Systems Scientists

"There is no power for change greater than a community discovering what it cares about."

"In our daily life, we encounter people who are angry, deceitful, intent only on satisfying their own needs. There is so much anger, distrust, greed, and pettiness that we are losing our capacity to work well together."

"When we can lay down our fear and anger and choose responses other than aggression, we create the conditions for bringing out the best in us humans."

"Leadership is always dependent upon the context, but the context is established by the relationships."

"The dense and tangled web of life-the interconnected nature of reality--now reveals itself on a daily basis. Since September 11th, think about how much you've learned about people, nations, and ways of life that previously you'd known nothing about. We've been learning how the lives of those far away affect our own. We're beginning to realize that in order to live peacefully together on this planet, we need to be in new relationships, especially with those far-distant from us."

"I believe that our very survival depends upon us becoming better systems thinkers. How can we learn to see the systems we're participating in? How can we act intelligently when things remain fuzzy?"

"If vision is a field, think about what we could do differently to create one. We would do our best to get it permeating through the entire organization so that we could take advantage of its formative properties. All employees, in any part of the company, who bumped up against the field, would be influenced by it. Their behavior could be shaped as a result of “field meetings”, where their energy would link with the fields form to create behavior congruent with the organizations goals. In the absence of that field, in areas of the organization that hadn’t been reached, we could hold no expectation of desired behaviors. If the field hadn’t extended into that space, there would be nothing there to help behaviors materialize, no invisible geometry working on our behalf"

"We have created trouble for ourselves in organizations by confusing control with order. This is no surprise, given that for most of its written history, leadership has been defined in terms of its control functions."

"The things we fear most in organizations - fluctuations, disturbances, imbalances - need not be signs ofan impending disorder that will destroy us. Instead, fluctuations are the primary source of creativity."

"We will need to become savvy about how to build relationships, how to nurture growing, evolving things. All of us will need better skills in listening, communicating, and facilitating groups, because these are the talents that build strong relationships."

"Here are a few principles I've learned. Start something, and see who notices it. It's only after we initiate something in a system that we see the threads that connect. Usually, someone we don't even know suddenly appears, either outraged or helpful."

"Change always involves a dark night when everything falls apart. Yet if this period of dissolution is used to create new meaning, then chaos ends and new order emerges."

"To name is to make visible."

"Scott London: How did you begin to explore the connection between management and science? Meg Wheatley: I didn't have an interest in the new science. I had a realization that in my profession — which was vaguely labeled "organizational change," "organizational development," or "management consulting" in general — none of us knew how organizations change. When I talked to other consultants, I noticed that if we had an organizational change effort that was successful, it felt like a miracle to us. I realized with a great start one day that we weren't even geared up for success. It didn't matter that we didn't know how to change organizations. We were all professionals who didn't hope to achieve what we were selling or suggesting to clients. The field was really moribund. At the same time — and this is the serendipity of life — I had a friend and educator whom I had worked with for many years who said casually one day "Meg, if you're interested in systems thinking, you should be reading quantum physics." He didn't know where I was in my despair over my professional failings. But I said, "Okay, give me a book list." He gave me ten titles. I read eight of those and I was off. I always credit him with that casual, helpful comment that changed my life."

"In organizations, real power and energy is generated through relationships. The patterns of relationships and the capacities to form them are more important than tasks, functions, roles, and positions."

"I was reading of chaos that contained order; of information as the primal, creative force; of systems that, by design, fell apart so they could renew themselves; and of invisible forces that structured space and held complex things together. These were compelling, evocative ideas, and they gave me hope, even if they did not reveal immediate solutions."

"Relationships are all there is. Everything in the universe only exists because it is in relationship to everything else. Nothing exists in isolation. We have to stop pretending we are individuals that can go it alone."

