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Artificial Intelligence Is an Engineering Discipline

  • 1 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, Eventually
       Just 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)
       Many 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 Form
       The 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 Formation
       It 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 Contexts
       Even 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)
        18) The Assumption That the Mind Is a Formal System
       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 Intelligence
       The 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 Propositions
       In 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

  • 2 conocimiento

    m.
    1 knowledge.
    hablar/actuar con conocimiento de causa to know what one is talking about/doing
    poner algo en conocimiento de alguien to bring something to somebody's attention, to inform somebody of something
    tener conocimiento de algo to be aware of something
    ha llegado a mi conocimiento que estás insatisfecho it has come to my attention that you are not happy
    2 consciousness (sentido, conciencia).
    perder/recobrar el conocimiento to lose/regain consciousness
    estaba tumbado en el suelo, sin conocimiento he was lying unconscious on the floor
    3 awareness, consciousness, cognizance.
    * * *
    1 (In 1, also used in plural with the same meaning) (saber) knowledge
    2 (sensatez) good sense
    3 (conciencia) consciousness
    \
    con conocimiento de causa with full knowledge of the facts
    perder el conocimiento to lose consciousness
    poner algo en conocimiento de alguien to make something known to somebody, inform somebody of something
    recobrar el conocimiento to regain consciousness, come round
    tener conocimiento de algo to know about something
    * * *
    noun m.
    * * *
    SM
    1) (=saber) knowledge

    conocimientos — (=nociones) knowledge sing

    mis pocos conocimientos de filosofía/cocina — my limited knowledge of philosophy/cookery

    2) (=información) knowledge

    • dar conocimiento de algo, dimos conocimiento del robo a la policía — we informed the police about the robbery

    • llegar a conocimiento de algn — to come to sb's attention o notice

    • tener conocimiento de algo, aún no tenemos conocimiento de su detención — we still do not know that he has been arrested

    desea ponerlo en conocimiento público — he wants it brought to the public's attention, he wishes it to be made public

    conocimiento de causa, hacer algo con conocimiento de causa — to be fully aware of what one is doing

    3) (=consciencia) consciousness

    recobrar o recuperar el conocimiento — to regain consciousness

    4) (=sentido común) common sense
    5) (Jur) cognizance frm
    6) (Com)
    * * *
    1)
    a) ( saber) knowledge
    b) conocimientos masculino plural ( nociones) knowledge
    2) (frml) ( información)

    dar conocimiento de algo a alguien — to inform o (frml) apprise somebody of something

    pongo en su conocimiento que... — (Corresp) I am writing to inform you that...

    con conocimiento de causa: obró con conocimiento de causa (frml) he took this step, fully aware of what the consequences would be; hablo con conocimiento de causa — I know what I'm talking about

    3) ( sentido) consciousness

    perder/recobrar el conocimiento — to lose/regain consciousness

    aún es pequeño, no tiene todavía conocimiento — he's not old enough to understand

