundings in which it operates. If the inner environment is appropriate to the outer environment, or vice versa, the artifact will serve its intended purpose.” ― Herbert A. Simon, The Sciences of the Artificial
In 1975, Yoshiki Kuramoto introduced a simple model to describe the collective dynamics of a set of interacting oscillators. In the model, each oscillator has a natural frequency, and is coupled equally to all other oscillators. Assuming a fixed spread in oscillator frequencies, Kuramoto showed that in the limit of a large number of oscillators, the model exhibits a continuous phase transition from asynchronous to synchronous behaviour with increasing inter-oscillator coupling. Since then, the model and generalizations of it have been widely used in exploring the synchronization behavior in groups of biological cells, fireflies, superconducting Josephson junctions, or the movements of swarms or flocks of organisms.
Self-organized criticality is a property of dynamical systems that have a critical point as an attractor. Their macroscopic behavior thus displays the spatial or temporal scale-invariance characteristic of the critical point of a phase transition, but without the need to tune control parameters to a precise value, because the system tunes itself as it evolves towards criticality. The concept was put forward by Per Bak, Chao Tang and Kurt Wiesenfeld, and is considered to be one of the mechanisms by which complexity arises in nature.
Christopher Langton(1948) is an American computer scientist and one of the founders of the field of artificial life.He coined the term in the late 1980s when he organized the first "Workshop on the Synthesis and Simulation of Living Systems" at the Los Alamos National Laboratory in 1987. Following his time at Los Alamos, Langton joined the Santa Fe Institute, to continue his research on artificial life. He left SFI in the late 1990s, and abandoned his work on artificial life, publishing no research since that time.
Langton's Ant Colonies- a two-dimensional universal Turing machine with a very simple set of rules but complex emergent behavior (1986)
Langton's Loops - a particular "species" of artificial life in a cellular automaton created in 1984 by Christopher Langton. They consist of a loop of cells containing genetic information, which flows continuously around the loop and out along an "arm" (or pseudopod), which will become the daughter loop.
After Langton disappeared from the ALife community in the 1990s, he reappeared in the 2007 as author of "Military Balance" by "International Institute for Strategic Studies".
Neti Neti (नेति नेति) is a Sanskrit expression which means "not this, not that", or "neither this, nor that". It is found in the Upanishads and constitutes an analytical meditation helping a person to understand the nature of Brahman by first understanding what is not Brahman.
Neti Neti as understood through the quadrilemma articulated by Kinhide Mushakoji (Global Issues and Interparadigmatic Dialogue; essays on multipolar politics, 1988):
Prigogine’s view on cosmology (the more widely accepted Big Band Theory and The Steady State Theory) agrees with that of the Indian cosmologist Jayant Vishnu Narlikar, who wrote “Astrophysicists of today who hold the view that the ‘ultimate cosmological problem’ has been more or less solved may well be in for a few surprises before this century is out”.
“Many scientists have been willing to explain this singularity (the big bang) in terms of the “hand of God” or the triumph of the biblical story or creation.”
“In accepting that the future is not determined, we come to the end of certainty” says Prigogine. He does not believe, however, that this is an admission of defeat for the human mind. He asserts that the opposite is true.
He views the universe as a giant thermodynamical system far from equilibrium, where we find fluctuations, instabilities, and evolutionary patterns at all levels.
Some great quotes from the end of the book: For Einstein, science was a means of avoiding the turmoil of everyday existence. He compared scientific activity to the “longing that irresistibly pulls the town-dweller away from his noisy, cramped quarters and toward the silent high mountains. Einstein’s view of the human condition was profoundly pessimistic.
Science began with the Promethean affirmation of the power or reason, but it seemed to end in alienation – a negation of everything that gives meaning to human life.
Einstein repeatedly stated that he had learned more from Fyodor Dostoyevsky than from any physicist. In a letter to Max Born in 1924, he wrote that if he were forced to abandon strict causality (classical physics and relativity), he “would rather be a cobbler, or even an employee in a gaming house, than a physicist”. In order to be of any value at all, physics has to satisfy his need to escape the tragedy of the human condition. “And yet and yet”, when Einstein was confronted by Godel with the extreme consequences of his quest, the denial of the very reality that physics endeavors to describe, Einstein recoiled. (Godel took Einstein’s Theory of Relativity and classical physics and showed that past and future are equivalent and that it is possible to travel back in time).
Prigogine has tried to follow a narrow path between two conceptions that both lead to alienation: a world ruled by deterministic laws, which leaves no place for novelty, and a world ruled by a dice-playing God, where everything is absurd, acausal, and incomprehensible.
Prigogine ends his book with the following words: “As we follow along the narrow path, we discover that a large part of the concrete world around us has until now “slipped through the meshes of the scientific net”, to use Whitehead’s expression. We face new horizons at this privileged moment in the history of science”.
"In The End of Certainty, Prigogine contends that determinism is no longer a viable scientific belief: "The more we know about our universe, the more difficult it becomes to believe in determinism." This is a major departure from the approach of Newton, Einstein and Schrödinger, all of whom expressed their theories in terms of deterministic equations. According to Prigogine, determinism loses its explanatory power in the face of irreversibility and instability."
"A thermodynamically open system which is operating out of, and often far from, thermodynamic equilibrium in an environment with which it exchanges energy and matter. A tornado may be thought of as a dissipative system."