"Among Kalman's early work was the development of what is now called the Kalman filter for detection of signals in noise. This revolutionized the field of estimation, by providing a recursive approach to the filtering problem. Before the advent of the Kalman filter, most mathematical work was based on Norbert Wiener's ideas, but the 'Wiener filtering' had proved difficult to apply. Kalman's approach, based on the use of state space techniques and a recursive least-squares algorithm, opened up many new theoretical and practical possibilities. The impact of Kalman filtering on all areas of applied mathematics, engineering, and sciences has been tremendous. It is impossible to even begin to enumerate its practical applications. Just as examples of their diversity, one may mention the guidance of the Apollo spacecraft and of commercial airplanes, uses in seismic data processing, nuclear power plant instrumentation, and demographic models, as well as applications in econometrics."

"::(iii) Characterization of the general results in terms of some simple quantities, such as signal-to-noise ratio, information rate, bandwidth, etc"

":(2) The computational aspect. The classical (more accurately, old-fashioned) view is that a mathematical problem is solved if the solution is expressed by a formula. It is not a trivial matter, however, to substitute numbers in a formula. The current literature on the Wiener problem is full of semi-rigorously derived formulas which turn out to be unusable for practical computation when the order of the system becomes even moderately large..."

"The creator of modern control and system theory, Kalman theory, which was established in the early 1960s, brought a fundamental reformation to control engineering and since then laid the foundation for the rapid progress of modern control theory."

"[H]is fundamental contributions to modern system theory... provided rigorous mathematical tools for engineering, econometrics, and statistics, and in particular for his invention of the "Kalman filter,"… was critical to achieving the Moon landings and creating the Global Positioning System and which has facilitated the use of computers in control and communications technology."

"::(ii) Conditions which guarantee a priori the existence, physical realizability, and stability of the optimal filter."

"I would like to comment briefly on Professor Zadeh's presentation. His proposals could be severely, ferociously, even brutally criticized from a technical point of view. This would be out of place here. But a blunt question remains: Is professor Zadeh presenting important ideas or is he indulging in wishful thinking? No doubt Professor Zadeh's enthusiasm for fuzziness has been reinforced by the prevailing climate in the U.S.-one of unprecedented permissiveness. 'Fuzzification, is a kind of scientific permissiveness; it tends to result in socially appealing slogans unaccompanied by the discipline of hard scientific work and patient observation."

"I have been aware from the outset (end of January 1959, the birthdate of the second paper in the citation) that the deep analysis of something which is now called were of major importance. But even with this immodesty I did not quite anticipate all the reactions to this work. Up to now there have been some 1000 related publications, at least two Citation Classics, etc. There is something to be explained. To look for an explanation, let me suggest a historical analogy, at the risk of further immodesty. I am thinking of Newton, and specifically his most spectacular achievement, the law of Gravitation. Newton received very ample "recognition" (as it is called today) for this work. it astounded - really floored - all his contemporaries. But I am quite sure, having studied the matter and having added something to it, that nobody then (1700) really understood what Newton's contribution was. Indeed, it seemed an absolute miracle to his contemporaries that someone, an Englishman, actually a human being, in some magic and un-understandable way, could harness mathematics, an impractical and eternal something, and so use mathematics as to discover with it something fundamental about the universe."

"Let me say quite categorically that there is no such thing as a fuzzy concept... We do talk about fuzzy things but they are not scientific concepts. Some people in the past have discovered certain interesting things, formulated their findings in a non-fuzzy way, and therefore we have progressed in science."

"A of the Riccati type is derived for the covariance matrix of the optimal filtering error. The solution of this 'variance equation' completely specifies the optimal filter for either finite or infinite smoothing intervals and stationary or non-stationary statistics. The variance equation is closely related to the Hamiltonian (canonical) differential equations of the calculus of variations. Analytic solutions are available in some cases. The significance of the variance equation is illustrated by examples which duplicate, simplify, or extend earlier results in this field. The duality principle relating stochastic estimation and deterministic control problems plays an important role in the proof of theoretical results. In several examples, the estimation problem and its dual are discussed side-by-side. Properties of the variance equation are of great interest in the theory of s. Some aspects of this are considered briefly."