    * * *
    = cognition, competency, enlightenment, expertise, familiarisation [familiarization, -USA], familiarity, insight, knowledge, learning, acquaintance, understanding, cognisance [cognizance, -USA], connoisseurship, consciousness.
    Ex. The information-processing model of cognition, and developments in artificial intelligence encourage such comparisons = El modelo de la cognición sobre el procesamiento de la información de y los avances de la inteligencia artificial fomentan este tipo de comparaciones.
    Ex. SLIS programmes intended to 'produce' librarians with competency in the use of IT have to be designed.
    Ex. Considered as necessary work in the interest of humanity and general enlightenment, bibliography gains ground as the years pass.
    Ex. Its primary function is to provide a centre for software and hardware expertise for its members.
    Ex. Step 1 Familiarisation: This first step involves the indexer in becoming conversant with the subject content of the document to be indexed.
    Ex. The most effective searchers are those who have both system experience and some familiarity with the subject area in which they are searching.
    Ex. The human indexer works mechanically and rapidly; he should require no insight into the document content.
    Ex. These factors form the basis of the problems in identifying a satisfactory subject approach, and start to explain the vast array of different tolls used in the subject approach to knowledge.
    Ex. It is the responsibility of educators to stretch their student's intellects, hone their skills of intuitive judgment and synthesis, and build a love of learning that will sustain them beyond the level of formal education.
    Ex. It is only with accumulating experience and many years of close study and acquaintance with bibliographic works that a really substantial body of knowledge of the potential of bibliographic sources is acquired.
    Ex. We librarians ought to have a clearer understanding of our stock-in-trade (books) and their function of social mechanism.
    Ex. The passive cognisance of growth causes considerable difficulties = El conocimiento pasivo del crecimiento causa dificultades importantes.
    Ex. This book explores the underlying institutional factors that help museum-based connoisseurship and aestheticism and university-based critical theory and revisionist scholarship exist.
    Ex. For example, the latter are unlikely to engage themselves in conservation issues as these now press upon the professional consciousness of librarians.
    ----
    * actualizar los conocimientos = upgrade + Posesivo + skills.
    * adquirir conocimiento = gain + knowledge, glean + knowledge, acquire + knowledge, build up + knowledge.
    * ampliar el conocimiento = expand + Posesivo + knowledge, expand + Posesivo + knowledge, widen + knowledge, broaden + knowledge, deepen + understanding.
    * ampliar las fronteras del conocimiento = push back + the frontiers of knowledge.
    * análisis de áreas del conocimiento = domain analysis.
    * análisis de dominios del conocimiento = domain analysis.
    * aprendizaje rico en conocimiento = knowledge-rich learning.
    * área de conocimiento = area of study.
    * área del conocimiento = area of knowledge, discipline, subject field, field of activity, knowledge domain, discipline of knowledge.
    * aumentar el conocimiento = expand + Posesivo + knowledge, deepen + awareness.
    * aumento del conocimiento = knowledge building.
    * bannco de conocimiento = knowledge bank.
    * basado en el conocimiento = knowledge-based.
    * basado en las disciplinas del conocimiento = discipline-based.
    * bibliotecario con conocimientos de medicina = informationist.
    * búsqueda del conocimiento = quest for/of knowledge.
    * campo del conocimiento = field of knowledge.
    * centrado en el conocimiento = knowledge-centric.
    * ciencia del conocimiento = cognitive science.
    * compartir el conocimiento = knowledge sharing, pool + knowledge.
    * con conocimiento = authoritatively.
    * con conocimiento básico en el manejo de la información = information literate [information-literate].
    * con conocimiento básico en el uso de la biblioteca = library literate [library-literate].
    * con conocimiento de = appreciative of, conversant with.
    * con conocimiento de causa = knowingly, knowingly.
    * con conocimiento de informática = computer literate [computer-literate].
    * con conocimiento en el uso de Internet = Internet-savvy.
    * con conocimientos en = versed in.
    * con conocimientos sobre el correo electrónico = e-mail literate.
    * con el conocimiento de que = on the understanding that.
    * conjunto de conocimientos = body of knowledge.
    * conocimiento académico = academic knowledge.
    * conocimiento acumulado sobre un tema = lore.
    * conocimiento básico = working familiarity, working knowledge.
    * conocimiento científico = scientific knowledge.
    * conocimiento compartido = knowledge sharing.
    * conocimiento de base = foundation study.
    * conocimiento de cómo sobrevivir en el bosque = woodcraft.
    * conocimiento de embarque = bill of lading.
    * conocimiento de la existencia = awareness.
    * conocimiento de lengua = language skill.
    * conocimiento del objeto = object knowledge.
    * conocimiento de los diferentes soportes = media competency.
    * conocimiento detallado = intimate knowledge.
    * conocimiento de un área temática = area knowledge.
    * conocimiento documentado = recorded knowledge.
    * conocimiento enciclopédico = factual knowledge.
    * conocimiento en tecnología = technological skill.
    * conocimiento específico = expert knowledge.
    * conocimiento experto = expert knowledge, expertise.
