♾️Cognitive Science: On Collective Intelligence (Quotes)

"We must therefore establish a form of decision-making in which voters need only ever pronounce on simple propositions, expressing their opinions only with a yes or a no. […] Clearly, if anyone’s vote was self-contradictory (intransitive), it would have to be discounted, and we should therefore establish a form of voting which makes such absurdities impossible." (Nicolas de Condorcet, "On the form of decisions made by plurality vote", 1788)

"Collective wisdom, alas, is no adequate substitute for the intelligence of individuals. Individuals who opposed received opinions have been the source of all progress, both moral and intellectual. They have been unpopular, as was natural." (Bertrand Russell, "Why I Am Not a Christian", 1927)

"The collective intelligence of any group of people who are thinking as a 'herd' rather than individually is no higher than the intelligence of the stupidest members." (Mary Day Winn, "Adam's Rib", 1931)

"Learning is a property of all living organisms. […] Since organized groups can be looked upon as living entities, they can be expected to exhibit learning […]" (Winfred B. Hirschmann, "Profit from the Learning Curve", Harvard Business Review, 1964)

"A cardinal principle in systems theory is that all parties that have a stake in a system should be represented in its management." (Malcolm S Knowles, "The Adult Learner", 1973)

"Collective intelligence emerges when a group of people work together effectively. Collective intelligence can be additive (each adds his or her part which together form the whole) or it can be synergetic, where the whole is greater than the sum of its parts." (Trudy and Peter Johnson-Lenz, "Groupware: Orchestrating the Emergence of Collective Intelligence", cca. 1980)

"Cybernetic information theory suggests the possibility of assuming that intelligence is a feature of any feedback system that manifests a capacity for learning." (Paul Hawken et al, "Seven Tomorrows", 1982)

"The concept of organizational learning refers to the capacity of organizational complexes to develop experiential knowledge, instincts, and 'feel' or intuition which are greater than the combined knowledge, skills and instincts of the individuals involved." (Don E. Kash, "Perpetual Innovation", 1989)

"We haven't worked on ways to develop a higher social intelligence […] We need this higher intelligence to operate socially or we're not going to survive. […] If we don't manage things socially, individual high intelligence is not going to make much difference. [...] Ordinary thought in society is incoherent - it is going in all sorts of directions, with thoughts conflicting and canceling each other out. But if people were to think together in a coherent way, it would have tremendous power." (David Bohm, "New Age Journal", 1989)

"Civilization is to groups what intelligence is to individuals. It is a means of combining the intelligence of many to achieve ongoing group adaptation. […] Civilization, like intelligence, may serve well, serve adequately, or fail to serve its adaptive function. When civilization fails to serve, it must disintegrate unless it is acted upon by unifying internal or external forces." (Octavia E Butler, "Parable of the Sower", 1993)

"Great leaders reinforce the idea that accomplishment in our society comes from great individual acts. We credit individuals for outcomes that required teams and communities to accomplish." (Peter Block, "Stewardship", 1993)

"We must learn to think together in an integrated, synergistic fashion, rather than in fragmented and competitive ways." (Joanna Macy, Noetic Sciences Bulletin, 1994-1995)

"The leading edge of growth of intelligence is at the cultural and societal level. It is like a mind that is struggling to wake up. This is necessary because the most difficult problems we face are now collective ones. They are caused by complex global interactions and are beyond the scope of individuals to understand and solve. Individual mind, with its isolated viewpoints and narrow interests, is no longer enough." (Jeff Wright, "Basic Beliefs", [email] 1995)

"It [collective intelligence] is a form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills. I'll add the following indispensable characteristic to this definition: The basis and goal of collective intelligence is mutual recognition and enrichment of individuals rather than the cult of fetishized or hypostatized communities." (Pierre Levy, "Collective Intelligence", 1999)

The three basic mechanisms of averaging, feedback and division of labor give us a first idea of a how a CMM [Collective Mental Map] can be developed in the most efficient way, that is, how a given number of individuals can achieve a maximum of collective problem-solving competence. A collective mental map is developed basically by superposing a number of individual mental maps. There must be sufficient diversity among these individual maps to cover an as large as possible domain, yet sufficient redundancy so that the overlap between maps is large enough to make the resulting graph fully connected, and so that each preference in the map is the superposition of a number of individual preferences that is large enough to cancel out individual fluctuations. The best way to quickly expand and improve the map and fill in gaps is to use a positive feedback that encourages individuals to use high preference paths discovered by others, yet is not so strong that it discourages the exploration of new paths." (Francis Heylighen, "Collective Intelligence and its Implementation on the Web", 1999)

"With the growing interest in complex adaptive systems, artificial life, swarms and simulated societies, the concept of “collective intelligence” is coming more and more to the fore. The basic idea is that a group of individuals (e. g. people, insects, robots, or software agents) can be smart in a way that none of its members is. Complex, apparently intelligent behavior may emerge from the synergy created by simple interactions between individuals that follow simple rules." (Francis Heylighen, "Collective Intelligence and its Implementation on the Web", 1999)

"Cultures are never merely intellectual constructs. They take form through the collective intelligence and memory, through a commonly held psychology and emotions, through spiritual and artistic communion." (Tariq Ramadan, "Islam and the Arab Awakening", 2012)

"[…] recent researchers in artificial intelligence and computational methods use the term swarm intelligence to name collective and distributed techniques of problem solving without centralized control or provision of a global model. […] the intelligence of the swarm is based fundamentally on communication. […] the member of the multitude do not have to become the same or renounce their creativity in order to communicate and cooperate with each other. They remain different in terms of race, sex, sexuality and so forth. We need to understand, then, is the collective intelligence that can emerge from the communication and cooperation of such varied multiplicity." (Antonio Negri, "Multitude: War and Democracy in the Age of Empire", 2004)

"Collective Intelligence (CI) is the capacity of human collectives to engage in intellectual cooperation in order to create, innovate, and invent." (Pierre Levy, "Toward a Self-referential Collective Intelligence", 2009)

"How is it that an ant colony can organize itself to carry out the complex tasks of food gathering and nest building and at the same time exhibit an enormous degree of resilience if disrupted and forced to adapt to changing situations? Natural systems are able not only to survive, but also to adapt and become better suited to their environment, in effect optimizing their behavior over time. They seemingly exhibit collective intelligence, or swarm intelligence as it is called, even without the existence of or the direction provided by a central authority." (Michael J North & Charles M Macal, "Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation", 2007)

"Some paths to superintelligence require great resources and are therefore likely to be the preserve of large well-funded projects. Whole brain emulation, for instance, requires many different kinds of expertise and lots of equipment. Biological intelligence enhancements and brain–computer interfaces would also have a large scale factor: while a small biotech firm might invent one or two drugs, achieving superintelligence along one of these paths (if doable at all) would likely require many inventions and many tests, and therefore the backing of an industrial sector or a well-funded national program. Achieving collective superintelligence by making organizations and networks more efficient requires even more extensive input, involving much of the world economy." (Nick Bostrom, "Superintelligence: Paths, Dangers, Strategies", 2014)

"By analyzing patterns in crowd behavior and honing methods of gauging fitness - or at least extricating it from popularity - the market can effectively use collective intelligence so that the cream always rises to the top." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)

❄️Systems Thinking: On Ecology (Quotes)

"[…] for as all organic beings are striving, it may be said, to seize on each place in the economy of nature, if any one species does not become modified and improved in a corresponding degree with its competitors, it will soon be exterminated." (Charles Darwin, "On the Origin of Species", 1859)

"Let it be borne in mind how infinitely complex and close-fitting are the mutual relations of all organic beings to each other and to their physical conditions of life. " (Charles Darwin, "On the Origin of Species", 1859)

"[…] without the theory of evolution all the big general series of phenomena of organic nature remain completely incomprehensible and inexplicable riddles, while by means of this theory they can be explained simply and consistently. This holds especially true for two complexes of biological phenomena which we now in conclusion wish to single out in a few words. These form the subject of two special branches of physiology which so far have been largely neglected, namely, the ecology and chorology of organisms." (Ernst Haeckel, "Generelle Morphologie der Organismen", 1866)

"By ecology we mean the body of knowledge concerning the economy of nature - the investigation of the total relations of the animal both to its inorganic and to its organic environment; including, above all, its friendly and inimical relations with those animals and plants with which it comes directly or indirectly into contact - in a word, ecology is the study of all those complex interrelations referred to by Darwin as the conditions of the struggle for existence." (Ernst Haeckel, [lecture] 1869)

 

"[employment of] exact or mathematical methods […] unfortunately is impossible in most branches of science (particularly in biology), because the empirical foundations are much too imperfect and the present problems much too complicated. Mathematical treatment of these does more harm than good because it gives a deceptive semblance of certainty which is not actually attainable. Part of physiology also involves problems which are difficult or impossible to resolve exactly, and these include the chorology and ecology of plankton." (Ernst Haeckel, “Plantonic studies”, 1891) 

"At a time when ecology and genetics are each racing swiftly towards one new concept after another, yet with little contact of thought between the two subjects, there may be some advantage in surveying, if only synoptically and in preliminary fashion, the largely uncharted territory between them." (Charles S Elton, 1938)

