🆆Edward Witten - Collected Quotes

"Discovery of supersymmetry would be one of the real milestones in physics, made even more exciting by its close links to still more ambitious theoretical ideas. Indeed, supersymmetry is one of the basic requirements of 'string theory', which is the framework in which theoretical physicists have had some success in unifying gravity with the rest of the elementary particle forces. Discovery of supersymmetry would would certainly give string theory an enormous boost." (Edward Witten, [preface to (Gordon Kane, "Supersymmetry: Unveiling the Ultimate Laws of Nature", 2000) 1999)

"In string theory, to understand the nature of the Big Bang, or the quantum fate of a black hole, or the nature of the vacuum state that determines the properties of the elementary particles, requires information beyond perturbation theory [...] Perturbation theory is not everything. It is just the way the [string] theory was discovered." (Edward Witten, "The Past and Future of String Theory", 2003)

"Replacing particles by strings is a naive-sounding step, from which many other things follow. In fact, replacing Feynman graphs by Riemann surfaces has numerous consequences: 1. It eliminates the infinities from the theory. [...] 2. It greatly reduces the number of possible theories. [...] 3. It gives the first hint that string theory will change our notions of spacetime." (Edward Witten, "The Past and Future of String Theory", 2003)

"To put it differently, global symmetry is a property of a system, but gauge symmetry in general is a property of a description of a system. What we really learn from the centrality of gauge symmetry in modern physics is that physics is described by subtle laws that are 'geometrical'. 
This concept is hard to define, but what it means in practice is that the laws of Nature are subtle in a way that defies efforts to make them explicit without making choices. The difficulty of making these laws explicit in a natural and non-redundant way is the reason for 'gauge symmetry'." (Edward Witten, "Symmetry and Emergence", 2018)

"We can see the relation between gauge symmetry and global symmetry in another way if we imagine whether physics as we know it could one day be derived from something much deeper – maybe unimaginably deeper than we now have. Maybe the spacetime we experience and the particles and fields in it are all 'emergent' from something much deeper." (Edward Witten, "Symmetry and Emergence", 2018)

"The equations that really work in describing nature with the most generality and the greatest simplicity are very elegant and subtle." (Edward Witten)

"Topology is the property of something that doesn't change when you bend it or stretch it as long as you don't break anything." (Edward Witten)

"Even though it is, properly speaking, a postprediction, in the sense that the experiment was made before the theory, the fact that gravity is a consequence of string theory, to me, is one of the greatest theoretical insights ever." (Edward Witten)

"I would expect that a proper elucidation of what string theory really is all about would involve a revolution in our concepts of the basic laws of physics - similar in scope to any that occurred in the past. (Edward Witten [interview])

On Structure: Structure in Mathematics (1980-1989)

"A real change of theory is not a change of equations - it is a change of mathematical structure, and only fragments of competing theories, often not very important ones conceptually, admit comparison with each other within a limited range of phenomena." (Yuri I Manin, "Mathematics and Physics", 1981)

"Philosophical objections may be raised by the logical implications of building a mathematical structure on the premise of fuzziness, since it seems (at least superficially) necessary to require that an object be or not be an element of a given set. From an aesthetic viewpoint, this may be the most satisfactory state of affairs, but to the extent that mathematical structures are used to model physical actualities, it is often an unrealistic requirement. [...] Fuzzy sets have an intuitively plausible philosophical basis. Once this is accepted, analytical and practical considerations concerning fuzzy sets are in most respects quite orthodox." (James Bezdek, 1981)

"The formalist makes a distinction between geometry as a deductive structure and geometry as a descriptive science. Only the first is regarded as mathematical. The use of pictures or diagrams, or even mental imagery, all are non- mathematical. In principle, they should be unnecessary. Consequently. he regards them as inappropriate in a mathematics text, perhaps even in a mathematics class." (Philip J Davis & Reuben Hersh, "The Mathematical Experience", 1981)

"[…] mathematics is not just a symbolism, a set of conventions for the use of special, formal vocabularies, but is intimately connected with the structure of rational thought, with reasoning practices. [...] mathematics is not just a language, and of refusing the foundationalist move of trying to reduce mathematics to logic, instead seeing mathematics as providing rational frameworks for science, is to set science against a background of rational structures and rational methods which itself has a built-in dynamics. The rational framework of science is itself historically conditioned, for it changes with developments in mathematics." (Mary Tiles, "Bachelard: Science and Objectivity", 1984)

"Scientific laws give algorithms, or procedures, for determining how systems behave. The computer program is a medium in which the algorithms can be expressed and applied. Physical objects and mathematical structures can be represented as numbers and symbols in a computer, and a program can be written to manipulate them according to the algorithms. When the computer program is executed, it causes the numbers and symbols to be modified in the way specified by the scientific laws. It thereby allows the consequences of the laws to be deduced." (Stephen Wolfram, "Computer Software in Science and Mathematics", 1984)