"At present, a nonspecialist might well regard the Wiener-Kolmogorov theory of filtering and prediction [1, 2] as "classical' — in short, a field where the techniques are well established and only minor improvements and generalizations can be expected. That this is not really so can be seen convincingly from recent results of Shinbrot [3], Stceg [4], Pugachev [5, 6], and Parzen [7]. Using a variety of methods, these investigators have solved some long-stauding problems in nonstationary filtering and prediction theory. We present here a unified account of our own independent researches during the past two years (which overlap with much of the work [3-71 just mentioned), as well as numerous new results. We, too, use time-domain methods, and obtain major improvements and generalizations of the conventional Wiener theory. In particular, our methods apply without modification to multivariate problems."

"One should clearly distinguish between two aspects of the estimation problem:"

":(1) The theoretical aspect. Here interest centers on:"

"::(1) The general form of the solution (see Fig. 1)."

"The motivation for an "information highway" was expressed in 1937, just prior to the advent of computer technology, when Wells was promoting the concept of a "World Brain" based on a "permanent world encyclopaedia" as a social good through giving universal access to all of human knowledge. He remarks: "our contemporary encyclopaedias are still in the coach-and-horses phase of development, rather than in the phase of the automobile and the aeroplane. Encyclopaedic enterprise has not kept pace with material progress. These observers realize that the modern facilities of transport, radio, photographic reproduction and so forth are rendering practicable a much more fully succinct and accessible assembly of facts and ideas than was ever possible before." (Wells, 1938)"

"Bush, a technical advisor to Roosevelt, published in 1945 an article in Atlantic Monthly which highlighted problems in the growth of knowledge, and proposed a technological solution based on his concept of memex, a multimedia personal computer: "Professionally, our methods of transmitting and reviewing the results of research are generations old and by now are totally inadequate for their purpose...The difficulty seems to be not so much that we publish unduly in view of the extent and variety of present-day interests, but rather that publication has been extended far beyond our present ability to make real use of the record." (Bush, 1945) The world brain has continued for over fifty years to provide an active objective for the information systems community (Goodman, 1987), and memex is often quoted as having been realized fifty years later through the World Wide Web (Berners-Lee, Cailliau, Luotonen, Nielsen and Secret, 1994)."

"Tracking the individual learning curves of the major technologies that comprise the infrastructure of information technology provides a more detailed account of the present and future state-of-the art of the technologies underlying convergence. The base technologies of digital electronics, general-purpose computer architectures, software and interaction are mature and provide solid foundations for computer science. The upper technologies of knowledge representation and acquisition, autonomy and sociality, support product innovation and provide the beginnings of foundations for knowledge science. Well's dream of a world brain making available all of human knowledge is well on its way to realization and it is in the representation, acquisition, and access and effective application of that knowledge that the commercial potential and socio-economic impact of convergence lies."

"Models of human reasoning are clearly relevant to a wide variety of subject areas such as sociology, economics, psychology, artificial intelligence and man-machine systems. Broadly there are two types: psychological models of what people actually do; and formal models of what logicians and philosophers feel a rational individual would, or should, do. The main problem with the former is that it is extremely difficult to monitor thought processes - the behaviourist approach is perhaps reasonable with rats but a ridiculously inadequate source of data on man - the introspectionist approach is far more successful [e.g. in analysing human chess strategy... but the data obtained is still incomplete and may not reflect the actual thought processes involved."

"Principle of causality is fundamental to human thinking, and it has been observed experimentally that this assumption leads to complex hypothesis formation by human subjects attempting to solve comparatively simple problems involving a causal randomly generated events"

"The postulation of a principle of causality, “to every effect there is a cause,” has been a continuing central problem for philosophy (Popper, 1972). Its role as a source of contention in modern science (Jauch, 1973) is epitomized by Einstein’s remark that, “I can’t believe that God plays dice.” Many of the arguments about the application of the principle are very relevant to systems science and to problems of system identification and machine learning, on the one hand,and to epistemology and behavioural psychology, on the other. In current system science the theory of causal deterministic systems is most well developed and generally applied, while the theory of modeling with alternative structures, e.g., stochastic automata, indeterminate automata, products of asynchronous automata, etc., has not been developed to the same degree."