"If there are favourable habitats and favorable forms of association for animals and plants, as ecology demonstrates, why not for men? If each particular natural environment has has its own balance; is there not perhaps an equivalent of this in culture?" (Lewis Mumford, "The Culture of Cities", 1938)

"That land is a community is the basic concept of ecology, but that land is to be loved and respected is an extension of ethics." (Aldo Leopold, "A Sand County Almanac", 1949)

"In calling society an ecological system we are not merely using an analogy; society is an example of the general concept of an 'ecosystem' that is, an ecological system of which biological systems - forests, fields, swamps - are other examples." (Kenneth E Boulding, "A Reconstruction of Economics", 1950)

"The general study of the equilibria and dynamics of populations seems to have no name; but as it has probably reached its highest development in the biological study known as 'ecology,' this name may well be given to it." (Kenneth E Boulding, "A Reconstruction of Economics", 1950)

"Can any of us fix anything? No. None of us can do that. We're specialized. Each one of us has his own line, his own work. I understand my work, you understand yours. The tendency in evolution is toward greater and greater specialization. Man's society is an ecology that forces adaptation to it. Continued complexity makes it impossible for us to know anything outside our own personal field — I can't follow the work of the man sitting at the next desk over from me. Too much knowledge has piled up in each field. And there are too many fields. (Philip K. Dick, "The Variable Man", 1952)

If we have been slow to develop the general concepts of ecology and conservation, we have been even more tardy in recognizing the facts of the ecology and conservation of man himself. We may hope that this will be the next major phase in the development of biology. Here and there awareness is growing that man, far from being the overlord of all creation, is himself part of nature, subject to the same cosmic forces that control all other life. Man's future welfare and probably even his survival depend upon his learning to live in harmony, rather than in combat, with these forces. (Rachel Carson, "Essay on the Biological Sciences" in Good Reading, 1958)

"The thing the ecologically illiterate don't realize about an ecosystem is that it's a system. A system! A system maintains a certain fluid stability that can be destroyed by a misstep in just one niche. A system has order, a flowing from point to point. If something dams the flow, order collapses. The untrained miss the collapse until too late. That's why the highest function of ecology is the understanding of consequences." (Frank Herbert, "Dune", 1965)

"Evolution cannot be understood except in the frame of ecosystems." (Ramón Margalef, "Perspectives in Ecological Theory", 1968)

"For some years now the activity of the artist in our society has been trending more toward the function of the ecologist: one who deals with environmental relationships. Ecology is defined as the totality or pattern of relations between organisms and their environment. Thus the act of creation for the new artist is not so much the invention of new objects as the revelation of previously unrecognized relation- ships between existing phenomena, both physical and metaphysical. So we find that ecology is art in the most fundamental and pragmatic sense, expanding our apprehension of reality." (Gene Youngblood, "Expanded Cinema", 1970) 

"Ecology is the scientific study of the interactions that determine the distribution and abundance of organisms." (Charles J Krebs, "Ecology", 1972)

"To do science is to search for repeated patterns, not simply to accumulate facts, and to do the science of geographical ecology is to search for patterns of plants and animal life that can be put on a map." (Robert H. MacArthur, "Geographical Ecology", 1972)

"It is the intertwined and interacting mechanisms of evolution and ecology, each of which is at the same time a product and a process, that are responsible for life as we see it, and as it has been." (James W. Valentine, "Evolutionary Paleoecology of the Marine Biosphere", 1973)

"This paper introduces a concept of organizational ecology. This refers to the organizational field created by a number of organizations, whose interrelations compose a system at the level of the field as a whole. The overall field becomes the object of inquiry, not the single organization as related to its organization-set. The emergence of organizational ecology from earlier organization theory is traced and illustrated from empirical studies. Its relevance to the task of institution-building, in a world in which the environment has become exceedingly complex and more interdependent, is argued." (Eric Trist , "A concept of organizational eecolog", Australian journal of management 2 (2), 1977)

"We argue that in order to deal with the various inertial pressures the adaptation perspective must be supplemented with a selection orientation. We consider first two broad issues that are preliminary to ecological modelling. The first concerns appropriate units of analysis. Typical analyses of the relation of organizations to environments take the point of view of a single organization facing an environment." (Michael T Hannan, "The Population Ecology of Organizations", 1977)

"The social dynamics of human history, even more than that of biological evolution, illustrate the fundamental principle of ecological evolution - that everything depends on everything else. The nine elements that we have described in societal evolution of the three families of phenotypes - the phyla of things, organizations and people, the genetic bases in knowledge operating through energy and materials to produce phenotypes, and the three bonding relations of threat, integration and exchange - all interact on each other." (Kenneth E Boulding, "Ecodynamics: A New Theory Of Societal Evolution", 1978)

"The world is a complex, interconnected, finite, ecological–social–psychological–economic system. We treat it as if it were not, as if it were divisible, separable, simple, and infinite. Our persistent, intractable global problems arise directly from this mismatch." (Donella Meadows,"Whole Earth Models and Systems", 1982)

"Ultimately, uncontrolled escalation destroys a system. However, change in the direction of learning, adaptation, and evolution arises from the control of control, rather than unchecked change per se. In general, for the survival and co-evolution of any ecology of systems, feedback processes must be embodied by a recursive hierarchy of control circuits." (Bradford P Keeney, "Aesthetics of Change", 1983)

"Scientific ecology works along a very great number of different lines - perhaps a typical feature of this discipline. In ecological research each element of these different approaches to work and the of the varied opinions formed about them plays its part. (Wolfgang Haber, Universitas: A Quarterly German Review of the Arts and Sciences Vol. 26, (2), 1984)

"The ecological principle of unity in diversity grades into a richly mediated social principle; hence my use of the term social ecology." (Murray Bookchin,"What Is Social Ecology?" , 1984)

"The existing literature usually stresses the capacity of organizations to learn about and adapt to uncertain, changing environments. We think this emphasis is misplaced. The most important issues about the applicability of evolutionary-ecological theories to organizations concern the timing of changes. Learning and adjusting structure enhance the chance of survival only if the speed of response is commensurate with the temporal patterns of relevant environments." (Michael T Hannan,"Organizational ecology", 1989)

"To halt the decline of an ecosystem, it is necessary to think like an ecosystem." (Douglas P Wheeler, EPA Journal, 1990)

"Ecological Economics studies the ecology of humans and the economy of nature, the web of interconnections uniting the economic subsystem to the global ecosystem of which it is a part." (Robert Costanza, "Ecological Economics: the science and management of sustainability", 1992)

"When the study of the household (ecology) and the management of the household (economics) can be merged, and when ethics can be extended to include environmental as well as human values, then we can be optimistic about the future of humankind. Accordingly, bringing together these three 'E's' is the ultimate holism and the great challenge for our future." (Eugene Odum," Ecology and our endangered life-support systems", 1993)

"Progressively higher levels of organization are attained as catalytic cycles on one level interlock and form hypercycles: these are systems on a higher level of organization. Thus molecules emerge from a combination of chemically active atoms; protocells emerge from sequences of complex molecules; eukaryotic cells emerge among the prokaryotes; metazoa make their appearance among the protozoa and converge in still higher-level ecological and social systems." (Ervin László,"Vision 2020: Reordering Chaos for Global Survival" , 1994)

"The new paradigm may be called a holistic world view, seeing the world as an integrated whole rather than a dissociated collection of parts. It may also be called an ecological view, if the term 'ecological' is used in a much broader and deeper sense than usual. Deep ecological awareness recognizes the fundamental interdependence of all phenomena and the fact that, as individuals and societies we are all embedded in (and ultimately dependent on) the cyclical process of nature." (Fritjof Capra & Gunter A. Pauli," Steering business toward sustainability", 1995)

"In the past several years, social work has increasingly focused on an ecological model. This model integrates both treatment and reform by conceptualizing and emphasizing the dysfunctional transactions between people and their physical and social environments. Human beings are viewed as developing and adapting through transactions with all elements of their environments. An ecological model gives attention to both internal and external factors. It does not view people as passive reactors to their environments but, rather, as being involved in dynamic and reciprocal interactions with them." (Charles Zastrow, "The practice of social work", 1995)

"Economics emphasizes competition, expansion, and domination; ecology emphasizes cooperation, conservation, and partnership. (Fritjof Capra, "The Web of Life", 1996)

"A major clash between economics and ecology derives from the fact that nature is cyclical, whereas our industrial systems are linear. Our businesses take resources, transform them into products plus waste, and sell the products to consumers, who discard more waste […]" (Fritjof Capra, "The Web of Life", 1996)

"These, then, are some of the basic principles of ecology - interdependence, recycling, partnership, flexibility, diversity, and, as a consequence of all those, sustainability... the survival of humanity will depend on our ecological literacy, on our ability to understand these principles of ecology and live accordingly."(Fritjof Capra, "The Web of Life", 1996)

"Understanding ecological interdependence means understanding relationships. It requires the shifts of perception that are characteristic of systems thinking—from the parts to the whole, from objects to relationships, from contents to patterns. [...] Nourishing the community means nourishing those relationships. (Fritjof Capra, "The Web of Life", 1996)

"Ecology, as it is currently practiced, sometimes deals with human impacts on ecosystems, but the more common tendency is to stick to 'natural' systems."(Robert Costanza & Janis King, "The first decade of ecological economics", Ecological Economics 28 (1), 1999)