"Nature is disordered, powerful and chaotic, and through fear of the chaos we impose system on it. We abhor complexity, and seek to simplify things whenever we can by whatever means we have at hand. We need to have an overall explanation of what the universe is and how it functions. In order to achieve this overall view we develop explanatory theories which will give structure to natural phenomena: we classify nature into a coherent system which appears to do what we say it does." (James Burke, "The Day the Universe Changed", 1985) 

"One cannot ‘invent’ the structure of an object. The most we can do is to patiently bring it to the light of day, with humility - in making it known, it is ‘discovered’. If there is some sort of inventiveness in this work, and if it happens that we find ourselves the maker or indefatigable builder, we are in no sense ‘making’ or ’building’ these ‘structures’. They have not waited for us to find them in order to exist, exactly as they are! But it is in order to express, as faithfully as possible, the things that we have been detecting or discovering, the reticent structure which we are trying to grasp at, perhaps with a language no better than babbling. Thereby are we constantly driven to ‘invent’ the language most appropriate to express, with increasing refinement, the intimate structure of the mathematical object, and to ‘construct’ with the help of this language, bit by bit, those ‘theories’ which claim to give a fair account of what has been apprehended and seen. There is a continual coming and going, uninterrupted, between the apprehension of things, and the means of expressing them by a language in constant state improvement [...].The sole thing that constitutes the true inventiveness and imagination of the researcher is the quality of his attention as he listens to the voices of things." (Alexander Grothendieck, "Récoltes et semailles –Rélexions et témoignage sur un passé de mathématicien", 1985)

"Somehow, after all, as the universe ebbs toward its final equilibrium in the featureless heat bath of maximum entropy, it manages to create interesting structures." (James Gleick, "Chaos: Making a New Science", 1987)

On Structure: Structure in Mathematics (1990-1999)

"[…] mathematics is not just an austere, logical structure of forbidding purity, but also a vital, vibrant instrument for understanding the world, including the workings of our minds, and this aspect of mathematics was all but lost." (Mark Kac,  "Mathematics: Tensions", 1992)

"Mathematicians apparently don’t generally rely on the formal rules of deduction as they are thinking. Rather, they hold a fair bit of logical structure of a proof in their heads, breaking proofs into intermediate results so that they don’t have to hold too much logic at once. In fact, it is common for excellent mathematicians not even to know the standard formal usage of quantifiers (for all and there exists), yet all mathematicians certainly perform the reasoning that they encode." (William P Thurston, "On Proof and Progress in Mathematics", 1994)

"The bottom line for mathematicians is that the architecture has to be right. In all the mathematics that I did, the essential point was to find the right architecture. It's like building a bridge. Once the main lines of the structure are right, then the details miraculously fit. The problem is the overall design." (Freeman J Dyson, [interview] 1994)

"The entrepreneur's instinct is to exploit the natural world. The engineer's instinct is to change it. The scientist's instinct is to try to understand it - to work out what's really going on. The mathematician's instinct is to structure that process of understanding by seeking generalities that cut across the obvious subdivisions." (Ian Stewart, "Nature's Numbers", 1995)

"Prime numbers are the most basic objects in mathematics. They also are among the most mysterious, for after centuries of study, the structure of the set of prime numbers is still not well understood […]" (Andrew Granville, 1997)

"Mathematics is a product - a discovery - of the human mind. It enables us to see the incredible, simple, elegant, beautiful, ordered structure that lies beneath the universe we live in. It is one of the greatest creations of mankind - if it is not indeed the greatest." (Keith Devlin, "Life By the Numbers", 1998)

"To some extent the beauty of number theory seems to be related to the contradiction between the simplicity of the integers and the complicated structure of the primes, their building blocks. This has always attracted people." (Andreas Knauf, "Number Theory, Dynamical Systems and Statistical Mechanics", 1998)

On Structure: Structure in Mathematics (2000-2009)

"Mathematics is not placid, static and eternal. […] Most mathematicians are happy to make use of those axioms in their proofs, although others do not, exploring instead so-called intuitionist logic or constructivist mathematics. Mathematics is not a single monolithic structure of absolute truth!" (Gregory J Chaitin, "A century of controversy over the foundations of mathematics", 2000)

