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1 Psychology
We come therefore now to that knowledge whereunto the ancient oracle directeth us, which is the knowledge of ourselves; which deserveth the more accurate handling, by how much it toucheth us more nearly. This knowledge, as it is the end and term of natural philosophy in the intention of man, so notwithstanding it is but a portion of natural philosophy in the continent of nature.... [W]e proceed to human philosophy or Humanity, which hath two parts: the one considereth man segregate, or distributively; the other congregate, or in society. So as Human philosophy is either Simple and Particular, or Conjugate and Civil. Humanity Particular consisteth of the same parts whereof man consisteth; that is, of knowledges which respect the Body, and of knowledges that respect the Mind... how the one discloseth the other and how the one worketh upon the other... [:] the one is honored with the inquiry of Aristotle, and the other of Hippocrates. (Bacon, 1878, pp. 236-237)The claims of Psychology to rank as a distinct science are... not smaller but greater than those of any other science. If its phenomena are contemplated objectively, merely as nervo-muscular adjustments by which the higher organisms from moment to moment adapt their actions to environing co-existences and sequences, its degree of specialty, even then, entitles it to a separate place. The moment the element of feeling, or consciousness, is used to interpret nervo-muscular adjustments as thus exhibited in the living beings around, objective Psychology acquires an additional, and quite exceptional, distinction. (Spencer, 1896, p. 141)Kant once declared that psychology was incapable of ever raising itself to the rank of an exact natural science. The reasons that he gives... have often been repeated in later times. In the first place, Kant says, psychology cannot become an exact science because mathematics is inapplicable to the phenomena of the internal sense; the pure internal perception, in which mental phenomena must be constructed,-time,-has but one dimension. In the second place, however, it cannot even become an experimental science, because in it the manifold of internal observation cannot be arbitrarily varied,-still less, another thinking subject be submitted to one's experiments, comformably to the end in view; moreover, the very fact of observation means alteration of the observed object. (Wundt, 1904, p. 6)It is [Gustav] Fechner's service to have found and followed the true way; to have shown us how a "mathematical psychology" may, within certain limits, be realized in practice.... He was the first to show how Herbart's idea of an "exact psychology" might be turned to practical account. (Wundt, 1904, pp. 6-7)"Mind," "intellect," "reason," "understanding," etc. are concepts... that existed before the advent of any scientific psychology. The fact that the naive consciousness always and everywhere points to internal experience as a special source of knowledge, may, therefore, be accepted for the moment as sufficient testimony to the rights of psychology as science.... "Mind," will accordingly be the subject, to which we attribute all the separate facts of internal observation as predicates. The subject itself is determined p. 17) wholly and exclusively by its predicates. (Wundt, 1904,The study of animal psychology may be approached from two different points of view. We may set out from the notion of a kind of comparative physiology of mind, a universal history of the development of mental life in the organic world. Or we may make human psychology the principal object of investigation. Then, the expressions of mental life in animals will be taken into account only so far as they throw light upon the evolution of consciousness in man.... Human psychology... may confine itself altogether to man, and generally has done so to far too great an extent. There are plenty of psychological text-books from which you would hardly gather that there was any other conscious life than the human. (Wundt, 1907, pp. 340-341)The Behaviorist began his own formulation of the problem of psychology by sweeping aside all medieval conceptions. He dropped from his scientific vocabulary all subjective terms such as sensation, perception, image, desire, purpose, and even thinking and emotion as they were subjectively defined. (Watson, 1930, pp. 5-6)According to the medieval classification of the sciences, psychology is merely a chapter of special physics, although the most important chapter; for man is a microcosm; he is the central figure of the universe. (deWulf, 1956, p. 125)At the beginning of this century the prevailing thesis in psychology was Associationism.... Behavior proceeded by the stream of associations: each association produced its successors, and acquired new attachments with the sensations arriving from the environment.In the first decade of the century a reaction developed to this doctrine through the work of the Wurzburg school. Rejecting the notion of a completely self-determining stream of associations, it introduced the task ( Aufgabe) as a necessary factor in describing the process of thinking. The task gave direction to thought. A noteworthy innovation of the Wurzburg school was the use of systematic introspection to shed light on the thinking process and the contents of consciousness. The result was a blend of mechanics and phenomenalism, which gave rise in turn to two divergent antitheses, Behaviorism and the Gestalt movement. The behavioristic reaction insisted that introspection was a highly unstable, subjective