"Knowledge is of two kinds. We know a subject ourselves, or we know where we can find information upon it." (Samuel Johnson, 1775)
"It is almost as difficult to make a man unlearn his errors as his knowledge. Mal-information is more hopeless than non-information; for error is always more busy than ignorance. Ignorance is a blank sheet, on which we may write; but error is a scribbled one, on which we must first erase. Ignorance is contented to stand still with her back to the truth; but error is more presumptuous, and proceeds in the same direction. Ignorance has no light, but error follows a false one. The consequence is, that error, when she retraces her footsteps, has further to go, before she can arrive at the truth, than ignorance." (Charles C Colton, “Lacon”, 1820)
"In every branch of knowledge the progress is proportional to the amount of facts on which to build, and therefore to the facility of obtaining data." (James C Maxwell, [Letter to Lewis Campbell] 1851)
"[The information of a message can] be defined as the 'minimum number of binary decisions which enable the receiver to construct the message, on the basis of the data already available to him.' These data comprise both the convention regarding the symbols and the language used, and the knowledge available at the moment when the message started." (Dennis Gabor, "Optical transmission" in Information Theory : Papers Read at a Symposium on Information Theory, 1952)
"Knowledge is not something which exists and grows in the abstract. It is a function of human organisms and of social organization. Knowledge, that is to say, is always what somebody knows: the most perfect transcript of knowledge in writing is not knowledge if nobody knows it. Knowledge however grows by the receipt of meaningful information - that is, by the intake of messages by a knower which are capable of reorganising his knowledge." (Kenneth E Boulding, "General Systems Theory - The Skeleton of Science", Management Science Vol. 2 (3), 1956)
"The idea of knowledge as an improbable structure is still a good place to start. Knowledge, however, has a dimension which goes beyond that of mere information or improbability. This is a dimension of significance which is very hard to reduce to quantitative form. Two knowledge structures might be equally improbable but one might be much more significant than the other." (Kenneth E Boulding, "Beyond Economics: Essays on Society", 1968)
"It is not enough to observe, experiment, theorize, calculate and communicate; we must also argue, criticize, debate, expound, summarize, and otherwise transform the information that we have obtained individually into reliable, well established, public knowledge." (John M Ziman, "Information, Communication, Knowledge", Nature Vol. 224 (5217), 1969)
"In perception itself, two distinct processes can be discerned. One is the gathering of the primary, sensory data or simple sensing of such things as light, moisture or pressure, and the other is the structuring of such data into information." (Edward Ihnatowicz, "The Relevance of Manipulation to the Process of Perception", 1977)
"Data, seeming facts, apparent associations-these are not certain knowledge of something. They may be puzzles that can one day be explained; they may be trivia that need not be explained at all. (Kenneth Waltz, "Theory of International Politics", 1979)
"Knowledge is the appropriate collection of information, such that it's intent is to be useful. Knowledge is a deterministic process. When someone 'memorizes' information (as less-aspiring test-bound students often do), then they have amassed knowledge. This knowledge has useful meaning to them, but it does not provide for, in and of itself, an integration such as would infer further knowledge." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)
"Information is data that has been given meaning by way of relational connection. This 'meaning' can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it." (Russell L Ackoff, "Towards a Systems Theory of Organization", 1985)
"There is no coherent knowledge, i.e. no uniform comprehensive account of the world and the events in it. There is no comprehensive truth that goes beyond an enumeration of details, but there are many pieces of information, obtained in different ways from different sources and collected for the benefit of the curious. The best way of presenting such knowledge is the list - and the oldest scientific works were indeed lists of facts, parts, coincidences, problems in several specialized domains." (Paul K Feyerabend, "Farewell to Reason", 1987)
"Probabilities are summaries of knowledge that is left behind when information is transferred to a higher level of abstraction." (Judea Pearl, "Probabilistic Reasoning in Intelligent Systems: Network of Plausible, Inference", 1988)
"Information engineering has been defined with the reference to automated techniques as follows: An interlocking set of automated techniques in which enterprise models, data models and process models are built up in a comprehensive knowledge-base and are used to create and maintain data-processing systems." (James Martin, "Information Engineering, 1989)