    * conocimiento explícito = explicit knowledge.
    * conocimiento factual = declarative knowledge.
    * conocimiento humano = human consciousness.
    * conocimiento humano, el = human record, the.
    * conocimiento indígena = indigenous knowledge.
    * conocimiento lingüístico = language skill.
    * conocimiento mutuo = mutual knowledge.
    * conocimiento pasivo = nodding acquaintance.
    * conocimiento pleno = awareness.
    * conocimiento práctico = working knowledge, procedural knowledge.
    * conocimiento previo = foreknowledge.
    * conocimientos = knowledge base [knowledge-base].
    * conocimientos básicos = literacy.
    * conocimientos básicos de búsqueda, recuperación y organización de informació = information literacy.
    * conocimientos básicos de documentación = information literacy.
    * conocimientos básicos de informática = computer literacy.
    * conocimientos básicos en tecnología = technical literacy.
    * conocimientos básicos sobre el uso de las bibliotecas = library skills.
    * conocimientos de tecnología = techno-savvy, tech-savvy.
    * conocimientos en el manejo de la información = info-savvy.
    * conocimiento sobre una materia = subject knowledge.
    * conocimientos requeridos = job specs.
    * conocimiento tácito = tacit knowledge, tacit knowledge, tacit knowledge.
    * conocimiento técnico = know-how, technical knowledge.
    * conocimiento teórico = declarative knowledge.
    * con poco conocimiento de las nuevas tecnologías = technologically challenged.
    * corpus de conocimiento = corpus of knowledge.
    * crear un fondo común de conocimientos = pool + knowledge.
    * cúmulo de conocimiento = repository of knowledge, knowledge repository.
    * decisión con conocimiento de causa = informed decision.
    * difundir el conocimiento = spread + knowledge.
    * director ejecutivo de la gestión del conocimiento = knowledge executive.
    * dominio del conocimiento = knowledge domain.
    * economía basada en el conocimiento = knowledge driven economy.
    * economía del conocimiento = knowledge economy.
    * Era del Conocimiento, la = Knowledge Age, the.
    * estructuración del conocimiento = knowledge structuring.
    * examinar los conocimientos = test + knowledge.
    * falta de conocimiento = unfamiliarity.
    * filtro del conocimiento = knowledge filter.
    * fomentar el conocimiento = advance + knowledge.
    * fondo común de conocimientos = pool of knowledge, pool of expertise.
    * frontera del conocimiento = frontier of knowledge.
    * fundamentos del conocimiento, los = foundations of knowledge, the.
    * gestión del conocimiento = knowledge management (KM).
    * gestor del conocimiento = knowledge worker, knowledge manager.
    * hacer avanzar el conocimiento = push back + the frontiers of knowledge.
    * hacer gala del conocimiento que uno tiene = air + knowledge.
    * hacer perder el conocimiento = knock + Nombre + out, knock + Nombre + unconscious.
    * hacer uso de un conocimiento = draw on/upon + knowledge.
    * impartir conocimiento = impart + knowledge.
    * inculcar conocimiento = instil + knowledge.
    * ingeniería del conocimiento = knowledge engineering.
    * ingeniero del conocimiento = knowledge engineer.
    * institucion del conocimiento = institution of learning.
    * intercambio de conocimientos = learning exchange, cross-fertilisation [cross-fertilization, -USA], cross-fertilisation of knowledge.
    * jefe de los servicios de gestión del conocimiento = chief knowledge officer (CKO).
    * metaconocimiento = meta-knowledge.
    * navegación por el conocimiento = knowledge navigation.
    * navegador del conocimiento = knowledge navigator.
    * obtener conocimiento = gain + an understanding.
    * ofrecer conocimiento = package + knowledge.
    * perder el conocimiento = lose + Posesivo + senses, pass out, lose + Posesivo + consciousness.
    * pérdida del conocimiento = unconsciousness, fainting, fainting fit, loss of consciousness.
    * personas sin conocimientos técnicos, las = non-technical, the.
    * presentar conocimiento = package + knowledge.
    * producto del conocimiento = knowledge record.
    * profundizar en el conocimiento = deepen + knowledge.
    * propagar el conocimiento = propagate + knowledge.
    * proporcionar conocimientos técnicos = supply + know-how.
    * quedarse sin conocimiento = lose + Posesivo + consciousness, pass out.
    * rama del conocimiento = branch of learning.
    * recobrar el conocimiento = regain + Posesivo + consciousness.
    * recuperar el conocimiento = regain + Posesivo + consciousness.
    * red de conocimiento = knowledge network.
    * servidor del conocimiento = knowledge server.
    * sin conocimiento = unconscious.
    * sin conocimiento de causa = unbeknown to, unbeknownst to.
    * sintetizar el conocimiento = synthesise + knowledge.
    * sistema basado en el conocimiento = knowledge-base system.
    * sistema de gestión del conocimiento = knowledge management system (KMS).
    * sociedad basada en el conocimiento = knowledge based society.
    * sociedad del conocimiento = knowledge society.
    * Sociedad para el Conocimiento Global = Global Knowledge Partnership.
    * suministrar conocimientos técnicos = supply + know-how.
    * tener conocimiento de = be privy to, be aware of.
    * toma de decisiones con conocimiento de causa = informed decision making.
    * tomar decisiones con conocimiento de causa = make + informed decisions.
    * transferencia de conocimiento = transfer of knowledge, knowledge transfer.
    * utilizar los conocimientos de Uno = put + Posesivo + knowledge to work.
    * * *
    1)
    a) ( saber) knowledge
    b) conocimientos masculino plural ( nociones) knowledge
    2) (frml) ( información)