"Most physical systems, particularly those complex ones, are extremely difficult to model by an accurate and precise mathematical formula or equation due to the complexity of the system structure, nonlinearity, uncertainty, randomness, etc. Therefore, approximate modeling is often necessary and practical in real-world applications. Intuitively, approximate modeling is always possible. However, the key questions are what kind of approximation is good, where the sense of 'goodness' has to be first defined, of course, and how to formulate such a good approximation in modeling a system such that it is mathematically rigorous and can produce satisfactory results in both theory and applications." (Guanrong Chen & Trung Tat Pham, "Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems", 2001)

"Our world resonates with patterns. The waxing and waning of the moon. The changing of the seasons. The microscopic cell structure of all living things have patterns. Perhaps that explains our fascination with prime numbers which are uniquely without pattern. Prime numbers are among the most mysterious phenomena in mathematics." (Manindra Agrawal, 2003)

"[…] mathematicians are much more concerned for example with the structure behind something or with the whole edifice. Mathematicians are not really puzzlers. Those who really solve mathematical puzzles are the physicists. If you like to solve mathematical puzzles, you should not study mathematics but physics!" (Carlo Beenakker, [interview] 2006)

"A good problem solver must also be a conceptual mathematician, with a good intuitive grasp of structures. But structures remain tools for the problem solver, instead of the main object of study." (David Ruelle, "The Mathematician's Brain", 2007)

"A proof in mathematics is a psychological device for convincing some person, or some audience, that a certain mathematical assertion is true. The structure, and the language used, in formulating that proof will be a product of the person creating it; but it also must be tailored to the audience that will be receiving it and evaluating it. Thus there is no ‘unique’ or ‘right’ or ‘best’ proof of any given result. A proof is part of a situational ethic." (Steven G Krantz, "The Proof is in the Pudding", 2007)

"It thus stands to reason that mathematical structures have a dual origin: in part human, in part purely logical. Human mathematics requires short formulations (because of our poor memory, etc.). But mathematical logic dictates that theorems with a short formulation may have very long proofs, as shown by Gödel. Clearly you don't want to go through the same long proof again and again. You will try instead to use repeatedly the short theorem that you have obtained. And an important tool to obtain short formulations is to give short names to mathematical objects that occur repeatedly. These short names describe new concepts. So we see how concept creation arises in the practice of mathematics as a consequence of the inherent logic of the sub ject and of the nature of human mathematicians." (David Ruelle, "The Mathematician's Brain", 2007)

"Logic moves in one direction, the direction of clarity, coherence, and structure. Ambiguity moves in the other direction, that of fluidity, openness, and release. Mathematics moves back and forth between these two poles. Mathematics is not a fixed, static entity that can be structured definitively. It is dynamic, alive: its dynamism a function of the relationship between the two poles that have been described above. It is the interactions between these different aspects that give mathematics its power." (William Byers, "How Mathematicians Think", 2007)

"Mathematics as done by mathematicians is not just heaping up statements logically deduced from the axioms. Most such statements are rubbish, even if perfectly correct. A good mathematician will look for interesting results. These interesting results, or theorems, organize themselves into meaningful and natural structures, and one may say that the object of mathematics is to find and study these structures." (David Ruelle, "The Mathematician's Brain", 2007)

"The panoply of technical tools of mathematics reflects the inside structure of mathematics and is basically all we know about this inside structure, so that building a new theory may change the way we understand the structural relations of different parts of mathematics." (David Ruelle, "The Mathematician's Brain", 2007)

"We must admit, however, that our knowledge of the logical structure of mathematics and of the workings of the human mind remain quite limited, so that we have only partial answers to some questions, while others remain quite open." (David Ruelle, "The Mathematician's Brain", 2007)

"In mathematics, beauty is a very important ingredient. Beauty exists in mathematics as in architecture and other things. It is a difficult thing to define but it is something you recognise when you see it. It certainly has to have elegance, simplicity, structure and form. All sorts of things make up real beauty. There are many different kinds of beauty and the same is true of mathematical theorems. Beauty is an important criterion in mathematics because basically there is a lot of choice in what you can do in mathematics and science. It determines what you regard as important and what is not." (Michael Atiyah, 2009)

"Philosophers have sometimes made a distinction between analytic and synthetic truths. Analytic truths are not verified by observation; true analytic statements are tautologies and are true by virtue of the definitions of their terms and their logical structure. Synthetic truths relate to the material world; the truth of synthetic statements depends on their correspondence to how physical reality works. Mathematics, according to this distinction, deals exclusively with analytic truths. Its statements are all tautologies and are (analytically) true by virtue of their adherence to formal rules of construction." (Raymond S Nickerson, "Mathematical Reasoning: Patterns, Problems, Conjectures, and Proofs", 2009)

🆆Karl E Weick - Collected Quotes

"If all of the elements in a large system are loosely coupled to one another, then any one element can adjust to and modify a local a local unique contingency without affecting the whole system. These local adaptations can be swift, relatively economical, and substantial." (Karl E Weick, "Educational organizations as loosely coupled systems", 1976)

