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conscious approach

Толкование Перевод

1 conscious approach

сознательный подход

Politics english-russian dictionary > conscious approach
2 conscious approach to work

Политика: сознательное отношение к труду

Универсальный англо-русский словарь > conscious approach to work
3 approach

1. n
1) подход, метод

2) pl подступы

•

to adopt an approach — вырабатывать подход

to champion an approach — выступать за какой-л. подход

to change one's approach — изменять свой подход

to demand a separate approach — требовать особого подхода

to develop an approach — разрабатывать подход

to find a new approach to old problems — находить новый подход к решению старых проблем

to formulate a new approach — формулировать новый подход

to make an approach — вступать в контакт, завязывать отношения

to modify smb's approach to smth — изменять чей-л. подход к чему-л.

to practice an individual approach to smb — практиковать индивидуальный подход к кому-л.

to show a reasonable approach — проявлять разумный подход

to soften one's approach to smth — смягчать свой подход к чему-л.

to take an approach — придерживаться какого-л. подхода, применять какой-л. метод

to use an approach — использовать метод

- ad hoc approach
- all-inclusive approach
- alternative approach
- approach to a problem
- approach to policy making
- balanced approach
- biased approach
- blanket approach
- bureaucratic approach
- businesslike approach
- carrot-and-stick approach
- case-by-case approach
- cautious approach
- class approach
- coherent approach
- combined approach
- common approach
- comprehensive approach
- concerted approach
- conciliatory approach
- concrete approach
- conscious approach
- consensual approach
- constructive approach
- coordinated approach
- creative approach
- critical approach
- democratic approach
- departmental approach
- dialectical approach
- diplomatic approach
- divide-and-rule approach
- dynamic approach
- economic approach
- effective approach
- environmentally sound approach
- equitable approach
- even-handed approach
- flexible approach
- forecasting approach
- formalist approach
- forthright approach
- fresh approach
- fuzzy approach
- general approach
- global approach
- gradualist approach
- hard-line approach
- heavy-handed approach
- historical approach
- holistic approach
- impartial approach
- incremental approach
- individual approach
- informal approach
- integrated approach
- interdisciplinary approach
- kid-glove approach
- liberalized approach
- lop-sided approach
- low-keyed approach
- metaphysical approach
- multilateral approach
- multipronged approach
- new approach
- nonrealistic approach
- nonviolent approach
- on the approaches to a city
- one-sided approach
- open approach
- overall approach
- package approach
- partial approach
- personal approach
- petty-minded approach
- phased approach
- piecemeal approach
- pluralistic approach
- politically effective approach
- positive approach
- practical approach
- pragmatic approach
- principled approach
- priority approach
- proper approach
- rational approach
- realistic approach
- rethink of smb's approach to smth
- revolutionary approach
- rigid approach
- scholarly approach
- scholastic approach
- scientific approach
- sectorial approach
- separate approach
- simplified approach
- soft approach
- softly-softly approach
- stage-by-stage approach
- statistical approach
- step-by-step approach
- theoretical approach
- tolerant approach
- tough approach
- traditional approach
- umbrella approach
- unbiased approach
- unified approach
- uniform approach
- unofficial approach
- unrealistic approach
- unscientific approach
- utilitarian approach
- wait-and-see approach 2. v
обращаться (к кому-л. с просьбой, предложением); вступать в контакт; вступать в переговоры

Politics english-russian dictionary > approach
4 return responsibility approach

return responsibility approach POL, ECON, SOC (Deu) Gegenforderungs-Ansatz m, Fordern-Ansatz m, Fordern-Konzept n (sozialpolitischer Grundsatz der Einforderung sozialverantwortlichen Verhaltens = socially responsible behaviour = socially conscious behaviour von Sozialhilfeempfängern = recipients of social assistance im Gegenzug zur staatlichen Förderung: cf Fördern und Fordern, support for recipients and responsibilities in return; cf Hartz IV = Hartz IV Law = Viertes Gesetz für moderne Dienstleistungen am Arbeitsmarkt = Fourth Act Promoting Modern Labour Market Services; Workfare-Ansatz)

Englisch-Deutsch Fachwörterbuch der Wirtschaft > return responsibility approach
5 Bibliography

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■ 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
6 Artificial Intelligence

   1) Programs and the Complexity of Human Mental Processes

   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)

   2) Artificial Intelligence Is an Engineering Discipline

   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)

   3) A Sceptical View of Artificial Intelligence

   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)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   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)

   6) The Meaning of a Symbolic Description

   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)

   7) The Principle of Artificial Intelligence

   [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)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   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)

    10) There Are Many Types of Reasoning

   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)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   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)

    12) The Synthesis of Man and Machine

   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)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   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)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological 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.