    dar conocimiento de algo a alguien — to inform o (frml) apprise somebody of something

    pongo en su conocimiento que... — (Corresp) I am writing to inform you that...

    con conocimiento de causa: obró con conocimiento de causa (frml) he took this step, fully aware of what the consequences would be; hablo con conocimiento de causa — I know what I'm talking about

    3) ( sentido) consciousness

    perder/recobrar el conocimiento — to lose/regain consciousness

    aún es pequeño, no tiene todavía conocimiento — he's not old enough to understand

    * * *
    = cognition, competency, enlightenment, expertise, familiarisation [familiarization, -USA], familiarity, insight, knowledge, learning, acquaintance, understanding, cognisance [cognizance, -USA], connoisseurship, consciousness.

    Ex: The information-processing model of cognition, and developments in artificial intelligence encourage such comparisons = El modelo de la cognición sobre el procesamiento de la información de y los avances de la inteligencia artificial fomentan este tipo de comparaciones.

    Ex: SLIS programmes intended to 'produce' librarians with competency in the use of IT have to be designed.
    Ex: Considered as necessary work in the interest of humanity and general enlightenment, bibliography gains ground as the years pass.
    Ex: Its primary function is to provide a centre for software and hardware expertise for its members.
    Ex: Step 1 Familiarisation: This first step involves the indexer in becoming conversant with the subject content of the document to be indexed.
    Ex: The most effective searchers are those who have both system experience and some familiarity with the subject area in which they are searching.
    Ex: The human indexer works mechanically and rapidly; he should require no insight into the document content.
    Ex: These factors form the basis of the problems in identifying a satisfactory subject approach, and start to explain the vast array of different tolls used in the subject approach to knowledge.
    Ex: It is the responsibility of educators to stretch their student's intellects, hone their skills of intuitive judgment and synthesis, and build a love of learning that will sustain them beyond the level of formal education.
    Ex: It is only with accumulating experience and many years of close study and acquaintance with bibliographic works that a really substantial body of knowledge of the potential of bibliographic sources is acquired.
    Ex: We librarians ought to have a clearer understanding of our stock-in-trade (books) and their function of social mechanism.
    Ex: The passive cognisance of growth causes considerable difficulties = El conocimiento pasivo del crecimiento causa dificultades importantes.
    Ex: This book explores the underlying institutional factors that help museum-based connoisseurship and aestheticism and university-based critical theory and revisionist scholarship exist.
    Ex: For example, the latter are unlikely to engage themselves in conservation issues as these now press upon the professional consciousness of librarians.
    * actualizar los conocimientos = upgrade + Posesivo + skills.
    * adquirir conocimiento = gain + knowledge, glean + knowledge, acquire + knowledge, build up + knowledge.
    * ampliar el conocimiento = expand + Posesivo + knowledge, expand + Posesivo + knowledge, widen + knowledge, broaden + knowledge, deepen + understanding.
    * ampliar las fronteras del conocimiento = push back + the frontiers of knowledge.
    * análisis de áreas del conocimiento = domain analysis.
    * análisis de dominios del conocimiento = domain analysis.
    * aprendizaje rico en conocimiento = knowledge-rich learning.
    * área de conocimiento = area of study.
    * área del conocimiento = area of knowledge, discipline, subject field, field of activity, knowledge domain, discipline of knowledge.
    * aumentar el conocimiento = expand + Posesivo + knowledge, deepen + awareness.