"Ecological rationality uses reason – rational reconstruction – to examine the behavior of individuals based on their experience and folk knowledge, who are ‘naïve’ in their ability to apply constructivist tools to the decisions they make; to understand the emergent order in human cultures; to discover the possible intelligence embodied in the rules, norms and institutions of our cultural and biological heritage that are created from human interactions but not by deliberate human design. People follow rules without being able to articulate them, but they can be discovered." (Vernon L Smith, "Constructivist and ecological rationality in economics",  2002)

"Organizations need to undergo fundamental changes, both in order to adapt to the new business environment and to become ecologically sustainable." (Fritjof Capra, "The Hidden Connections", 2002)

"Ecology, on the other hand, is messy. We cannot find anything deserving of the term law, not because ecology is less developed than physics, but simply because the underlying phenomena are more chaotic and hence less amenable to description via generalization." (Lev Ginzburg & Mark Colyvan," Ecological Orbits: How Planets Move and Populations Grow", 2004)

"Limiting factors in population dynamics play the role in ecology that friction does in physics. They stop exponential growth, not unlike the way in which friction stops uniform motion. Whether or not ecology is more like physics in a viscous liquid, when the growth-rate-based traditional view is sufficient, is an open question. We argue that this limit is an oversimplification, that populations do exhibit inertial properties that are noticeable. Note that the inclusion of inertia is a generalization—it does not exclude the regular rate-based, first-order theories. They may still be widely applicable under a strong immediate density dependence, acting like friction in physics." (Lev Ginzburg & Mark Colyvan, "Ecological Orbits: How Planets Move and Populations Grow", 2004)

"It is science that brings us an understanding of the true complexity of natural systems. The insights from the science of ecology are teaching us how to work with the checks and balances of nature, and encouraging a new, rational, limited-input, environmentally sound means of vineyard management that offers a third way between the ideologically driven approach of Biodynamics and conventional chemical-based agricultural systems." (Jamie Goode," The Science of Wine: From Vine to Glass", 2005)

"An ecology provides the special formations needed by organizations. Ecologies are: loose, free, dynamic, adaptable, messy, and chaotic. Innovation does not arise through hierarchies. As a function of creativity, innovation requires trust, openness, and a spirit of experimentation - where random ideas and thoughts can collide for re-creation." (George Siemens, "Knowing Knowledge", 2006)

"Knowledge flow can be likened to a river that meanders through the ecology of an organization. In certain areas, the river pools and in other areas it ebbs. The health of the learning ecology of the organization depends on effective nurturing of flow." (George Siemens, "Knowing Knowledge", 2006)

"Nodes and connectors comprise the structure of a network. In contrast, an ecology is a living organism. It influences the formation of the network itself." (George Siemens, "Knowing Knowledge", 2006)

"[ecology:] the scientific study of the distribution and abundance of organisms and the interactions that determine distribution and abundance." (Michael Begon et al, "Ecology: From individuals to ecosystems", 2006)

"The living world can be viewed as a biological hierarchy that starts with subcellular particles, and continues up through cells, tissues and organs. Ecology deals with the next three levels: the individual organism, the population (consisting of individuals of the same species) and the community (consisting of a greater or lesser number of species populations). At the level of the organism, ecology deals with how individuals are affected by (and how they affect) their environment. At the level of the population, ecology is concerned with the presence or absence of particular species, their abundance or rarity, and with the trends and fluctuations in their numbers. Community ecology then deals with the composition and organization of ecological communities." (Michael Begon et al, "Ecology: From individuals to ecosystems", 2006)

"We need to renegotiate our contract with nature. Ecology is a unifying force that can diminish intolerance and expand our empathy towards others - both human and animal." (Gregory Colbert, "Peace and Harmony: The Message of Our Discovery", [Photo No. 427] 2006)

"When we focus on designing ecologies in which people can forage for knowledge, we are less concerned about communicating the minutiae of changing knowledge. Instead, we are creating the conduit through which knowledge will flow." (George Siemens, "Knowing Knowledge", 2006)

"Any new dominant communications medium leads to a new information ecology in society that inevitably changes the way ideas, feelings, wealth, power and influence are distributed and the way collective decisions are made." (Al Gore,"The Assault on Reason", 2007)

"Social ecology is based on the conviction that nearly all of our present ecological problems originate in deep-seated social problems. It follows, from this view, that these ecological problems cannot be understood, let alone solved, without a careful understanding of our existing society and the irrationalities that dominate it. To make this point more concrete: economic, ethnic, cultural, and gender conflicts, among many others, lie at the core of the most serious ecological dislocations we face today—apart, to be sure, from those that are produced by natural catastrophes." (Murray Bookchin, "Social Ecology and Communalism", 2007)

"In ecology, we are often interested in exploring the behavior of whole systems of species or ecosystem composed of individual components which interact through biological processes. We are interested not simply in the dynamics of each species or component in isolation, but the dynamics of each species or component in the context of all the others and how those coupled dynamics account for properties of the system as a whole, such as its persistence. This is what people seem to mean when they say that ecology is ‘holistic’, an otherwise rather vague term." (John Pastor, "Mathematical Ecology of Populations and Ecosystems", 2008)

"Much of what we deal with in ecology are rates of change of biological objects: growth of an organism, decay of a dead leaf, fluctuations in populations, accumulation or erosion of soil, increases or decreases in lake levels, etc. But rates of change are some of the hardest things to measure. What we measure are static properties such as the sizes of objects at different times and then infer that change has taken place between those two measurements." (John Pastor, "Mathematical Ecology of Populations and Ecosystems", 2008)

"Therefore, mathematical ecology does not deal directly with natural objects. Instead, it deals with the mathematical objects and operations we offer as analogs of nature and natural processes. These mathematical models do not contain all information about nature that we may know, but only what we think are the most pertinent for the problem at hand. In mathematical modeling, we have abstracted nature into simpler form so that we have some chance of understanding it. Mathematical ecology helps us understand the logic of our thinking about nature to help us avoid making plausible arguments that may not be true or only true under certain restrictions. It helps us avoid wishful thinking about how we would like nature to be in favor of rigorous thinking about how nature might actually work." (John Pastor, "Mathematical Ecology of Populations and Ecosystems", 2008)

"This new model of development would be based clearly on the goal of sustainable human well-being. It would use measures of progress that clearly acknowledge this goal. It would acknowledge the importance of ecological sustainability, social fairness, and real economic efficiency. Ecological sustainability implies recognizing that natural and social capital are not infinitely substitutable for built and human capital, and that real biophysical limits exist to the expansion of the market economy." (Robert Costanza, "Toward a New Sustainable Economy", 2008)

"The answers to the human problems of ecology are to be found in economy. And the answers to the problems of economy are to be found in culture and character. To fail to see this is to go on dividing the world falsely between guilty producers and innocent consumers." (Wendell Berry, "What Are People For?: Essays", 2010)

"Economists don't seem to have noticed that the economy sits entirely within the ecology." (Carl Safina, "The View from Lazy Point: A Natural Year in an Unnatural World", 2011)

"Shallow ecology is anthropocentric, or human-centered. It views humans as above or outside of nature, as the source of all value, and ascribes only instrumental, or ‘use’, value to nature. Deep ecology does not separate humans - or anything else-from the natural environment. It sees the world not as a collection of isolated objects, but as a network of phenomena that are fundamentally interconnected and interdependent. Deep ecology recognizes the intrinsic value of all living beings and views humans as just one particular strand in the web of life." (Fritjof Capra, "The Systems View of Life: A Unifying Vision", 2014)

"When we chop nature into bits in an attempt to understand it, we lose sight of the relationships among those bits. But ecological healing is all about the healing of relationships." (Charles Eisenstein, "Climate: A New Story", 2018)

"Ecology is] the science of relations between organisms and their environment." (Ernst Haeckel)

🔖Knowledge Representation: Defining Mental Models (Part III)

Mental Models Series

Packing one or more labels (expressing the same thing) together with a set of characteristics into discrete cognitive units within a context is what defines a concept. Therefore, one or more labels can be associated with a concept, while a label can be associated with more concepts when different contexts apply. 

Concepts are associated with physical objects (doors, keys, latches, knobs), subjects (doorman, locksmith), scenarios and actions (opening a door, opening a door with a key, opening a door without a key, closing a door, breaking a door). As previously discussed, this mix forms together a ‘mental model’, however more precision is needed if we want to delimit the borders of a mental model.

When one or more labels are associated with one or more actions, or a chain of causality exists, then a mental model can be more likely extrapolated (aka build). Minimally we can consider only one object (the door) and only one action (opening the door) with two states (door open, door closed). One can consider the action of opening a door also as an objective, while in addition a basis heuristic is also implied (pushing the door). Thus, to open the door, I push it, and it will open or will remain closed. This is a description of the simplest mechanical model I can build. 

Of course, I can consider more factors: if I don’t apply enough force, the door might not open, so the force applied needs to be higher than the resistance. However, “force” and “resistance” are indirectly considered in our model and for the sake of simplicity can be ignored. Still, I can extend the model with one more heuristic – trying again. I can try again by applying the same force, or by pushing the door with my body’s force (maximal force) if the door didn’t open the first time. In the later case we deal thus with a third heuristic. A fourth heuristic might be to slightly increase the push force. 