"There is no methodological process by which one can confirm the existence of an object independent of the confirmatory process involving oneself. The outside is a void, there is only the inside. A person's world, the inside or internal view is all that can be known. The rest can only be the object of speculation." (Karl E Weick, 1977)

"In a loosely coupled system there is more room available for self-determination by the actors. If it is argued that a sense of efficacy is crucial for human beings. when a sense of efficacy might be greater in a loosely coupled system with autonomous units than it would be in a tightly coupled system where discretion is limited." (Karl E Weick, "Educational organizations as loosely coupled systems", 1976)

"Any approach to the study of organizations is built on specific assumptions about the nature of organizations and how they are designed and function." (Richard L Daft & Karl E Weick, "Toward a model of organizations as interpretation systems", Academy of Management Review Vol 9 (2), 1984)

"An ordered set of assertions about a generic behavior or structure assumed to hold throughout a significantly broad range of specific instances." (Karl E Weick, "Theory construction as disciplined imagination", 1989)

"Sensemaking is about the enlargement of small cues. It is a search for contexts within which small details fit together and make sense. It is people interacting to flesh out hunches. It is a continuous alternation between particulars and explanations with each cycle giving added form and substance to the other." (Karl E Weick, "Sensemaking in Organizations", 1995)

"Sensemaking tends to be swift, which means we are more likely to see products than processes." (Karl E Weick, Sensemaking in Organizations, 1995)

"The point we want to make here is that sensemaking is about plausibility, coherence, and reasonableness. Sensemaking is about accounts that are socially acceptable and credible... It would be nice if these accounts were also accurate. But in an equivocal, postmodern world, infused with the politics of interpretation and conflicting interests and inhabited by people with multiple shifting identities, an obsession with accuracy seems fruitless, and not of much practical help, either." (Karl E Weick, "Sensemaking in Organizations", 1995)

"To talk about sensemaking is to talk about reality as an ongoing accomplishment that takes form when people make retrospective sense of the situations in which they find themselves and their creations. There is a strong reflexive quality to this process. People make sense of things by seeing a world on which they already imposed what they believe. In other words, people discover their own inventions. This is why sensemaking can be understood as invention and interpretations understood as discovery. These are complementary ideas. If sensemaking is viewed as an act of invention, then it is also possible to argue that the artifacts it produces include language games and texts." (Karl E Weick, "Sensemaking in Organizations", 1995)

"The basic idea of sensemaking is that reality is an ongoing accomplishment that emerges from efforts to create order and make retrospective sense of what occurs." (Karl E Weick, "The collapse of sensemaking in organizations: The Mann Gulch disaster", Administrative Science Quarterly 3, 1993)

🪸Systems Thinking V

"[Systems thinking is] A new way to view and mentally frame what we see in the world; a worldview and way of thinking whereby we see the entity or unit first as a whole, with its fit and relationship to its environment as primary concerns." (Stephen G Haines, "The Managers Pocket Guide to Systems Thinking & Learning", 1998)

"The beauty of this [systems thinking] mindset is that its mental models are based on natural laws, principles of interrelationship, and interdependence found in all living systems. They give us a new view of ourselves and our many systems, from the tiniest cell to the entire earth; and as our organizations are included in that great range, they help us define organizational problems as systems problems, so we can respond in more productive ways. The systems thinking mindset is a new orientation to life. In many ways it also operates as a worldview - an overall perspective on, and understanding of, the world." (Stephen G Haines, "The Managers Pocket Guide to Systems Thinking & Learning", 1998)

"As a meta-discipline, systems science will transfer its content from discipline to discipline and address problems beyond conventional reductionist boundaries. Generalists, qualified to manage today’s problem better than the specialist, could be fostered. With these intentions, systems thinking and systems science should not replace but add, complement and integrate those aspects that seem not to be adequately treated by traditional science." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"Systems thinking expands the focus of the observer, whereas analytical thinking reduces it. In other words, analysis looks into things, synthesis looks out of them. This attitude of systems thinking is often called expansionism, an alternative to classic reductionism. Whereas analytical thinking concentrates on static and structural properties, systems thinking concentrates on the function and behaviour of whole systems. Analysis gives description and knowledge; systems thinking gives explanation and understanding." (Lars Skyttner, "General Systems Theory: Ideas and Applications", 2001)

"System Thinking is a common concept for understanding how causal relationships and feedbacks work in an everyday problem. Understanding a cause and an effect enables us to analyse, sort out and explain how changes come about both temporarily and spatially in common problems. This is referred to as mental modelling, i.e. to explicitly map the understanding of the problem and making it transparent and visible for others through Causal Loop Diagrams (CLD)." (Hördur V Haraldsson, "Introduction to System Thinking and Causal Loop Diagrams", 2004)