    * aumento del conocimiento = knowledge building.
    * bannco de conocimiento = knowledge bank.
    * basado en el conocimiento = knowledge-based.
    * basado en las disciplinas del conocimiento = discipline-based.
    * bibliotecario con conocimientos de medicina = informationist.
    * búsqueda del conocimiento = quest for/of knowledge.
    * campo del conocimiento = field of knowledge.
    * centrado en el conocimiento = knowledge-centric.
    * ciencia del conocimiento = cognitive science.
    * compartir el conocimiento = knowledge sharing, pool + knowledge.
    * con conocimiento = authoritatively.
    * con conocimiento básico en el manejo de la información = information literate [information-literate].
    * con conocimiento básico en el uso de la biblioteca = library literate [library-literate].
    * con conocimiento de = appreciative of, conversant with.
    * con conocimiento de causa = knowingly, knowingly.
    * con conocimiento de informática = computer literate [computer-literate].
    * con conocimiento en el uso de Internet = Internet-savvy.
    * con conocimientos en = versed in.
    * con conocimientos sobre el correo electrónico = e-mail literate.
    * con el conocimiento de que = on the understanding that.
    * conjunto de conocimientos = body of knowledge.
    * conocimiento académico = academic knowledge.
    * conocimiento acumulado sobre un tema = lore.
    * conocimiento básico = working familiarity, working knowledge.
    * conocimiento científico = scientific knowledge.
    * conocimiento compartido = knowledge sharing.
    * conocimiento de base = foundation study.
    * conocimiento de cómo sobrevivir en el bosque = woodcraft.
    * conocimiento de embarque = bill of lading.
    * conocimiento de la existencia = awareness.
    * conocimiento de lengua = language skill.
    * conocimiento del objeto = object knowledge.
    * conocimiento de los diferentes soportes = media competency.
    * conocimiento detallado = intimate knowledge.
    * conocimiento de un área temática = area knowledge.
    * conocimiento documentado = recorded knowledge.
    * conocimiento enciclopédico = factual knowledge.
    * conocimiento en tecnología = technological skill.
    * conocimiento específico = expert knowledge.
    * conocimiento experto = expert knowledge, expertise.
    * conocimiento explícito = explicit knowledge.
    * conocimiento factual = declarative knowledge.
    * conocimiento humano = human consciousness.
    * conocimiento humano, el = human record, the.
    * conocimiento indígena = indigenous knowledge.
    * conocimiento lingüístico = language skill.
    * conocimiento mutuo = mutual knowledge.
    * conocimiento pasivo = nodding acquaintance.
    * conocimiento pleno = awareness.
    * conocimiento práctico = working knowledge, procedural knowledge.
    * conocimiento previo = foreknowledge.
    * conocimientos = knowledge base [knowledge-base].
    * conocimientos básicos = literacy.
    * conocimientos básicos de búsqueda, recuperación y organización de informació = information literacy.
    * conocimientos básicos de documentación = information literacy.
    * conocimientos básicos de informática = computer literacy.
    * conocimientos básicos en tecnología = technical literacy.
    * conocimientos básicos sobre el uso de las bibliotecas = library skills.
    * conocimientos de tecnología = techno-savvy, tech-savvy.
    * conocimientos en el manejo de la información = info-savvy.
    * conocimiento sobre una materia = subject knowledge.
    * conocimientos requeridos = job specs.
    * conocimiento tácito = tacit knowledge, tacit knowledge, tacit knowledge.
    * conocimiento técnico = know-how, technical knowledge.
    * conocimiento teórico = declarative knowledge.
    * con poco conocimiento de las nuevas tecnologías = technologically challenged.
    * corpus de conocimiento = corpus of knowledge.
    * crear un fondo común de conocimientos = pool + knowledge.