   ♦ Weak Psychological AI

   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.

   ♦ Strong Psychological AI

... 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)

   ♦ Suprapsychological AI

   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)

    17) Form and Content Are Not Fundamentally Different

   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)

    20) Mathematical Logic Provides the Basis for Theory in AI

   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)

    22) Definitions of Artificial Intelligence

   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)

    23) The Computer Can Not Be a Model of the Mind

   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)

    24) Computers Will Not Always Be Inferior to Human Brains

   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
7 Consciousness

   1) Consciousness and the New Mysterians

   Consciousness is what makes the mind-body problem really intractable.

... Without consciousness the mind-body problem would be much less interesting. With consciousness it seems hopeless. (T. Nagel, 1979, pp. 165-166)

   2) Consciousness and Sensory Qualia

   This approach to understanding sensory qualia is both theoretically and empirically motivated... [;] it suggests an effective means of expressing the allegedly inexpressible. The "ineffable" pink of one's current visual sensation may be richly and precisely expressed as a 95Hz/80Hz/80Hz "chord" in the relevant triune cortical system. The "unconveyable" taste sensation produced by the fabled Australian health tonic Vegamite might be poignantly conveyed as a 85/80/90/15 "chord" in one's four channeled gustatory system.... And the "indescribably" olfactory sensation produced by a newly opened rose might be quite accurately described as a 95/35/10/80/60/55 "chord" in some six-dimensional space within one's olfactory bulb. (P. M. Churchland, 1989, p. 106)

   3) Consciousness Appears to Be the Last Bastion of Occult Properties

   One of philosophy's favorite facets of mentality has received scant attention from cognitive psychologists, and that is consciousness itself: fullblown, introspective, inner-world phenomenological consciousness. In fact if one looks in the obvious places... one finds not so much a lack of interest as a deliberate and adroit avoidance of the issue. I think I know why. Consciousness appears to be the last bastion of occult properties, epiphenomena, and immeasurable subjective states-in short, the one area of mind best left to the philosophers, who are welcome to it. Let them make fools of themselves trying to corral the quicksilver of "phenomenology" into a respectable theory. (Dennett, 1978b, p. 149)

   4) Consciousness Can Be Resolved into Its Elementary Sensations

   When I am thinking about anything, my consciousness consists of a number of ideas.... But every idea can be resolved into elements... and these elements are sensations. (Titchener, 1910, p. 33)

   5) Consciousness Is an Aspect of the Darwinian Machine

   A Darwin machine now provides a framework for thinking about thought, indeed one that may be a reasonable first approximation to the actual brain machinery underlying thought. An intracerebral Darwin Machine need not try out one sequence at a time against memory; it may be able to try out dozens, if not hundreds, simultaneously, shape up new generations in milliseconds, and thus initiate insightful actions without overt trial and error. This massively parallel selection among stochastic sequences is more analogous to the ways of darwinian biology than to the "von Neumann" serial computer. Which is why I call it a Darwin Machine instead; it shapes up thoughts in milliseconds rather than millennia, and uses innocuous remembered environments rather than noxious real-life ones. It may well create the uniquely human aspect of our consciousness. (Calvin, 1990, pp. 261-262)

   6) Problems about Consciousness Arise from Use of the Personal Pronoun "I"

   To suppose the mind to exist in two different states, in the same moment, is a manifest absurdity. To the whole series of states of the mind, then, whatever the individual, momentary successive states may be, I give the name of our consciousness.... There are not sensations, thoughts, passions, and also consciousness, any more than there is quadruped or animal, as a separate being to be added to the wolves, tygers, elephants, and other living creatures.... The fallacy of conceiving consciousness to be something different from the feeling, which is said to be its object, has arisen, in a great measure, from the use of the personal pronoun I. (T. Brown, 1970, p. 336)