"[systems thinking is]  thinking holistically and conscientiously about the world by focusing on the interaction of the parts and their influence within and over the system." (Kambiz E Maani, "Systems Thinking and the Internet from Independence to Interdependence", Encyclopedia of Information Science and Technology, Second Edition, 2009)

"Systems thinking, in contrast, focuses on how the thing being studied interacts with the other constituents of the system - a set of elements that interact to produce behaviour - of which it is a part. This means that instead of isolating smaller and smaller parts of the system being studied, systems thinking works by expanding its view to take into account larger and larger numbers of interactions as an issue is being studied. This results in sometimes strikingly different conclusions than those generated by traditional forms of analysis, especially when what is being studied is dynamically complex or has a great deal of feedback from other sources, internal or external. Systems thinking allows people to make their understanding of social systems explicit and improve them in the same way that people can use engineering principles to make explicit and improve their understanding of mechanical systems." (Raed M Al-Qirem & Saad G Yaseen, "Modelling a Small Firm in Jordan Using System Dynamics" [in "Handbook of Research on Discrete Event Simulation Environments: Technologies and Applications"], 2010)

"Understanding interdependency requires a way of thinking different from analysis. It requires systems thinking. And analytical thinking and systems thinking are quite distinct. [...] Systems thinking is the art of simplifying complexity. It is about seeing through chaos, managing interdependency, and understanding choice. We see the world as increasingly more complex and chaotic because we use inadequate concepts to explain it. When we understand something, we no longer see it as chaotic or complex." (Jamshid Gharajedaghi, "Systems Thinking: Managing Chaos and Complexity A Platform for Designing Business Architecture", 2011)

"Systems thinking focuses on optimizing for the whole, looking at the overall flow of work, identifying what the largest bottleneck is today, and eliminating it." (Matthew Skelton & Manuel Pais, "Team Topologies: Organizing Business and Technology Teams for Fast Flow", 2019)

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🅱Yaneer Bar-Yamm - Collected Quotes

"A complex system is a system formed out of many components whose behavior is emergent, that is, the behavior of the system cannot be simply inferred from the behavior of its components. The amount of information necessary to describe the behavior of such a system is a measure of its complexity." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"A dictionary definition of the word ‘complex’ is: ‘consisting of interconnected or interwoven parts’ […] Loosely speaking, the complexity of a system is the amount of information needed in order to describe it. The complexity depends on the level of detail required in the description. A more formal definition can be understood in a simple way. If we have a system that could have many possible states, but we would like to specify which state it is actually in, then the number of binary digits (bits) we need to specify this particular state is related to the number of states that are possible." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"Many of the systems that surround us are complex. The goal of understanding their properties motivates much if not all of scientific inquiry. […] all scientific endeavor is based, to a greater or lesser degree, on the existence of universality, which manifests itself in diverse ways. In this context, the study of complex systems as a new endeavor strives to increase our ability to understand the universality that arises when systems are highly complex." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"There are two approaches to organizing the properties of complex systems that will serve as the foundation of our discussions. The first of these is the relationship between elements, parts and the whole. Since there is only one property of the complex system that we know for sure - that it is complex - the primary question we can ask about this relationship is how the complexity of the whole is related to the complexity of the parts. […] The second approach to the study of complex systems begins from an understanding of the relationship of systems to their descriptions. The central issue is defining quantitatively what we mean by complexity."  (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"Traditional geometry is the study of the properties of spaces or objects that have integral dimensions. This can be generalized to allow effective fractional dimensions of objects, called fractals, that are embedded in an integral dimension space. […] Fractals are often defined as geometric objects whose spatial structure is self-similar. This means that by magnifying one part of the object, we find the same structure as of the original object. The object is characteristically formed out of a collection of elements: points, line segments, planar sections or volume elements. These elements exist in a space of the same or higher dimension to the elements themselves." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"When the behavior of the system depends on the behavior of the parts, the complexity of the whole must involve a description of the parts, thus it is large. The smaller the parts that must be described to describe the behavior of the whole, the larger the complexity of the entire system. […] A complex system is a system formed out of many components whose behavior is emergent, that is, the behavior of the system cannot be simply inferred from the behavior of its components." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"When we think about methodology, we must keep purpose in mind. Our purpose in studying complex systems is to extract general principles. General principles can take many forms. Most principles are articulated as relationships between properties - when a system has the property x, then it has the property y. When possible, relationships should be quantitative and expressed as equations. In order to explore such relationships, we must construct and study mathematical models. Asking why the property x is related to the property y requires an understanding of alternatives. What else is possible?  As a bonus, when we are able to generate systems with various properties, we may also be able to use them for practical applications." (Yaneer Bar-Yamm, "Dynamics of Complexity", 1997)