    * cúmulo de conocimiento = repository of knowledge, knowledge repository.
    * decisión con conocimiento de causa = informed decision.
    * difundir el conocimiento = spread + knowledge.
    * director ejecutivo de la gestión del conocimiento = knowledge executive.
    * dominio del conocimiento = knowledge domain.
    * economía basada en el conocimiento = knowledge driven economy.
    * economía del conocimiento = knowledge economy.
    * Era del Conocimiento, la = Knowledge Age, the.
    * estructuración del conocimiento = knowledge structuring.
    * examinar los conocimientos = test + knowledge.
    * falta de conocimiento = unfamiliarity.
    * filtro del conocimiento = knowledge filter.
    * fomentar el conocimiento = advance + knowledge.
    * fondo común de conocimientos = pool of knowledge, pool of expertise.
    * frontera del conocimiento = frontier of knowledge.
    * fundamentos del conocimiento, los = foundations of knowledge, the.
    * gestión del conocimiento = knowledge management (KM).
    * gestor del conocimiento = knowledge worker, knowledge manager.
    * hacer avanzar el conocimiento = push back + the frontiers of knowledge.
    * hacer gala del conocimiento que uno tiene = air + knowledge.
    * hacer perder el conocimiento = knock + Nombre + out, knock + Nombre + unconscious.
    * hacer uso de un conocimiento = draw on/upon + knowledge.
    * impartir conocimiento = impart + knowledge.
    * inculcar conocimiento = instil + knowledge.
    * ingeniería del conocimiento = knowledge engineering.
    * ingeniero del conocimiento = knowledge engineer.
    * institucion del conocimiento = institution of learning.
    * intercambio de conocimientos = learning exchange, cross-fertilisation [cross-fertilization, -USA], cross-fertilisation of knowledge.
    * jefe de los servicios de gestión del conocimiento = chief knowledge officer (CKO).
    * metaconocimiento = meta-knowledge.
    * navegación por el conocimiento = knowledge navigation.
    * navegador del conocimiento = knowledge navigator.
    * obtener conocimiento = gain + an understanding.
    * ofrecer conocimiento = package + knowledge.
    * perder el conocimiento = lose + Posesivo + senses, pass out, lose + Posesivo + consciousness.
    * pérdida del conocimiento = unconsciousness, fainting, fainting fit, loss of consciousness.
    * personas sin conocimientos técnicos, las = non-technical, the.
    * presentar conocimiento = package + knowledge.
    * producto del conocimiento = knowledge record.
    * profundizar en el conocimiento = deepen + knowledge.
    * propagar el conocimiento = propagate + knowledge.
    * proporcionar conocimientos técnicos = supply + know-how.
    * quedarse sin conocimiento = lose + Posesivo + consciousness, pass out.
    * rama del conocimiento = branch of learning.
    * recobrar el conocimiento = regain + Posesivo + consciousness.
    * recuperar el conocimiento = regain + Posesivo + consciousness.
    * red de conocimiento = knowledge network.
    * servidor del conocimiento = knowledge server.
    * sin conocimiento = unconscious.
    * sin conocimiento de causa = unbeknown to, unbeknownst to.
    * sintetizar el conocimiento = synthesise + knowledge.
    * sistema basado en el conocimiento = knowledge-base system.
    * sistema de gestión del conocimiento = knowledge management system (KMS).
    * sociedad basada en el conocimiento = knowledge based society.
    * sociedad del conocimiento = knowledge society.
    * Sociedad para el Conocimiento Global = Global Knowledge Partnership.
    * suministrar conocimientos técnicos = supply + know-how.
    * tener conocimiento de = be privy to, be aware of.
    * toma de decisiones con conocimiento de causa = informed decision making.
    * tomar decisiones con conocimiento de causa = make + informed decisions.
    * transferencia de conocimiento = transfer of knowledge, knowledge transfer.
    * utilizar los conocimientos de Uno = put + Posesivo + knowledge to work.