   7) The Capacity for Consciousness and Self- Consciousness Is Characteristically Human

   The human capacity for speech is certainly unique. But the gulf between it and the behavior of animals no longer seems unbridgeable.... What does this leave us with, then, which is characteristically human?.... t resides in the human capacity for consciousness and self-consciousness. (Rose, 1976, p. 177)

   8) The Origin of the Problems of Consciousness

   [Human consciousness] depends wholly on our seeing the outside world in such categories. And the problems of consciousness arise from putting reconstitution beside internalization, from our also being able to see ourselves as if we were objects in the outside world. That is in the very nature of language; it is impossible to have a symbolic system without it.... The Cartesian dualism between mind and body arises directly from this, and so do all the famous paradoxes, both in mathematics and in linguistics.... (Bronowski, 1978, pp. 38-39)

   9) Views on Consciousness and Computation

   It seems to me that there are at least four different viewpoints-or extremes of viewpoint-that one may reasonably hold on the matter [of computation and conscious thinking]:

   A. All thinking is computation; in particular, feelings of conscious awareness are evoked merely by the carrying out of appropriate computations.

   B. Awareness is a feature of the brain's physical action; and whereas any physical action can be simulated computationally, computational simulation cannot by itself evoke awareness.

   C. Appropriate physical action of the brain evokes awareness, but this physical action cannot even be properly simulated computationally.

   D. Awareness cannot be explained by physical, computational, or any other scientific terms. (Penrose, 1994, p. 12)

Historical dictionary of quotations in cognitive science > Consciousness
8 support for recipients and responsibilities in return

support for recipients and responsibilities in return POL, ECON, SOC Fördern n und Fordern n (sozialpolitischer Grundsatz der Einforderung sozialverantwortlichen = sozialethischen Verhaltens = socially responsible behaviour = socially conscious behaviour von Sozialhilfeempfängern –recipients of social assistance– im Gegenzug zur staatlichen Förderung; anders: return responsibility approach; cf Hartz IV = Hartz IV Law = Viertes Gesetz für moderne Dienstleistungen am Arbeitsmarkt = Fourth Act Promoting Modern Labour Market Services; return responsibility approach; Workfare-Ansatz)

Englisch-Deutsch Fachwörterbuch der Wirtschaft > support for recipients and responsibilities in return
9 blind

1. n штора, маркиза; жалюзи; ставень

lower the blinds — опустите шторы

the slats of a Venetian blind — пластинки жалюзи

awning blind — верхнеподвесной откидной ставень

blackout blind — светоизолирующая штора

blind fastener — крепление для шторы

blind pl — жалюзи; ставни

2. n собир. употр. гл. мн. ч. с во слепые

blind man — слепой

blind gut — слепая кишка

blind lode — слепая жила

blind test — слепой опыт

blind vein — слепая жила

3. n наглазники, шоры

4. n предлог, отговорка; обман

his piety is only a blind — его благочестие просто маска

5. n разг. пьянка

6. n охот. засидка

7. n спец. заглушка

blind plug — заглушка

8. n фото шторка

9. n опт. диафрагма, бленда

дымовая завеса; дымовой экран

10. n воен. неразорвавшийся снаряд

11. a слепой, незрячий

blind obedience — слепое повиновение

ultrasonic aid for blind — ультразвуковые очки для слепых

embossed printing for blind — рельефная печать для слепых

blind and perverse incredulity — слепое и упрямое неверие

double blind study — двойной слепой метод исследования

blind approach landing system — система слепой посадки

12. a предназначенный для слепых

blind asylum — приют для слепых

blind loop — слепая петля

blind shaft — слепой ствол

blind flight — слепой полет

stark blind — совсем слепой

blind apex — слепая верхушка

13. a не видящий, не замечающий, не обращающий внимания

to be blind to the beauties of nature — не воспринимать красот природы

14. a действующий вслепую

blind search — поиск вслепую

blind booking — кино заключение контракта на прокат кинофильма заранее

blind cultivation — обработка вслепую ; шаровка

work blind — работать вслепую

go it blind — действовать вслепую

blind acquisition — захват вслепую

15. a бессмысленный, безрассудный

in his blind haste he was almost run over — он бежал как сумасшедший и чуть не попал под машину