"Although complexity is very important for survival, scale also matters. In general, larger scale challenges should be met with larger scale responses. The rule of thumb is that the complexity of the organism has to match the complexity of the environment at all scales in order to increase the likelihood of survival." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"Complex problems are the problems that persist - the problems that bounce back and continue to haunt us. People often go through a series of stages in dealing with such problems - from believing they are beyond hope, to galvanizing collective efforts of many people and dollars to address the problem, to despair, retreat, and rationalization." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"Descriptions underlie everything from science to art. Science explores the descriptions we share (or should share) when we look at the world. Art explores the differences between the descriptions that exist in each of our minds. Thinking is always about descriptions even when we don’t realize it because what we have in our minds is a kind of description, not the system itself." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"If the degree of complexity is relative, our job is to describe how different observers measure complexity. Each observer considers the complexity of a system to be the length of a description that he needs to describe the system. Because of differences in the observers the length of their descriptions differ. The trick is to understand the systematic way the lengths differ so that this variation can be part of our understanding. In this section we focus on what happens when observers use different languages." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"The notion that complexity is measured by the length of the description. […] The idea that complexity is not an absolute, but is relative to who is giving the description and who is receiving the description should not discourage us from thinking about complexity. Descriptions are always relative to the observer and this is already recognized in basic physics." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"There is no doubt that science has made great progress by taking things apart, but it has become increasingly clear that many important questions can only be addressed by thinking more carefully about relationships between and amongst the parts. Indeed, one of the main difficulties in answering questions or solving problems - any kind of problem - is that we think the problem is in the parts, when it is really in the relationships between them." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"What do people do today when they don’t understand 'the system'? They try to assign responsibility to someone to fix the problem, to oversee 'the system', to coordinate and control what is happening. It is time we recognized that 'the system' is how we work together. When we don’t work together effectively putting someone in charge by its very nature often makes things worse, rather than better, because no one person can understand 'the system' well enough to be responsible. We need to learn how to improve the way we work together, to improve 'the system' without putting someone in charge, in order to make things work." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

"When parts are acting independently, the fine scale behavior is more complex. When they are working together, the fine scale complexity is much smaller, but the behavior is on a larger scale. This means that complexity is always a trade-off, more complex at a large scale means simpler at a fine scale. This trade-off is a basic conceptual tool that we need in order to understand complex systems." (Yaneer Bar-Yam, "Making Things Work: Solving Complex Problems in a Complex World", 2004)

🪷On Mind: Mental Models LXII

"A mental model is a collection of 'connected' autonomous objects. Running  a mental model corresponds to modifying the parameters of the model by propagating information using the internal rules and specified topology. Running a mental model can also occur when autonomous objects change state. For us the definition of state is distinct from the current parameter values of an object. A state change consists of the replacement of one set of behavior rules with another." (Michael D Williams et al, "Human Reasoning About a Simple Physical System", [in "Mental Models", Ed(s). Dedre Gentner & Albert L Stevens], 1983)

"Central to this conception of mental models is the notion of autonomous objects. An autonomous object is a mental object with an explicit representation of state, an explicit representation of its topological connections to other objects, and a set of internal parameters. Associated with each autonomous object is a set of rules which modify its parameters and thus specify its behavior." (Michael D Williams et al, "Human Reasoning About a Simple Physical System", [in "Mental Models", Ed(s). Dedre Gentner & Albert L Stevens], 1983)

"In the consideration of mental models we need really consider four different things: the target system, the conceputal model of that target system, the user’s mental model of the target system, and the scientist's conceptualization of that mental model. The system that the person is learning or using is, by definition, the target system. A conceptual model is invented to provide an appropriate representation of the target system, appropriate in the sense of being accurate, consistent, and complete." (Donald A Norman, "Some Observations on Mental Models" [in "Mental Models", Ed(s). Dedre Gentner & Albert L Stevens], 1983)

"The purpose of a mental model is to allow the person to understand and to anticipate the behavior of a physical system. This means that the model must have predictive power, either by applying rules of inference or by procedural derivation (in whatever manner these properties may be realized in a person); in other words, it should be possible for people to ' run' their models mentally. This means that the conceptual mental model must also include a model of the relevant human information processing and knowledge structures that make it possible for the person to use a mental model to predict and understand the physical system." (Donald A Norman, "Some Observations on Mental Models" [in "Mental Models"], Ed(s). Dedre Gentner & Albert L Stevens], 1983)