When one talks about repeatability of an action a loop is implied with an exist condition - I push the door, it doesn’t open, then I try to apply more force. When just enough force is applied the door opens, and this is the exit criterion from the loop. If after several tries the door doesn’t open, then one has the choice of persisting or of breaking the option – another exit criterion. Typically a few tries are enough, though one might be tempted to try again later, though this behavior might include other drivers and probably the existence of other models. 

One can extend the model by including a door latch and with it adding more heuristics, pushing down/up the latch, if a simple push of the door doesn’t work. With it the number of states increases – latch push down, respectively up. Also here the force applied plays an important role and a loop is implied. The more objects are involved, more complex the model becomes. Of course, one doesn’t need to consider all the heuristics and states, just the more relevant or more probably one. 

On the other side, the model we are trying to build even if reflects to some degree how the mind works, is deeply submerged into our cognitive space to the degree that it become an automatism. However, we can become aware of the entire mechanism as soon we try to describe it into a functional unit, even if the process might not always be that straightforward as we would like to. In addition, the are many elements which we are forced to ignore or simplify. 

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🔖Knowledge Representation: Defining Mental Models (Part II)

Mental Models Series

Even if a good definition for a concept is available this doesn’t mean that people are able to recognize concept’s characteristics, usage and area of applicability. Therefore, the easiest way to understand what a concept like ‘mental model’ is about is by having one or more representative examples. Even if the examples aren’t always sufficient, they allow us in theory more chances to succeed. With this in mind, let’s consider the scenario of ‘opening a door’. 

If I need to open the door, then I can use the door knob or latch to do that. If I try that and the door doesn’t open, then I might also need a certain key (or one deals with something that isn’t a door, e.g. a false door). Only a specific key will work unless I have a master key which can open any door within the building, though not in other buildings. Supposing that I have other special skills, I could open a locked door with other objects – a big and hard object that will break the door, maybe a picklock, or any other device that will help me achieve that. Otherwise I can call somebody who has the skills or means to do it. I still need to differentiate between the different types of doors, keys or on whether I am or not entitled to enter the building.

We deal thus with a set of objects (doors, keys, knobs, latches, picklock), subjects (doorman, security man, locksmith), actions (opening, breaking, entering), heuristics (trying the knob first, first trying by myself then ask for help) and contexts (am I entitled to open the door?, can I ask for help?) which, when put together form a mental model. If we look at this mix, one can break it down to smaller units – how to open a door, a lock, how to bypass security, how to break a door, etc. All these can be considered as separate mental models which when put within a context or situation can form another mental model. Therefore, the delimitation between mental models is really thin as many mental models overlap or aggregate to handle more complex situations. 

To open a door, one even doesn’t need to know how the objects or subjects are called. Being able to use a language gives us this luxury. In contrast, a cat or a dog can open an unlocked door (when that is possible) and probably there must have some cognitive structure that allows them to recognize that they deal with something that can be opened, how it could be opened, and repeat the action when needed. Of course, they could also mimic behavior they have seen (us opening the door), though there must be a small sprung of intelligence in recognizing that by reaching to the door latch and grabbing it the door will open.

Being able to use language allows us to describe and communicate how to open a door, how to arrive from A to B, how to solve problems, etc. Labeling things and agreeing on the labels with other people helps in the process, to the degree that we can use the respective labels to communicate with people we don’t even know, or cope with unknown situations based on descriptions using the labels we know (e.g. opening a door with a touch key). It helps also that the labels carry with them some characteristics that define them and that characteristics apply to a set of objects sharing them. There are also characteristics that can slightly differ, while upon case these variances can be ignored or make a considerable difference.

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🔖Knowledge Representation: Mental Models (Part I: An Early Retrospective)

Mental Models Series

Browsing through the various material available on mental models it’s hard not to observe the frequency with which relatively modern scholastic sources like Craik [46], Johnson-Laird [47] or Boulding [48] are considered as starting points in elaborating the ideas. One is tempted to believe there's nothing else before them. However, as soon one leaves the standard paths of cognitive sciences and adventure on the paths of philosophy or pseudosciences, one is surprised to find a rich of material attempting to describe how the mind perceives, represents und understands reality, respectively the phenomena we deal with. 

One can agree that Craik’s work was a milestone within this context, as he considered that organisms and not only humans carry ‘small-scale model’ of external reality (aka mental models). However the term can be rooted back to antiquity if we consider Aristotle’s phantasmata (mental images) - perceptual states without matter used by intellect to think and associated with the imagination faculty [4] [5]. Similar interpretations appear in Augustinus [8], Avicenna [9] [10] [11], Maimonides [12], Aquinas [13] and much later St. Thomas [14] or Spinoza’s [16] works. Probably many of these sources have as direct or indirect source Aristotle’s work.

One can be entitled to suppose that there are also earlier similar attempts to explain how the mind reflects the reality, for example Plato’s 'images of beauty' [3] and model of resemblance [2]. Further early references are met in the works of Cicero [6] or Plotinus’ Enneads [7]. The available translations are maybe copies that haven’t kept the original or the meaning were adapted to modern times. References to the 'eye of the mind' or the 'thinking soul' are indicators for such attempts, typically in the context of treating imagination and perception themes.

One should not neglect the scriptures of the East, probably the earliest knowledge sources which attempted to describe metaphorically the inner workings of the mind. Patañjali 'Yoga Sūtras' [1] is maybe the best-known example of such sources, available in various translations with rich commentaries. Despite its character of pseudoscience and its interpretational complexity, the depth of the work could provide food for thought for the scientist and nonscientist altogether.

Hobbes [15], Berkely [17] [18], Hume [19], Reid [21] or Coleridge’s [22] [23] works seem to be more elaborated and have the advantage of eliminating the translator from the process, being to some degree easier to consume, despite the complex logical constructs of the literary style and the muddy character of the advanced ideas. In opposition with them, Kant [20] and later Nietzsche’s [25] works form the groundwork on which the modern German and European philosophy was built upon. Kant and  Nietzsche’s schemas and schemata reflect the purposeful and structural character of such representations when associated with concepts.

Starting with Helmholtz’s 'Anschauungsbild' [24] (mental image) the term starts being use by scientists like Hertz [26] [31], Boltzmann [29] [35], Heisenberger [44] or Dirac [43] in respect to the modelling of phenomena. In parallel the works of Galton [27], Frege [28] [39], James [30], Peirce [32] [37] [38], Bergson [33], Wundt [34], Ribot [36], Wittgenstein [40], Freud [41], Piaget [42] or Sartre [45] represent a new wave into the development of cognitive sciences. It’s a really long list of precursors, probably incomplete, and ignoring them in the detriment of Craik, Johnson-Laird, Boulding, or any others, is an injustice made to the former.

Whether one talks about phantasmata, (mental) images, pictures, models or representations, schema, schemata, diagrams, conceptual schemes/models, or frames, they are all metaphors with similar meaning. It’s important to stress the fact that the metaphors used across the centuries and geographies reflect also the vocabulary available and the languages used to express them. The deeper one dives into the early ages’ cultural heritage, the more one discovers such metaphors. Unfortunately, without appropriate keys to decipher them and minds to explore them, the sources can become lost in the thread of time. 

References (the quotes are available here):

[1] Yoga Sūtras of Patañjali, cca. 500 BC-400 CE

[2] Plato, “The Symposium", cca. 385–370 BC)
[3] Plato, “Timaeus”, 360 BC

[4] Aristotle, "De Anima" III, cca. 350 BC

[5] Aristotle, “De Memoria et Reminiscentia” [On Memory and Recollection], 4th century BC

[6] Marcus Tullius Cicero, "De Natura Deorum" ["On the Nature of the Gods"], 45 BC

[7] Plotinus, “Enneads”, cca. 270 AD

[8] Aurelius Augustinus, "The City of God", early 400s

[9] Avicenna Latinus [Ibn Sina], "A Compendium on the Soul", cca. 996-997

[10] Avicenna Latinus [Ibn Sina], "Liber De anima", cca. 1014-1027

[11] Avicenna Latinus [Ibn Sina], "Pointer and Reminders", cca. 1030

[12] Moses Maimonides, “The Guide for the Perplexed”, 1190

[13] Saint Thomas Aquinas, “De Anima” III, cca. 1268

[14] John of St. Thomas, “Tractatus de signis”, 1632

[15] Thomas Hobbes, “Leviathan”, 1651

[16] Baruch Spinoza, "Ethics", 1677

[17] George Berkeley, "Principles of Human Knowledge", 1710

[18] George Berkeley, "Three Dialogues", 1713

[19] David Hume, “Treatise of Human Nature”, 1738

[20] Immanuel Kant," Critique of Pure Reason", 1781

[21] Thomas Reid, "Essays on the Intellectual Powers of Man", 1785

[22] Samuel T Coleridge, "On the Principles of Genial Criticism", 1814

[23] Samuel T Coleridge, "The Statesman's Manual", 1816 

[24] Hermann von Helmholtz, "Tonempfindungen" ["Sensations of Tone"], 1863

[25] Friedrich Nietzsche, "On Truth and Lie in an Extra-Moral Sense", 1873

[26] Heinrich Hertz, "The Facts in Perception", 1878

[27] Francis Galton, “Mental imagery”, 1880

[28] Gottlob Frege, "The Foundations of Arithmetic", 1884

[29] Ludwig E Boltzmann, “On the Significance of Theories”, 1890

[30] William James, “The Principles of Psychology”, 1890

[31] Heinrich Hertz, “The Principles of Mechanics Presented in a New Form”, 1894

[32] Charles S Peirce, “Kinds of Reasoning”, cca. 1896

[33] Henri Bergson, "Matter and Memory", 1896

[34] Wilhelm M Wundt, “Outlines of Psychology”, 1897

[35] Ludwig Boltzmann, "On the development of the methods of theoretical physics", 1899