16. a невидимый, скрытный

blind hemming — потайной шов

blind crack — невидимая трещина

blind firing — стрельба по невидимой цели

17. a горн. не имеющий выхода на поверхность

blind drain — подземный дренаж, подземная, закрытая дрена

blind zone — мертвая зона

18. a неясный, неразборчивый, слепо напечатанный

blind letter — письмо без адреса или с неполным адресом

blind impulse — слепой порыв

blind image — слепое изображение

blind jealousy — слепая ревность

blind workings — слепые выработки

totally blind — совершенно слепой

19. a глухой

blind hatch — глухой люк

blind nut — глухая гайка

blind ram — глухая плашка

blind wall — глухая стена

blind corner — глухой угол

20. a оканчивающийся тупиком, не имеющий прохода

blind maze — лабиринт без выхода

blind lead — тупик

blind pass — тупик

blind path — тупик

blind alley — тупик

lead to a blind alley — завести в тупик

21. a стр. фальшивый

blind arch — декоративная арка

22. a матовый

23. a разг. пьяный

blind to the world — вдребезги пьяный

blind drunk — мертвецки пьяный

24. a без цветов и плодов

слепой, по приборам

blind flying — слепой полёт

blind landing — посадка по приборам; слепая посадка

blind cheese — сыр без глазков

color blind — не различающий цветов

blind entries — записи без пояснений

transmit blind — передавать без приема

transmitting blind — передача без приема

25. v ослеплять, лишать зрения

blind robot — слепой робот не имеющий системы технического зрения

26. v слепить глаза, ослеплять

he was blinded by the spotlight — луч прожектора ослепил его

blind in one eye — слепой на один глаз

27. v ослеплять, поражать

28. v затемнять

darkness blinded the sky — тьма окутала небо

29. v затмевать

her beauty blinded all the rest — своей красотой она затмила всех

30. v скрывать, обманывать

to blind the real state of affairs — скрывать истинное положение дел

blind the real state of affairs — скрывать истинное положение дел

31. v фото диафрагмировать

Синонимический ряд:

1. accidental (adj.) accidental; chance; random; unplanned

2. concealed (adj.) concealed; confused; dark; disguised; hidden; obscure; remote; secluded

3. dead end (adj.) blocked; closed; dead end; dead-end; obstructed; shut off

4. dull (adj.) dead; dim; dull; flat; lackluster; lusterless; mat; muted; uncomprehending

5. heedless (adj.) careless; heedless; ignorant; indiscriminate; oblivious; obtuse; thoughtless; unaware; uncritical; unenlightened

6. impetuous (adj.) benighted; hasty; headlong; impetuous; irrational; rash; uncontrolled; undiscerning; unreasonable; violent

7. intoxicated (adj.) alcoholized; cockeyed; drunk; drunken; fried; inebriated; inebrious; intoxicated; looped; muddled; pixilated; polluted; rum-dum; slewed; slopped; sloppy; soshed; sozzled; squiffed; stiff; stoned; tanked; tight; unsober; wet; zonked

8. sightless (adj.) eyeless; purblind; sightless; stone-blind; unseeing; visionless; visually impaired

9. ambush (noun) ambush; hiding place; pitfall; snare; trap

10. cover (noun) blinder; blindfold; cover; curtain; disguise; screen; shade; shield; subterfuge; veil; venetian blind; visor

11. decoy (noun) capper; decoy; shill; shillaber; stick

12. ruse (noun) front; pretence; pretext; ruse; stratagem; trick

13. stand (noun) stand

14. daze (verb) bedazzle; daze; dazzle

Антонимический ряд:

clear-sighted; conscious; cunning; discerning; discriminating; enlightened; keen; open; penetrating; perceptive; quick; rational; seeing; sensitive; sharp-eyed

English-Russian base dictionary > blind

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Словари и энциклопедии на Академике

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conscious approach

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Словари и энциклопедии на Академике

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conscious approach

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