"s have long provided visual languages widely used in many different disciplines and application domains. Abstractly, they are sorted graphs visually represented as nodes having a type, name and content, some of which are linked by arcs. Concretely, they are structured diagrams having discipline- and domain-specific interpretations for their user communities, and, sometimes, formally defining computer data structures. Concept maps have been used for a wide range of purposes and it would be useful to make such usage available over the World Wide Web."

"The principle assumption made in Artificial Life is that the 'logical form' of an organism can be separated from its material basis of construction, and that 'aliveness' will be found to be a property of the former, not of the latter."

"Holland's and Kauffman's work, together with Dawkins' simulations of evolution and Varela's models of autopoietic systems, provide essential inspiration for the new discipline of artificial life, This approach, initiated by Chris Langton (1989, 1992), tries to develop technological systems (computer programs and autonomous robots) that exhibit lifelike properties, such as reproduction, sexuality, swarming, and co-evolution."

"Artificial Life is concerned with tuning the behaviors of such low-level machines that the behavior that emerges at the global level is essentially the same as some behavior exhibited by a natural living system... Artificial Life is concerned with generating lifelike behavior."

"There's a reason for poetry... Poetry is a very nonlinear use of language, where the meaning is more than just the sum of the parts. And science requires that it be nothing more than the sum of the parts. And just the fact that there's stuff to explain out there that's more than the sum of the parts means that the traditional approach, just characterizing the parts and the relations, is not going to be adequate for capturing the essence of many systems that you would like to be able to do. That's not to say that there isn't a way to do it in a more scientific way than poetry, but I just like the feeling that culturally there's going to be more of something like poetry in the future of science."

"Artificial Life [AL] is the study of man-made systems that exhibit behaviors characteristic of natural living systems. It complements the traditional biological sciences concerned with the analysis of living organisms by attempting to synthesize life-like behaviors within computers and other artificial media. By extending the empirical foundation upon which biology is based beyond the carbon-chain life that has evolved on Earth, Artificial Life can contribute to theoretical biology by locating life-as-we-know-it within the larger picture of life-as-it-could-be."

"You can see these two species coexisting in a long period of stability; then on of the them drops out and all hell breaks loose. Tremendous instability. That's the Soviet Union."

"Artificial Life (``AL or ``Alife) is the name given to a new discipline that studies "natural" life by attempting to recreate biological phenomena from scratch within computers and other "artificial" media. Alife complements the traditional analytic approach of traditional biology with a synthetic approach in which, rather than studying biological phenomena by taking apart living organisms to see how they work, one attempts to put together systems that behave like living organisms."

"Biology is the scientific study of life - in principle, anyway. In practice, biology is the scientific study of life on Earth based on carbon-chain chemistry. There is nothing in its charter that restricts biology to carbon-based life; it is simply that this is the only kind of life that has been available to study. Thus, theoretical biology has long faced the fundamental obstacle that it is impossible to derive general principles from single examples... Without other examples, it is difficult to distinguish essential properties of life - properties that would be shared by any living system - from properties that may be incidental to life in principle, but which happen to be universal to life on Earth due solely to a combination of local historical accident and common genetic descent."

"[AL] views life as a property of the organization of matter, rather than a property of the matter which is so organized. Whereas biology has largely concerned itself with the material basis of life, Artificial Life is concerned with the formal basis of life."

"Biological systems are dynamical, not easily predicted, and are creative in many ways... In the old equilibrium worldview, ideas about change were dominated by the action-reaction formula. It was a clockwork world, ultimately predictable in boring ways."

"A system in which a few things interacting produce tremendously divergent behavior; deterministic chaos; it looks random but its not."

"It starts at the bottom, viewing an organism as a large population of simple machines, and works upwards synthetically from there — constructing large aggregates of simple, rule-governed objects which interact with one another nonlinearly in the support of life-like, global dynamics. The ‘key' concept in AL is emergent behavior."