procedure.... Behaviorism reformulated the task of psychology as one of explaining the response of organisms as a function of the stimuli impinging upon them and measuring both objectively. However, Behaviorism accepted, and indeed reinforced, the mechanistic assumption that the connections between stimulus and response were formed and maintained as simple, determinate functions of the environment.The Gestalt reaction took an opposite turn. It rejected the mechanistic nature of the associationist doctrine but maintained the value of phenomenal observation. In many ways it continued the Wurzburg school's insistence that thinking was more than association-thinking has direction given to it by the task or by the set of the subject. Gestalt psychology elaborated this doctrine in genuinely new ways in terms of holistic principles of organization.Today psychology lives in a state of relatively stable tension between the poles of Behaviorism and Gestalt psychology.... (Newell & Simon, 1963, pp. 279-280)As I examine the fate of our oppositions, looking at those already in existence as guide to how they fare and shape the course of science, it seems to me that clarity is never achieved. Matters simply become muddier and muddier as we go down through time. Thus, far from providing the rungs of a ladder by which psychology gradually climbs to clarity, this form of conceptual structure leads rather to an ever increasing pile of issues, which we weary of or become diverted from, but never really settle. (Newell, 1973b, pp. 288-289)The subject matter of psychology is as old as reflection. Its broad practical aims are as dated as human societies. Human beings, in any period, have not been indifferent to the validity of their knowledge, unconcerned with the causes of their behavior or that of their prey and predators. Our distant ancestors, no less than we, wrestled with the problems of social organization, child rearing, competition, authority, individual differences, personal safety. Solving these problems required insights-no matter how untutored-into the psychological dimensions of life. Thus, if we are to follow the convention of treating psychology as a young discipline, we must have in mind something other than its subject matter. We must mean that it is young in the sense that physics was young at the time of Archimedes or in the sense that geometry was "founded" by Euclid and "fathered" by Thales. Sailing vessels were launched long before Archimedes discovered the laws of bouyancy [ sic], and pillars of identical circumference were constructed before anyone knew that C IID. We do not consider the ship builders and stone cutters of antiquity physicists and geometers. Nor were the ancient cave dwellers psychologists merely because they rewarded the good conduct of their children. The archives of folk wisdom contain a remarkable collection of achievements, but craft-no matter how perfected-is not science, nor is a litany of successful accidents a discipline. If psychology is young, it is young as a scientific discipline but it is far from clear that psychology has attained this status. (Robinson, 1986, p. 12)Historical dictionary of quotations in cognitive science > Psychology
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2 Bibliography
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Westport, CT: Praeger.■ Wagman, M. (2000). Scientific discovery processes in humans and computers: Theory and research in psychology and artificial intelligence. Westport, CT: Praeger.■ Wall, R. (1972). Introduction to mathematical linguistics. Englewood Cliffs, NJ: Prentice-Hall.■ Wallas, G. (1926). The Art of Thought. New York: Harcourt, Brace & Co.■ Wason, P. (1977). Self contradictions. In P. Johnson-Laird & P. Wason (Eds.), Thinking: Readings in cognitive science. Cambridge: Cambridge University Press.■ Wason, P. C., & P. N. Johnson-Laird. (1972). Psychology of reasoning: Structure and content. Cambridge, MA: Harvard University Press.■ Watson, J. (1930). Behaviorism. New York: W. W. Norton.■ Watzlawick, P. (1984). Epilogue. In P. Watzlawick (Ed.), The invented reality. New York: W. W. Norton, 1984.■ Weinberg, S. (1977). The first three minutes: A modern view of the origin of the uni verse. New York: Basic Books.■ Weisberg, R. W. (1986). Creativity: Genius and other myths. New York: W. H. Freeman.■ Weizenbaum, J. (1976). Computer power and human reason: From judgment to cal culation. San Francisco: W. H. Freeman.■ Wertheimer, M. (1945). Productive thinking. New York: Harper & Bros.■ Whitehead, A. N. (1925). Science and the modern world. New York: Macmillan.■ Whorf, B. L. (1956). In J. B. Carroll (Ed.), Language, thought and reality: Selected writings of Benjamin Lee Whorf. Cambridge, MA: MIT Press.■ Whyte, L. L. (1962). The unconscious before Freud. New York: Anchor Books.■ Wiener, N. (1954). The human use of human beings. Boston: Houghton Mifflin.■ Wiener, N. (1964). God & Golem, Inc.: A comment on certain points where cybernetics impinges on religion. Cambridge, MA: MIT Press.■ Winograd, T. (1972). Understanding natural language. New York: Academic Press.■ Winston, P. H. (1987). Artificial intelligence: A perspective. In E. L. Grimson & R. S. Patil (Eds.), AI in the 1980s and beyond (pp. 1-12). Cambridge, MA: MIT Press.■ Winston, P. H. (Ed.) (1975). The psychology of computer vision. New York: McGrawHill.■ Wittgenstein, L. (1953). Philosophical investigations. Oxford: Basil Blackwell.■ Wittgenstein, L. (1958). The blue and brown books. New York: Harper Colophon.■ Woods, W. A. (1975). What's in a link: Foundations for semantic networks. In D. G. Bobrow & A. Collins (Eds.), Representations and understanding: Studies in cognitive science (pp. 35-84). New York: Academic Press.■ Woodworth, R. S. (1938). Experimental psychology. New York: Holt; London: Methuen (1939).■ Wundt, W. (1904). Principles of physiological psychology (Vol. 1). E. B. Titchener (Trans.). New York: Macmillan.■ Wundt, W. (1907). Lectures on human and animal psychology. J. E. Creighton & E. B. Titchener (Trans.). New York: Macmillan.■ Young, J. Z. (1978). Programs of the brain. New York: Oxford University Press.■ Ziman, J. (1978). Reliable knowledge: An exploration of the grounds for belief in science. Cambridge: Cambridge University Press.Historical dictionary of quotations in cognitive science > Bibliography