"From a functional point of view, mental models can be described as symbolic structures which permit people: to generate descriptions of the purpose of a system, to generate descriptions of the architecture of a system, to provide explanations of the state of a system, to provide explanations of the functioning of a system, to make predictions of future states of a system." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"Under the label 'cognitive maps', mental models have been conceived of as the mental representation of spatial aspects of the environment. A mental model, in this sense, comprises the topology of an area, including relevant districts, landmarks, and paths. [...] Under the label 'naive physics', mental models have been conceived of as the mental representation of natural or technical systems. A mental model, in this sense, comprises the effective determinants, true or not, of the functioning of a physical system. [...] Under the label 'model based reasoning', the mental models notion is featured in yet another area of cognitive science - deductive reasoning. In contrast to the commonly held view that logical competence depends on formal rules of deduction, it has been argued that reasoning is a semantic process based on the manipulation of mental models. [...] Finally, under terms like 'discourse model', 'situation model', or 'scenario', mental models have been conceived of as the mental representation of a verbal description of some real or fictional state of affairs. The role of mental models in the comprehension of discourse is discussed in more detail below." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"A mental model is an internal representation with analogical relations to its referential object, so that local and temporal aspects of the object are preserved. It comes somewhat close to the mental images people report having in their minds whilst processing information. The great advantage of the notion of mental models, however, is its ability to include the notion of a partner model and the notion of a situation model. Thus, mental models can build a bridge to the other two dimensions of communication, namely interaction and situation." (Gert Rickheit et al, "The concept of communicative competence" [in "Handbook of Communication Competence"], 2008)

"Because all mental models or mindsets are incomplete, we can engage in second-order studies, evaluations, judgments, and assessments about our own and other operative mental models. Of course this is highly complex since the act of reflection is itself a further of framing or reframing." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"Mental models bind our awareness within a particular scaffold and then selectively can filter the content we subsequently receive. Through recalibration using revised mental models, we argue, we cultivate strategies anew, creating new habits, and galvanizing more intentional and evolved mental models. This recalibration often entails developing a strong sense of self and self-worth, realizing that each of us has a range of moral choices that may deviate from those in authority, and moral imagination." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"These framing perspectives or mental models construe the data of our experiences, and it is the construed data that we call 'facts'. What we often call reality, or the world, is constructed or socially construed in certain ways such that one cannot get at the source of the data except through these construals." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

🆆Patricia H Werhan - Collected Quotes

"[...] each of us frames, orders and/or organizes our experiences in terms of socially learned incomplete mental models or mind sets that shape our experiences perspectivally. These mental models are constitutive of all our experiences. They are the ways in which we make sense of our experiences [...]" (Patricia H Werhane "A Place for Philosophers in Applied Ethics and the Role of Moral Reasoning in Moral Imagination", Business Ethics Quarterly 16 (3), 2007)

"The most serious problem in applied ethics, or at least in business ethics, is not that we frame experiences; it is not that these mental models are incomplete, sometimes biased, and surely parochial. The larger problem is that most of us either individually or as managers do not realize that we are framing, disregarding data, ignoring counterevidence, or not taking into account other points of view." (Patricia H Werhane "A Place for Philosophers in Applied Ethics and the Role of Moral Reasoning in Moral Imagination", Business Ethics Quarterly 16 (3), 2007)

"Although good ethical decision-making requires us carefully to take into account as much relevant information as is available to us, we have good reason to think that we commonly fall well short of this standard – either by overlooking relevant facts completely or by underestimating their significance. The mental models we employ can contribute to this problem. As we have explained, mental models frame our experiences in ways that both aid and hinder our perceptions. They enable us to focus selectively on ethically relevant matters. By their very nature, they provide incomplete perspectives, resulting in bounded awareness and bounded ethicality. Insofar as our mental modeling practices result in unwarranted partiality, or even ethical blindness, the desired reflective process is distorted. This distortion is aggravated by the fact that our mental models can have this distorting effect without our consciously realizing it. Thus, although we cannot do without mental models, they leave us all vulnerable to blindness and, insofar as we are unaware of this, self-deception." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"Because all mental models or mindsets are incomplete, we can engage in second-order studies, evaluations, judgments, and assessments about our own and other operative mental models. Of course this is highly complex since the act of reflection is itself a further of framing or reframing." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"It is important to emphasize that the dangers that certain mental models pose to ethical decision-making cannot be mitigated or overcome by imagining that we could somehow free ourselves of the need for mental models altogether. Without mental models to mediate and shape our experiences, we would be incapable of having experiences at all." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"Mental models bind our awareness within a particular scaffold and then selectively can filter the content we subsequently receive. Through recalibration using revised mental models, we argue, we cultivate strategies anew, creating new habits, and galvanizing more intentional and evolved mental models. This recalibration often entails developing a strong sense of self and self-worth, realizing that each of us has a range of moral choices that may deviate from those in authority, and moral imagination." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"Mental models serve to conceptualize, focus and shape our experiences, but in so doing, they sometimes cause us to ignore data and occlude critical reflection that might be relevant or, indeed, necessary to practical decision-making. [...] distorting mental models are the foundation or underpinning of many of the impediments to effective ethical decision-making." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"These framing perspectives or mental models construe the data of our experiences, and it is the construed data that we call 'facts'. What we often call reality, or the world, is constructed or socially construed in certain ways such that one cannot get at the source of the data except through these construals." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"Various scientific methodologies are themselves mental models through which scientists discover, predict, and hypothesize about what we then call reality. In the social constructionist paradigm such mental models frame all our experiences. They schematize, and otherwise facilitate and guide the ways in which we recognize, react, and organize the world. How we define the world is dependent on such schema and thus all realities are socially structured. In the socially constructed paradigm, the multivariate mental models or conceptual schema are the means and mode through which we constitute our experiences." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