    * * *
    A
    1 (saber) knowledge
    tiene algunos conocimientos de inglés he has some knowledge of English, he knows some English
    B ( frml)
    (información): dio conocimiento del suceso a las autoridades he informed o ( frml) apprised the authorities of the incident
    puso el hecho en conocimiento de la policía she informed the police of the incident, she reported the incident to the police
    pongo en su conocimiento que … ( Corresp) I am writing to inform you that …
    al tener conocimiento del suceso upon learning of the incident ( frml)
    a esas horas no se tenía todavía conocimiento de la noticia at that time we/they still had not heard the news
    ciertas personas tienen conocimiento de sus actividades certain people are aware of her activities
    llegar a conocimiento de algn to come to sb's attention o notice ( frml)
    con conocimiento de causa: obró con conocimiento de causa ( frml); he took this step, fully aware of what the consequences would be
    te lo digo con conocimiento de causa I know what I'm talking about
    Compuesto:
    bill of lading, waybill
    C (sentido) consciousness
    perder el conocimiento to lose consciousness
    cuando recobró el conocimiento when he regained consciousness, when he came to o round
    estar sin conocimiento to be unconscious
    D
    (entendimiento): aún es pequeño, no tiene todavía conocimiento he's not old enough to understand
    * * *

     

    conocimiento sustantivo masculino


    poner algo en conocimiento de algn to inform sb of sth;
    tener conocimiento de algo to be aware of sth

    ◊ perder/recobrar el conocimiento to lose/regain consciousness;

    estar sin conocimiento to be unconscious
    conocimiento sustantivo masculino
    1 knowledge
    2 (conciencia) consciousness
    3 conocimientos, knowledge
    ♦ Locuciones: perder/recobrar el conocimiento, to lose/regain consciousness
    con conocimiento de causa, with full knowledge of the facts
    ' conocimiento' also found in these entries:
    Spanish:
    braga
    - ciencia
    - conciencia
    - desfallecer
    - desvanecerse
    - dominio
    - error
    - orientación
    - parcela
    - revelar
    - sentida
    - sentido
    - experiencia
    - perder
    - pérdida
    - reanimar
    - recobrar
    - saber
    English:
    acquaintance
    - air
    - black out
    - blackout
    - cognizance
    - come to
    - comprehensive
    - consciousness
    - familiarity
    - grounding
    - improve
    - knock out
    - knowledge
    - notice
    - privy
    - recover
    - self-awareness
    - sketchy
    - superficial
    - thorough
    - unconsciousness
    - black
    - knock
    - know
    - pass
    * * *
    1. [saber] knowledge;
    hablar/actuar con conocimiento de causa to know what one is talking about/doing;
    puso el robo en conocimiento de la policía she informed the police of the burglary;
    ponemos en su conocimiento que se ha detectado un error en el programa this is to inform you that an error has been detected in the program;
    no teníamos conocimiento de su dimisión we were not aware that he had resigned;
    al tener conocimiento del accidente, acudió inmediatamente al hospital when she found out about the accident she immediately went to the hospital;
    ha llegado a mi conocimiento que estás insatisfecho it has come to my attention that you are not happy
    2.
    conocimientos [nociones] knowledge;
    tengo algunos conocimientos de informática I have some knowledge of computers, I know a bit about computers;
    nuestros conocimientos acerca de la enfermedad son muy limitados our knowledge of the disease is very limited, we know very little about the disease
    3. [sentido, conciencia] consciousness;
    perder el conocimiento to lose consciousness;
    recobrar el conocimiento to regain consciousness;
    estaba tumbado en el suelo, sin conocimiento he was lying unconscious on the floor
    4. [juicio] (common) sense;
    5. Com conocimiento de embarque bill of lading
    * * *
    m
    1 knowledge;
    con conocimiento de causa hacer algo fully aware of the consequences;
    para su conocimiento for your information;
    conocimientos pl ( nociones) knowledge sg
    2 MED consciousness;
    perder el conocimiento lose consciousness;
    sin conocimiento unconscious;
    recobrar el conocimiento regain consciousness
    * * *
    1) : knowledge
    2) sentido: consciousness
    * * *
    1. (en general) knowledge
    2. (sentido) consciousness

    Spanish-English dictionary > conocimiento

См. также в других словарях:

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