[36] Théodule-Armand Ribot, "Essay on the Creative Imagination", 1900

[37] Charles S Peirce, “Fallibility of Reasoning and the Feeling of Rationality”, cca. 1902

[38] Charles S Peirce, “On Existential Graphs, Euler's Diagrams, and Logical”, 1903 

[39] Gottlob Frege, [in "On the Foundations of Geometry and Formal Theories of Arithmetic" 1971] cca. 1903-1909

[40] Ludwig Wittgenstein, “Tractatus Logico-Philosophicus”, 1922

[41] Sigmund Freud, "The Ego And The Id", 1923

[42] Jean Piaget, "The Language and Thought of the Child", 1926

[43] Paul A M Dirac, "The Principles of Quantum Mechanics", 1930

[44] Werner K Heisenberg, "The Physical Principles of the Quantum Theory", 1930

[45] Jean-Paul Sartre, “The Psychology of Imagination”, 1940)

[46] Kenneth Craik, “The Nature of Explanation”, 1943

[47] Kenneth E Boulding, "The Image: Knowledge in life and society", 1956

[48] Philip Johnson-Laird, "Mental models: Toward a cognitive science of language, inference, and consciousness", 1983

🏷️Knowledge Representation: On Maps (Quotes)

"The world can doubtless never be well known by theory: practice is absolutely necessary; but surely it is of great use to a young man, before he sets out for that country, full of mazes, windings, and turnings, to have at least a general map of it, made by some experienced traveler." (Philip Stanhope, "Letters Written by the Earl of Chesterfield to His Son", 1827)

"The world of ideas which it [mathematics] discloses or illuminates, the contemplation of divine beauty and order which it induces, the harmonious connexion of its parts, the infinite hierarchy and absolute evidence of the truths with which it is concerned, these, and such like, are the surest grounds of the title of mathematics to human regard, and would remain unimpeached and unimpaired were the plan of the universe unrolled like a map at our feet, and the mind of man qualified to take in the whole scheme of creation at a glance." (James J Sylvester, [Presidential Address to British Association] 1869)

"What are the sciences but maps of universal laws, and universal laws but the channels of universal power; and universal power but the outgoings of a universal mind?" (Edward Thomson, "Evidences of Revealed Religion", 1872)

"Just as, in the map of a half-explored country, we see detached bits of rivers, isolated mountains, and undefined plains, not connected into any complete plan, so a new branch of knowledge consists of groups of facts, each group standing apart, so as not to allow us to reason from one to another." (William S Jevons, "The Principles of Science: A Treatise on Logic and Scientific Method", 1887)

"The first of the principles governing symbols is this: The symbol is NOT the thing symbolized; the word is NOT the thing; the map is NOT the territory it stands for." (Samuel I Hayakawa, "Language in Thought and Action", 1949)

"We all inherit a great deal of useless knowledge, and a great deal of misinformation and error (maps that were formerly thought to be accurate), so that there is always a portion of what we have been told that must be discarded. But the cultural heritage of our civilization that is transmitted to us - our socially pooled knowledge, both scientific and humane - has been valued principally because we have believed that it gives us accurate maps of experience. The analogy of verbal words to maps is an important one [...]. It should be noticed at this point, however, that there are two ways of getting false maps of the world into our heads: first, by having them given to us; second, by creating them ourselves when we misread the true maps given to us." (Samuel I Hayakawa, "Language in Thought and Action", 1949)

"A fundamental value in the scientific outlook is concern with the best available map of reality. The scientist will always seek a description of events which enables him to predict most by assuming least. He thus already prefers a particular form of behavior. If moralities are systems of preferences, here is at least one point at which science cannot be said to be completely without preferences. Science prefers good maps." (Anatol Rapoport, "Science and the goals of man: a study in semantic orientation", 1950)

"No map contains all the information about the territory it represents. The road map we get at the gasoline station may show all the roads in the state, but it will not as a rule show latitude and longitude. A physical map goes into details about the topography of a country but is indifferent to political boundaries. Furthermore, the scale of the map makes a big difference. The smaller the scale the less features will be shown." (Anatol Rapoport, "Science and the goals of man: a study in semantic orientation", 1950) 

"Good design looks right. It is simple (clear and uncomplicated). Good design is also elegant, and does not look contrived. A map should be aesthetically pleasing, thought provoking, and communicative."  (Arthur H Robinson, "Elements of Cartography", 1953)

"The design process involves a series of operations. In map design, it is convenient to break this sequence into three stages. In the first stage, you draw heavily on imagination and creativity. You think of various graphic possibilities, consider alternative ways." (Arthur H Robinson, "Elements of Cartography", 1953)

"Scientific research was much like prospecting: you went out and you hunted, armed with your maps and your instruments, but in the end your preparations did not matter, or even your intuition. You needed your luck, and whatever benefits accrued to the diligent, through sheer, grinding hard work." (Michael Crichton, "The Andromeda Strain", 1969)

"To do science is to search for repeated patterns, not simply to accumulate facts, and to do the science of geographical ecology is to search for patterns of plants and animal life that can be put on a map." (Robert H. MacArthur, "Geographical Ecology", 1972)

"The orchard of science is a vast globe-encircling monster, without a map, and known to no one man; indeed, to no group of men fewer than the whole international mass of creative scientists. Within it, each observer clings to his own well-known and well-loved clump of trees. If he looks beyond, it is usually with a guilty sigh." (Isaac Asimov, "View from a Height", 1975)

"As we experience space, and construct representations of it, we know that it will be continuous, everything is somewhere, and no matter what other characteristics objects do not share, they always share relative location, that is, spatiality; hence the desirability of equating knowledge with space, an intellectual space. This assures an organization and basis for predictability, which are shared by absolutely everyone. This proposition appears to be so fundamental that apparently it is simply adopted a priori." (Arthur H Robinson & Barbara B Petchenik, "The Nature of Maps: Essays toward Understanding Maps and Mapping", 1976)

"Mapping is based on systems of assumptions, on logic, on human needs, and on human cognitive characteristics, very little of which has been recognized or discussed in cartography." (Arthur H Robinson & Barbara B Petchenik, "The Nature of Maps: Essays toward Understanding Maps and Mapping", 1976)

"A map seems the type of conceptual object, yet the interesting thing is the grotesquely token foot it keeps in the world of the physical, having the unreality without the far-fetched appropriateness of the edibles in Communion, being a picture to the degree that the sacrament is a meal. For a feeling of thorough transcendence such unobvious relations between the model and the representation seem essential, and the flimsy connection between acres of soil and their image on the map makes reading one an erudite act." (Robert Harbison, "Eccentric Spaces", 1977)

"The theory of probability is the only mathematical tool available to help map the unknown and the uncontrollable. It is fortunate that this tool, while tricky, is extraordinarily powerful and convenient." (Benoit Mandelbrot, "The Fractal Geometry of Nature", 1977)

"Mathematical equations and literary phrases are useful but they are no substitute for the spatial eloquence of the map." (Arthur H Robinson, "Uniqueness of the Map", American Cartographer Vol. 5 (1), 1978)

"Maps containing marks that indicate a variety of features at specific locations are easy to produce and often revealing for the reader. You can use dots, numbers, and shapes, with or without keys. The basic map must always be simple and devoid of unnecessary detail. There should be no ambiguity about what happens where." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"Maps used as charts do not need fine cartographic detail. Their purpose is to express ideas, explain relationships, or store data for consultation. Keep your maps simple. Edit out irrelevant detail. Without distortion, try to present the facts as the main feature of your map, which should serve only as a springboard for the idea you're trying to put across." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"Physicists' models are like maps: never final, never complete until they grow as large and complex as the reality they represent." (James Gleick, "Genius: The Life and Science of Richard Feynman, Epilogue", 1992)

"The prevailing style of management must undergo transformation. A system cannot understand itself. The transformation requires a view from outside. The aim [...] is to provide an outside view - a lens - that I call a system of profound knowledge. It provides a map of theory by which to understand the organizations that we work in." (Dr. W. Edwards Deming, "The New Economics for Industry, Government, Education", 1994)

"The representational nature of maps, however, is often ignored - what we see when looking at a map is not the word, but an abstract representation that we find convenient to use in place of the world. When we build these abstract representations we are not revealing knowledge as much as are creating it." (Alan MacEachren, "How Maps Work: Representation, Visualization, and Design", 1995)

"A good map tells a multitude of little white lies; it suppresses truth to help the user see what needs to be seen. Reality is three-dimensional, rich in detail, and far too factual to allow a complete yet uncluttered two-dimensional graphic scale model. Indeed, a map that did not generalize would be useless. But the value of a map depends on how well its generalized geometry and generalized content reflect a chosen aspect of reality." (Mark S Monmonier, "How to Lie with Maps" 2nd Ed., 1996)