"We identify and analyze distorting mental models that constitute experience in a manner that occludes the moral dimension of situations from view, thereby thwarting the first step of ethical decision-making. Examples include an unexamined moral self-image, viewing oneself as merely a bystander, and an exaggerated conception of self-sufficiency. These mental models, we argue, generate blind spots to ethics, in the sense that they limit our ability to see facts that are right before our eyes – sometimes quite literally, as in the many examples of managers and employees who see unethical behavior take place in front of them, but do not recognize it as such." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)

🆁Gert Rickheit - Collected Quotes

"According to the representational format claim, images constitute a class of mental models that is particularly suited to represent visually perceptible information. More specifically, an image can be conceived of as a viewer centered projection of an underlying mental model which, in turn, represents spatiotemporal aspects of external objects or events. Unlike propositional or network representations, images depict, rather than describe, a particular state of affairs." (Gert Rickheit & Lorenz Sichelschmidt, „Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"From a functional point of view, mental models can be described as symbolic structures which permit people: to generate descriptions of the purpose of a system, to generate descriptions of the architecture of a system, to provide explanations of the state of a system, to provide explanations of the functioning of a system, to make predictions of future states of a system." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"In broad terms, a mental model is to be understood as a dynamic symbolic representation of external objects or events on the par. t of some natural or artificial cognitive system. Mental models are thought to have certain properties which make them stand out against other forms of symbolic representations." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"In order to be able to embrace a multitude of external situations, mental models must cope with a variety of representational formats - from quasi-verbal propositions to quasi-pictorial images."  (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"In the end, structural analogy may turn out to be the defining characteristic of mental models. Provided that the modeling function is specified with respect to the aspects figured and the aspects disregarded, and provided that there is sufficient circumstantial evidence for assuming a correspondence in structure between an external situation and its internal representation, regarding mental models as a unique form of symbolic representation may be justified." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"The major problem of the mental model approach lies in the fact that the external world is to be represented in a highly specific way. Representing indeterminacy in terms of mental models thus poses difficulties, casting some doubt on the contention that mental models can do without variables." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"Under the label 'cognitive maps', mental models have been conceived of as the mental representation of spatial aspects of the environment. A mental model, in this sense, comprises the topology of an area, including relevant districts, landmarks, and paths. [...] Under the label 'naive physics', mental models have been conceived of as the mental representation of natural or technical systems. A mental model, in this sense, comprises the effective determinants, true or not, of the functioning of a physical system. [...] Under the label 'model based reasoning', the mental models notion is featured in yet another area of cognitive science - deductive reasoning. In contrast to the commonly held view that logical competence depends on formal rules of deduction, it has been argued that reasoning is a semantic process based on the manipulation of mental models. [...] Finally, under terms like 'discourse model', 'situation model', or 'scenario', mental models have been conceived of as the mental representation of a verbal description of some real or fictional state of affairs. The role of mental models in the comprehension of discourse is discussed in more detail below." (Gert Rickheit & Lorenz Sichelschmidt, "Mental Models: Some Answers, Some Questions, Some Suggestions", 1999)

"A mental model is an internal representation with analogical relations to its referential object, so that local and temporal aspects of the object are preserved. It comes somewhat close to the mental images people report having in their minds whilst processing information. The great advantage of the notion of mental models, however, is its ability to include the notion of a partner model and the notion of a situation model. Thus, mental models can build a bridge to the other two dimensions of communication, namely interaction and situation." (Gert Rickheit et al, "The concept of communicative competence" [in "Handbook of Communication Competence"], 2008)