"Knowledge is theory. We should be thankful if action of management is based on theory. Knowledge has temporal spread. Information is not knowledge. The world is drowning in information but is slow in acquisition of knowledge. There is no substitute for knowledge." (William E Deming, "The New Economics for Industry, Government, Education", 1993)
"Knowledge, truth, and information flow in networks and swarm systems. I have always been interested in the texture of scientific knowledge because it appears to be lumpy and uneven. Much of what we collectively know derives from a few small areas, yet between them lie vast deserts of ignorance. I can interpret that observation now as the effect of positive feedback and attractors. A little bit of knowledge illuminates much around it, and that new illumination feeds on itself, so one corner explodes. The reverse also holds true: ignorance breeds ignorance. Areas where nothing is known, everyone avoids, so nothing is discovered. The result is an uneven landscape of empty know-nothing interrupted by hills of self-organized knowledge." (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)
"Now that knowledge is taking the place of capital as the driving force in organizations worldwide, it is all too easy to confuse data with knowledge and information technology with information." (Peter Drucker, "Managing in a Time of Great Change", 1995)
"Data is discrimination between physical states of things (black, white, etc.) that may convey or not convey information to an agent. Whether it does so or not depends on the agent's prior stock of knowledge." (Max Boisot, "Knowledge Assets", 1998)
"The unit of coding is the most basic segment, or element, of the raw data or information that can be assessed in a meaningful way regarding the phenomenon." (Richard Boyatzis, "Transforming qualitative information", 1998)
"While hard data may inform the intellect, it is largely soft data that generates wisdom." (Henry Mintzberg, "Strategy Safari: A Guided Tour Through The Wilds of Strategic Management", 1998)
"Information is just bits of data. Knowledge is putting them together. Wisdom is transcending them." (Ram Dass, "One-Liners: A Mini-Manual for a Spiritual Life (ed. Harmony", 2007)
"Traditional statistics is strong in devising ways of describing data and inferring distributional parameters from sample. Causal inference requires two additional ingredients: a science-friendly language for articulating causal knowledge, and a mathematical machinery for processing that knowledge, combining it with data and drawing new causal conclusions about a phenomenon."(Judea Pearl, "Causal inference in statistics: An overview", Statistics Surveys 3, 2009)
"We also use our imagination and take shortcuts to fill gaps in patterns of nonvisual data. As with visual input, we draw conclusions and make judgments based on uncertain and incomplete information, and we conclude, when we are done analyzing the patterns, that out picture is clear and accurate. But is it?" (Leonard Mlodinow, "The Drunkard's Walk: How Randomness Rules Our Lives", 2009)
"We reach wisdom when we achieve a deep understanding of acquired knowledge, when we not only 'get it', but when new information blends with prior experience so completely that it makes us better at knowing what to do in other situations, even if they are only loosely related to the information from which our original knowledge came. Just as not all the information we absorb leads to knowledge, not all of the knowledge we acquire leads to wisdom." (Alberto Cairo, "The Functional Art", 2011)
"Any knowledge incapable of being revised with advances in data and human thinking does not deserve the name of knowledge." (Jerry Coyne, "Faith Versus Fact", 2015)
"The term data, unlike the related terms facts and evidence, does not connote truth. Data is descriptive, but data can be erroneous. We tend to distinguish data from information. Data is a primitive or atomic state (as in ‘raw data’). It becomes information only when it is presented in context, in a way that informs. This progression from data to information is not the only direction in which the relationship flows, however; information can also be broken down into pieces, stripped of context, and stored as data. This is the case with most of the data that’s stored in computer systems. Data that’s collected and stored directly by machines, such as sensors, becomes information only when it’s reconnected to its context." (Stephen Few, "Signal: Understanding What Matters in a World of Noise", 2015)
"Real wisdom is not the knowledge of everything, but the knowledge of which things in life are necessary, which are less necessary, and which are completely unnecessary to know." (Lev N Tolstoy)
"The Information Age offers much to mankind, and I would like to think that we will rise to the challenges it presents. But it is vital to remember that information - in the sense of raw data - is not knowledge, that knowledge is not wisdom, and that wisdom is not foresight. But information is the first essential step to all of these." (Arthur C Clark)
No comments:
Post a Comment