"Not only is it easy to lie with maps, it's essential. To portray meaningful relationships for a complex, three-dimensional world on a flat sheet of paper or a video screen, a map must distort reality. As a scale model, the map must use symbols that almost always are proportionally much bigger or thicker than the features they represent. To avoid hiding critical information in a fog of detail, the map must offer a selective, incomplete view of reality. There's no escape from the cartographic paradox: to present a useful and truthful picture, an accurate map must tell white lies." (Mark S Monmonier, "How to Lie with Maps" 2nd Ed., 1996)

"The nature of maps and of their use in science and society is in the midst of remarkable change - change that is stimulated by a combination of new scientific and societal needs for geo-referenced information and rapidly evolving technologies that can provide that information in innovative ways. A key issue at the heart of this change is the concept of ‘visualization’." (Alan MacEachren, "Exploratory cartographic visualization: advancing the agenda", 1997)

"The pursuit of science is more than the pursuit of understanding. It is driven by the creative urge, the urge to construct a vision, a map, a picture of the world that gives the world a little more beauty and coherence than it had before." (John A Wheeler, "Geons, Black Holes, and Quantum Foam: A Life in Physics", 1998)

"Eliciting and mapping the participant's mental models, while necessary, is far from sufficient [...] the result of the elicitation and mapping process is never more than a set of causal attributions, initial hypotheses about the structure of a system, which must then be tested. Simulation is the only practical way to test these models. The complexity of the cognitive maps produced in an elicitation workshop vastly exceeds our capacity to understand their implications. Qualitative maps are simply too ambiguous and too difficult to simulate mentally to provide much useful information on the adequacy of the model structure or guidance about the future development of the system or the effects of policies." (John D Sterman, "Learning in and about complex systems", Systems Thinking Vol. 3 2003)

"[Maps] are a way of cataloguing the 'important' (and ignoring the 'unimportant') features of the earth’s surface and the social world; a way of accounting for the resources, objects and public infrastructure of the earth’s surface; and a tool for the representation and territorialization of space (emphasis in original)." (John Pickles, "A History of Spaces: Cartographic Reason, Mapping and the Geo-Coded World", 2004)

"On the maps provided by science, we find everything except ourselves." (Bryan Appleyard, "Understanding the Present: An Alternative History of Science", 2004)

"There is no end to the information we can use. A 'good' map provides the information we need for a particular purpose - or the information the mapmaker wants us to have. To guide us, a map’s designers must consider more than content and projection; any single map involves hundreds of decisions about presentation." (Peter Turchi, "Maps of the Imagination: The writer as cartographer", 2004)

"A road plan can show the exact location, elevation, and dimensions of any part of the structure. The map corresponds to the structure, but it's not the same as the structure. Software, on the other hand, is just a codification of the behaviors that the programmers and users want to take place. The map is the same as the structure. […] This means that software can only be described accurately at the level of individual instructions. […] A map or a blueprint for a piece of software must greatly simplify the representation in order to be comprehensible. But by doing so, it becomes inaccurate and ultimately incorrect. This is an important realization: any architecture, design, or diagram we create for software is essentially inadequate. If we represent every detail, then we're merely duplicating the software in another form, and we're wasting our time and effort." (George Stepanek, "Software Project Secrets: Why Software Projects Fail", 2005) 

"The way you describe the tale is by telling the story. It is a balancing act and a dream. The more accurate the map, the more it resembles the territory. The most accurate map [...] would be the territory and thus would be perfectly accurate and perfectly useless. The tale is the map that is the territory." (Neil Gaiman, "Fragile Things: Short Fictions and Wonders", 2006)

"Science is the art of the appropriate approximation. While the flat earth model is usually spoken of with derision it is still widely used. Flat maps, either in atlases or road maps, use the flat earth model as an approximation to the more complicated shape." (Byron K Jennings, "On the Nature of Science", Physics in Canada Vol. 63 (1), 2007)

"A map does not just chart, it unlocks and formulates meaning; it forms bridges between here and there, between disparate ideas that we did not know were previously connected." (Reif Larsen, "The Selected Works of T S Spivet", 2009)

"If maps are essentially subjective, interpretative, and fictional constructs of facts, constructs that influence decisions, actions, and cultural values generally, then why not embrace the profound efficacy of mapping in exploring and shaping new realities? Why not embrace the fact that the potentially infinite capacity of mapping to find and found new conditions might enable more socially engaging modes of exchange within larger milieux?" (James Corner, "The Agency of Mapping: Speculation, Critique and Invention", 2011)

"It is ironic but true: the one reality science cannot reduce is the only reality we will ever know. This is why we need art. By expressing our actual experience, the artist reminds us that our science is incomplete, that no map of matter will ever explain the immateriality of our consciousness." (Jonah Lehrer, "Proust Was a Neuroscientist", 2011)

"[...] mapping is not the indiscriminate, blinkered accumulation and endless array of data, but rather an extremely shrewd and tactical enterprise, a practice of relational reasoning that intelligently unfolds new realities out of existing constraints, quantities, facts and conditions." (James Corner, "The Agency of Mapping: Speculation, Critique and Invention", 2011)

"Making a map is the physical production including conceptualization and design. Mapping is the mental interpretation of the world and although it must precede the map, it does not necessarily result in a map artifact. Mapping defined in mathematics is the correspondence between each element of a given set with each element of another. Similarly in linguistics emphasis is on the correspondence between associated elements of different types. For designers all drawings are maps - they represent relationships between objects, places and ideas." (Winifred E Newman, "Data Visualization for Design Thinking: Applied Mapping", 2017)

"Maps are parenthetical - maps frame what you want to hold apart from the real in the world. Maps do this by creating conceptual representations of the milieu using symbols and relations between symbols. [...] Maps, any map and every map, begin with a frame. This is the literal and conceptual demarcation between what is in the map and what is not. Making a map begins with an observation which is both a thought about thinking and the object of thought itself. The undifferentiated world cannot be apprehended, therefore; all maps have a frame whether a concept or a cosmography." (Winifred E Newman, "Data Visualization for Design Thinking: Applied Mapping", 2017)

"The utility of mapping as a form of data visualization isn’t in accuracy or precision, but rather the map’s capacity to help us make and organize hypothesis about the world of ideas and things. hypothesis-making through the map isn’t strictly inductive or deductive, although it can use the thought process of either, but it is often based on general observations." (Winifred E Newman, "Data Visualization for Design Thinking: Applied Mapping", 2017)

"Using maps as communication tools masks their complexity as a mode of thinking. Maps act like language: we attribute the signs or marks in the map to a natural extension of thought. But post-structuralism exposed maps (like language) as artificial signs whose meaning is tethered to time, place, culture, gesture, smell - in short, a plethora of cognitive and phenomenal attributes of our communication ecology." (Winifred E Newman, "Data Visualization for Design Thinking: Applied Mapping", 2017)

"Maps also have the disadvantage that they consume the most powerful encoding channels in the visualization toolbox - position and size - on an aspect that is held constant. This leaves less effective encoding channels like color for showing the dimension of interest." (Danyel Fisher & Miriah Meyer, "Making Data Visual", 2018)

"We cannot draw a complete map, a complete geometry, of everything that happens in the world, because such happenings - including among them the passage of time - are always triggered only by an interaction with, and with respect to, a physical system involved in the interaction. The world is like a collection of interrelated points of view. To speak of the world 'seen from outside' makes no sense, because there is no “outside” to the world." (Carlo Rovelli, "The Order of Time", 2018)

"Maps can be a metaphor for discovery and for dominion. They embody the same principles of logic, order, and discipline that codify empirical scientific processes." (Murray Dick, "The Infographic: A History of Data Graphics in News and Communications", 2020)

"Maps are a type of chart that can convey relationships about space and relationships between objects that we relate to in the real world. Their effectiveness as a communication medium is strongly influenced by a host of factors: the nature of spatial data, the form and structure of representation, their intended purpose, the experience of the audience, and the context in the time and space in which the map is viewed. In other words, maps are a ubiquitous representation of spatial information that we can understand and relate to." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

See also: Maps as Graphical Representation, Maps and Mind

❄️Systems Thinking: On Feedback (Quotes)

"Purposeful active behavior may be subdivided into two classes: ‘feed-back’ (or ‘teleological’) and ‘non-feed-back’ (or ‘non-teleological’). The expression feed-back is used by engineers in two different senses. In a broad sense it may denote that some of the output energy of an apparatus or machine is returned as input; an example is an electrical amplifier with feed-back. The feed-back is in these cases positive - the fraction of the output which reenters the object has the same sign as the original input signal. Positive feed-back adds to the input signals, it does not correct them. The term feed-back is also employed in a more restricted sense to signify that the behavior of an object is controlled by the margin of error at which the object stands at a given time with reference to a relatively specific goal. The feed-back is then negative, that is, the signals from the goal are used to restrict outputs which would otherwise go beyond the goal. It is this second meaning of the term feed-back that is used here." (Arturo Rosenblueth, Norbert Wiener & Julian Bigelow, "Behavior, Purpose and Technology", Philosophy of Science Vol. 10 (1), 1943)