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3 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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4 علم
عِلْم \ knowledge: what one knows: His knowledge of radio is very wide. His general knowledge is slight. learning: knowledge that is gained by long serious study: He is a man of great learning. scholarship: the qualities of a very learned person: This writer on Shakespeare is famous for his scholarship. science: the careful study of any serious subject: political science; the science of language. \ بِغَير عِلْمِه \ behind sb.’s back: when someone is not present: He tells untrue stories about me behind my back. \ عِلْم الآثار القَديمة \ archaeology, archeology: the scientific study of life in the distant past by digging up ancient cities, examining buried objects, etc. \ عِلْم الاجْتِماع \ sociology: the study of society and human behaviour in groups. \ عِلْم الإِحْصَاء \ statistics: (with pl. verb) facts that are shown by numbers; (with sg. verb) the science of showing facts by numbers: National statistics of births and deaths are collected regularly. Statistics is a modern science. \ عِلْم الأَحْياء \ biology: the science of living things. \ عِلْم الأخلاق \ ethics: the study of good and bad in human behaviour. \ عِلْم الأرصاد الجوّيّة \ meteorology: the science of the weather. \ عِلْم الأساطير \ mythology: myths in general; the study of myths. \ عِلْم الاشْتِقاق (في علم اللُّغَة) \ etymology: the study of the history of words. \ عِلْم الأصوات \ phonetics: (as subject of study; pl. as a practical activity) the science of speech sounds; the signs used for these sounds; the practical use of this science: Phonetics is a modern science. Are these phonetics correct? Phonetics help foreigners to pronounce words. \ عِلْم الاقتصاد \ economics: the science of national economy. \ عِلْم الإنْسَان \ anthropology: the scientific study of man, his way of life, religions, races, etc. \ عِلْم بالوُصُول \ acknowledg(e)ment: a note of receipt: I sent the money but I’ve had no acknowledgement. \ عِلْم التاريخ \ history: an orderly record or study of past events: a student of history; the history of Europe. \ عِلْم التَّحْليل النَّفْسي \ psychoanalysis: (the scientific study of) a way of treating disorders ot the mind by examination of all that sb. can remember of his past life, dreams, feelings, etc.. \ عِلْم التَّدْبِير المنزليّ \ domestic science: the study of cooking and other housekeeping skills. \ عِلْم التَّنْجيم \ astrology: the study of the stars in relation to human fate. \ عِلْم الجَبْر \ algebra: a branch of mathematics, using signs and letters as well as numbers. \ عِلْم الجُغْرافيا \ geography: the scientific study of the structure, produce and use of the earth’s surface. \ عِلْم الحَرْب \ warfare: the science of making war; fighting. \ عِلْم حَرَكة السوائل \ hydraulics: the science of controlling and using liquid pressure, esp. for engineering purposes. \ عِلْم الحَشَرات \ entomology: the study of insects. \ عِلْم الحَيَوان \ zoology: the scientific study of animal life. \ عِلْم الرِّياضيّات \ mathematics: the science of numbers and space; the practical use of this science: Mathematics is an exact science. maths: the usual shortening of mathematics. \ عِلْم الزراعة بدون تُربة \ hydroponics: the science of growing plants in water, without soil. \ عِلْم السِّيَاسَة \ politics: (sg. as an art or activity; pl. as personal beliefs, etc.) the art of government; the affairs of government; one’s opinions on government: Is politics an art or a science? My politics are my private concern. \ عِلْم الصحّة \ hygiene: the study and practice of how to keep good health, esp. by paying attention to cleaniness. \ عِلْم صيانة الأحراش \ forestry: the science of growing trees for man’s use as wood. \ عِلْم الطّبّ \ medicine: the science and the art of dealing with disease. \ عِلْم طَبَقات الأرض \ geology: the study of the rocks that make up the earth. \ عِلْم الطبيعة \ physics: the science of heat, light, sound, Motion, etc.: Physics is an important branch of science. \ See Also الفيزياء \ عِلْم طبيعيّ \ science: the study of the substances, forces, etc. found in nature (esp. Biology; Chemistry; Physics): Schools teach science. \ عِلْم الطُّيُور \ ornithology: the scientific study of birds. \ عِلْم الفَلَك \ astronomy: the scientific study of the stars. \ عِلْم الكِيمْياء \ chemistry: the science that studies the nature and behaviour of all substances. \ عِلْم المالية \ finance: the science of controlling money. \ See Also إدارة المال \ عِلْم المَنْطِق \ logic: the science of reasoning. \ عِلْم النَّبَات \ botany: the scientific study of plants. \ عِلْم النَّفْس \ psychology: the scientific study of the mind. \ عِلْم الهَنْدَسة \ geometry: the science of lines, angles, surfaces and solid figures, and of their measurements.
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