"All purposeful behavior may be considered to require negative feed-back. If a goal is to be attained, some signals from the goal are necessary at some time to direct the behavior. By non-feed-back behavior is meant that in which there are no signals from the goal which modify the activity of the object in the course of the behavior. Thus, a machine may be set to impinge upon a luminous object although the machine may be insensitive to light." (Arturo Rosenblueth, Norbert Wiener & Julian Bigelow, "Behavior, Purpose and Technology", Philosophy of Science Vol. 10 (1), 1943)

"It is my thesis that the physical functioning of the living individual and the operation of some of the newer communication machines are precisely parallel in their analogous attempts to control entropy through feedback. Both of them have sensory receptors as one stage of their cycle of operation: that is, in both of them there exists a special apparatus for collecting information from the outer world at low energy levels, and for making it available in the operation of the individual or of the machine. In both cases these external messages are not taken neat, but through the internal transforming powers of the apparatus, whether it be alive or dead. The information is then turned into a new form available for the further stages of performance. In both the animal and the machine this performance is made to be effective on the outer world. In both of them, their performed action on the outer world, and not merely their intended action, is reported back to the central regulatory apparatus." (Norbert Wiener, "The Human Use of Human Beings", 1950)

"Feedback is a method of controlling a system by reinserting into it the results of its past performance. If these results are merely used as numerical data for the criticism of the system and its regulation, we have the simple feedback of the control engineers. If, however, the information which proceeds backward from the performance is able to change the general method and pattern of performance, we have a process which may be called learning." (Norbert Wiener, 1954)

"[...] the concept of 'feedback', so simple and natural in certain elementary cases, becomes artificial and of little use when the interconnexions between the parts become more complex. When there are only two parts joined so that each affects the other, the properties of the feedback give important and useful information about the properties of the whole. But when the parts rise to even as few as four, if every one affects the other three, then twenty circuits can be traced through them; and knowing the properties of all the twenty circuits does not give complete information about the system. Such complex systems cannot be treated as an interlaced set of more or less independent feedback circuits, but only as a whole. For understanding the general principles of dynamic systems, therefore, the concept of feedback is inadequate in itself. What is important is that complex systems, richly cross-connected internally, have complex behaviours, and that these behaviours can be goal-seeking in complex patterns." (W Ross Ashby, "An Introduction to Cybernetics", 1956)

"To say a system is 'self-organizing' leaves open two quite different meanings. There is a first meaning that is simple and unobjectionable. This refers to the system that starts with its parts separate (so that the behavior of each is independent of the others' states) and whose parts then act so that they change towards forming connections of some type. Such a system is 'self-organizing' in the sense that it changes from 'parts separated' to 'parts joined'. […] In general such systems can be more simply characterized as 'self-connecting', for the change from independence between the parts to conditionality can always be seen as some form of 'connection', even if it is as purely functional […]  'Organizing' […] may also mean 'changing from a bad organization to a good one' […] The system would be 'self-organizing' if a change were automatically made to the feedback, changing it from positive to negative; then the whole would have changed from a bad organization to a good." (W Ross Ashby, "Principles of the self-organizing system", 1962)

"Negative feedback is the form normally encountered in the control of physical systems. Yet, positive feedback dominates in the growth and decline patterns of social systems." (Jay W Forrester, "Modeling the Dynamic Processes of Corporate Growth", 1964)

"Traditional organizational theories have tended to view the human organization as a closed system. This tendency has led to a disregard of differing organizational environments and the nature of organizational dependency on environment. It has led also to an over-concentration on principles of internal organizational functioning, with consequent failure to develop and understand the processes of feedback which are essential to survival." (Daniel Katz, "The Social Psychology of Organizations", 1966)

"Like all systems, the complex system is an interlocking structure of feedback loops [...] This loop structure surrounds all decisions public or private, conscious or unconscious. The processes of man and nature, of psychology and physics, of medicine and engineering all fall within this structure [...]" (Jay W Forrester, "Urban Dynamics", 1969)

"Nonlinear coupling allows one feedback loop to dominate the system for a time and then cause this dominance to shift to another part of the system where behavior is so different that the two seem unrelated." (Jay W. Forrester, "Urban Dynamics", 1969)

"The structure of a complex system is not a simple feedback loop where one system state dominates the behavior. The complex system has a multiplicity of interacting feedback loops. Its internal rates of flow are controlled by non‐linear relationships. The complex system is of high order, meaning that there are many system states (or levels). It usually contains positive‐feedback loops describing growth processes as well as negative, goal‐seeking loops." (Jay F Forrester, "Urban Dynamics", 1969)

"To model the dynamic behavior of a system, four hierarchies of structure should be recognized: closed boundary around the system; feedback loops as the basic structural elements within the boundary; level variables representing accumulations within the feedback loops; rate variables representing activity within the feedback loops." (Jay W Forrester, "Urban Dynamics", 1969)

"Whatever the system, adaptive change depends upon feedback loops, be it those provided by natural selection or those of individual reinforcement. In all cases, then, there must be a process of trial and error and a mechanism of comparison. […] By superposing and interconnecting many feedback loops, we (and all other biological systems) not only solve particular problems but also form habits which we apply to the solution of classes of problems." (Gregory Bateson, "Steps to an Ecology of Mind", 1972)

"When the phenomena of the universe are seen as linked together by cause-and-effect and energy transfer, the resulting picture is of complexly branching and interconnecting chains of causation. In certain regions of this universe (notably organisms in environments, ecosystems, thermostats, steam engines with governors, societies, computers, and the like), these chains of causation form circuits which are closed in the sense that causal interconnection can be traced around the circuit and back through whatever position was (arbitrarily) chosen as the starting point of the description. In such a circuit, evidently, events at any position in the circuit may be expected to have effect at all positions on the circuit at later times." (Gregory Bateson, "Steps to an Ecology of Mind", 1972)

"A nonlinear relationship causes the feedback loop of which it is a part to vary in strength, depending on the state of the system. Linked nonlinear feedback loops thus form patterns of shifting loop dominance- under some conditions one part of the system is very active, and under other conditions another set of relationships takes control and shifts the entire system behavior. A model composed of several feedback loops linked nonlinearly can produce a wide variety of complex behavior patterns." (Jørgen Randers, "Elements of the System Dynamics Method", 1980)

"Effect spreads its 'tentacles' not only forwards (as a new cause giving rise to a new effect) but also backwards, to the cause which gave rise to it, thus modifying, exhausting or intensifying its force. This interaction of cause and effect is known as the principle of feedback. It operates everywhere, particularly in all self-organising systems where perception, storing, processing and use of information take place, as for example, in the organism, in a cybernetic device, and in society. The stability, control and progress of a system are inconceivable without feedback." (Alexander Spirkin, "Dialectical Materialism", 1983)

"The autonomy of living systems is characterized by closed, recursive organization. [...] A system's highest order of recursion or feedback process defines, generates, and maintains the autonomy of a system. The range of deviation this feedback seeks to control concerns the organization of the whole system itself. If the system should move beyond the limits of its own range of organization it would cease to be a system. Thus, autonomy refers to the maintenance of a systems wholeness. In biology, it becomes a definition of what maintains the variable called living." (Bradford P Keeney, "Aesthetics of Change", 1983)

"Ultimately, uncontrolled escalation destroys a system. However, change in the direction of learning, adaptation, and evolution arises from the control of control, rather than unchecked change per se. In general, for the survival and co-evolution of any ecology of systems, feedback processes must be embodied by a recursive hierarchy of control circuits." (Bradford P Keeney, "Aesthetics of Change", 1983)

"What is sometimes called 'positive feedback' or 'amplified deviation' is therefore a partial arc or sequence of a more encompassing negative feedback process. The appearance of escalating runaways in systems is a consequence of the frame of reference an observer has punctuated. Enlarging one's frame of reference enables the 'runaway' to be seen as a variation subject to higher orders of control." (Bradford P Keeney, "Aesthetics of Change", 1983)

"Every system of whatever size must maintain its own structure and must deal with a dynamic environment, i.e., the system must strike a proper balance between stability and change. The cybernetic mechanisms for stability (i.e., homeostasis, negative feedback, autopoiesis, equifinality) and change (i.e., positive feedback, algedonodes, self-organization) are found in all viable systems." (Barry Clemson, "Cybernetics: A New Management Tool", 1984) 

"The term closed loop-learning process refers to the idea that one learns by determining what s desired and comparing what is actually taking place as measured at the process and feedback for comparison. The difference between what is desired and what is taking place provides an error indication which is used to develop a signal to the process being controlled." (Harold Chestnut, 1984) 

"The term chaos is used in a specific sense where it is an inherently random pattern of behaviour generated by fixed inputs into deterministic (that is fixed) rules (relationships). The rules take the form of non-linear feedback loops. Although the specific path followed by the behaviour so generated is random and hence unpredictable in the long-term, it always has an underlying pattern to it, a 'hidden' pattern, a global pattern or rhythm. That pattern is self-similarity, that is a constant degree of variation, consistent variability, regular irregularity, or more precisely, a constant fractal dimension. Chaos is therefore order (a pattern) within disorder (random behaviour)." (Ralph D Stacey, "The Chaos Frontier: Creative Strategic Control for Business", 1991)

"In many parts of the economy, stabilizing forces appear not to operate. Instead, positive feedback magnifies the effects of small economic shifts; the economic models that describe such effects differ vastly from the conventional ones. Diminishing returns imply a single equilibrium point for the economy, but positive feedback – increasing returns – makes for many possible equilibrium points. There is no guarantee that the particular economic outcome selected from among the many alternatives will be the ‘best’ one."  (W Brian Arthur, "Returns and Path Dependence in the Economy", 1994)

"[…] self-organization is the spontaneous emergence of new structures and new forms of behavior in open systems far from equilibrium, characterized by internal feedback loops and described mathematically by nonlinear equations." (Fritjof  Capra, "The web of life: a new scientific understanding of living systems" , 1996)

"[…] feedback is not necessarily transmitted and returned through the same system component - or even through the same system. It may travel through several intervening components within the system first, or return from an external system, before finally arriving again at the component where it started." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Causal Loops", 1997)

"Feedback is the transmission and return of information. […] A system has feedback within itself. But because all systems are part of larger systems, a system also has feedback between itself and external systems. In some systems, the feedback and adjustment processes happen so quickly that it is relatively easy for an observer to follow. In other systems, it may take a long time before the feedback is returned, so an observer would have trouble identifying the action that prompted the feedback." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Causal Loops", 1997)

"In a complex system, it is not uncommon for subsystems to have goals that compete directly with or diverge from the goals of the overall system. […] Feedback gathered from small, local subsystems for use by larger subsystems may be either inaccurately conveyed or inaccurately interpreted. Yet it is this very flexibility and looseness that allow large, complex systems to endure, although it can be hard to predict what these organizations are likely to do next." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Causal Loops", 1997)

"Reinforcing loops can be seen as the engines of growth and collapse. That is, they compound change in one direction with even more change in that direction. Many reinforcing loops have a quality of accelerating movement in a particular direction, a sense that the more one variable changes, the more another changes." (Virginia Anderson & Lauren Johnson, "Systems Thinking Basics: From Concepts to Causal Loops", 1997)

"Something of the previous state, however, survives every change. This is called in the language of cybernetics (which took it form the language of machines) feedback, the advantages of learning from experience and of having developed reflexes." (Guy Davenport, "The Geography of the Imagination: Forty Essays", 1997)

"Cybernetics is the science of effective organization, of control and communication in animals and machines. It is the art of steersmanship, of regulation and stability. The concern here is with function, not construction, in providing regular and reproducible behaviour in the presence of disturbances. Here the emphasis is on families of solutions, ways of arranging matters that can apply to all forms of systems, whatever the material or design employed. [...] This science concerns the effects of inputs on outputs, but in the sense that the output state is desired to be constant or predictable – we wish the system to maintain an equilibrium state. It is applicable mostly to complex systems and to coupled systems, and uses the concepts of feedback and transformations (mappings from input to output) to effect the desired invariance or stability in the result." (Chris Lucas, "Cybernetics and Stochastic Systems", 1999)

"All dynamics arise from the interaction of just two types of feedback loops, positive (or self-reinforcing) and negative (or self-correcting) loops. Positive loops tend to reinforce or amplify whatever is happening in the system […] Negative loops counteract and oppose change." (John D Sterman, "Business Dynamics: Systems thinking and modeling for a complex world", 2000)

"The self-reinforcing feedback between expectations and perceptions has been repeatedly demonstrated […]. Sometimes the positive feedback assists learning by sharpening our ability to perceive features of the environment, as when an experienced naturalist identifies a bird in a distant bush where the novice sees only a tangled thicket. Often, however, the mutual feedback of expectations and perception blinds us to the anomalies that might challenge our mental models and lead to deep insight." (John D Sterman, "Business Dynamics: Systems thinking and modeling for a complex world", 2000)

"Much of the art of system dynamics modeling is discovering and representing the feedback processes, which, along with stock and flow structures, time delays, and nonlinearities, determine the dynamics of a system. […] the most complex behaviors usually arise from the interactions (feedbacks) among the components of the system, not from the complexity of the components themselves." (John D Sterman, "Business Dynamics: Systems thinking and modeling for a complex world", 2000)

"The phenomenon of emergence takes place at critical points of instability that arise from fluctuations in the environment, amplified by feedback loops." (Fritjof Capra, "The Hidden Connections: A Science for Sustainable Living", 2002)

"In particular, complexity examines how components of a system can through their dynamic interaction 'spontaneously' develop collective properties or patterns, such as colour, that do not seem implicit, or at least not implicit in the same way, within individual components.  Complexity investigates emergent properties, certain regularities of behaviour that somehow transcend the ingredients that make them up. Complexity argues against reductionism, against reducing the whole to the parts. And in so doing it transforms scientific understanding of far-from-equilibrium structures, of irreversible times and of non-Euclidean mobile spaces. It emphasizes how positive feedback loops can exacerbate initial stresses in the system and render it unable to absorb shocks to re-establish the original equilibrium. Positive feedback occurs when a change tendency is reinforced rather than dampened clown. Very strong interactions occur between the parts of such systems, with the absence of a central hierarchical structure that unambiguously' governs' and produces outcomes. These outcomes are to be seen as both uncertain and irreversible." (John Urry, "Global Complexity", 2003)

"All models are mental projections of our understanding of processes and feedbacks of systems in the real world. The general approach is that models are as good as the system upon which they are based. Models should be designed to answer specific questions and only incorporate the necessary details that are required to provide an answer." (Hördur V Haraldsson & Harald U Sverdrup, "Finding Simplicity in Complexity in Biogeochemical Modelling", 2004)

"[…] some systems […] are very sensitive to their starting conditions, so that a tiny difference in the initial ‘push’ you give them causes a big difference in where they end up, and there is feedback, so that what a system does affects its own behavior." (John Gribbin, "Deep Simplicity", 2004)

"Feedback and its big brother, control theory, are such important concepts that it is odd that they usually find no formal place in the education of physicists. On the practical side, experimentalists often need to use feedback. Almost any experiment is subject to the vagaries of environmental perturbations. Usually, one wants to vary a parameter of interest while holding all others constant. How to do this properly is the subject of control theory. More fundamentally, feedback is one of the great ideas developed (mostly) in the last century, with particularly deep consequences for biological systems, and all physicists should have some understanding of such a basic concept." (John Bechhoefer, "Feedback for physicists: A tutorial essay on control". Reviews of Modern Physics Vol. 77, 2005)

"Thus, nonlinearity can be understood as the effect of a causal loop, where effects or outputs are fed back into the causes or inputs of the process. Complex systems are characterized by networks of such causal loops. In a complex, the interdependencies are such that a component A will affect a component B, but B will in general also affect A, directly or indirectly.  A single feedback loop can be positive or negative. A positive feedback will amplify any variation in A, making it grow exponentially. The result is that the tiniest, microscopic difference between initial states can grow into macroscopically observable distinctions." (Carlos Gershenson, "Design and Control of Self-organizing Systems", 2007)

"[…] our mental models fail to take into account the complications of the real world - at least those ways that one can see from a systems perspective. It is a warning list. Here is where hidden snags lie. You can’t navigate well in an interconnected, feedback-dominated world unless you take your eyes off short-term events and look for long-term behavior and structure; unless you are aware of false boundaries and bounded rationality; unless you take into account limiting factors, nonlinearities and delays. You are likely to mistreat, misdesign, or misread systems if you don’t respect their properties of resilience, self-organization, and hierarchy." (Donella H Meadows, "Thinking in Systems: A Primer", 2008)

"The notion of feedback to regulate servomechanisms is the control engineer’s contribu￾tion to understanding how systems can be sensed, and then sufficient sense made of this for the purpose of having the system behave agreeably. The cleverness of control has been to influence systems behavior when a priori knowledge of that system is difficult or impossible to achieve. Usually you need to know what it is you are controlling to have a chance of regulating its behavior; that is one consequence of the law of requisite variety." (John Boardman & Brian Sauser, "Systems Thinking: Coping with 21st Century Problems", 2008)

"You can’t navigate well in an interconnected, feedback-dominated world unless you take your eyes off short-term events and look for long term behavior and structure; unless you are aware of false boundaries and bounded rationality; unless you take into account limiting factors, nonlinearities and delays." (Donella H Meadow, "Thinking in Systems: A Primer", 2008)

"A perturbation in a system with a negative feedback mechanism will be reduced whereas in a system with positive feedback mechanisms, the perturbation will grow. Quite often, the system dynamics can be reduced to a low-order description. Then, the growth or decay of perturbations can be classified by the systems’ eigenvalues or the pseudospectrum." (Gerrit Lohmann, "Abrupt Climate Change Modeling", 2009)

"The work around the complex systems map supported a concentration on causal mechanisms. This enabled poor system responses to be diagnosed as the unanticipated effects of previous policies as well as identification of the drivers of the sector. Understanding the feedback mechanisms in play then allowed experimentation with possible future policies and the creation of a coherent and mutually supporting package of recommendations for change."  (David C Lane et al, "Blending systems thinking approaches for organisational analysis: reviewing child protection", 2015)

"Feedback systems are closed loop systems, and the inputs are changed on the basis of output. A feedback system has a closed loop structure that brings back the results of the past action to control the future action. In a closed system, the problem is perceived, action is taken and the result influences the further action. Thus, the distinguishing feature of a closed loop system is a feedback path of information, decision and action connecting the output to input." (Bilash K Bala et al, "System Dynamics: Modelling and Simulation", 2017)