Activity

Some Possible Fodder for Thought …
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REPRINT OF HISTORICALLY SIGNIFICANT DOCUMENT
Man-Computer Symbiosis

Licklider, J.C.R.

From IRE Transactions on Human Factors in Electronics, March 1960:4-11.
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1. Introduction

A. SYMBIOSIS
The fig tree is pollinated only by the insect Blastaphaga grossorum. The larva of the insect lives in the ovary of the fig tree, and there it gets its food. The tree
and the insect are thus heavily interdependent: the tree cannot reproduce without the insect; the insect cannot eat without the tree; together,
they constitute not only a viable but a productive and thriving partnership. This cooperative “living together in intimate association,
or even close union, of two dissimilar organisms” is called symbiosis.(1)
“Man-computer symbiosis” is a subclass of “man-machine systems.” There are many man-machine systems. At present, however, there are
no man-computer symbioses. The purposes of this paper are to present the concept and, hopefully, to foster the development of man-computer
symbiosis by analyzing some problems of interaction between men and computing machines, calling attention to applicable principles
of man-machine engineering, and pointing out a few questions to which research answers are needed. The hope is that, in not too many years,
human brains and computing machines will be coupled together very tightly, and that the resulting
partnership will think as no human brain has ever thought and process data in a way not
——————————————————————————-
Manuscript received by the PGHFE, January 13, 1960;
revised manuscript received, January 18, 1960. The
background work on which this paper is based was
supported largely by the Behavioral Sciences Dlvlslon, Air
Force Office of Scientific Research, Air Research and
Development Command, through Contract
No. AF-49(638)-355.
Bolt Beranek and Newman Inc., Cambridge, Mass.

(1) “Webster’s New International Dictionary,” 2nd ed., G.
and C. Merriam Co., Springfield, Mass., p. 2555; 1958.
approached by the information-handling machines
we know today.

B. BETWEEN “MECHANICALLY EXTENDED MAN”
AND “ARTIFICIAL INTELLIGENCE”
As a concept, man-computer symbiosis is different in an important way from what North (2) has called “mechanically extended man.” In the
man-machine systems of the past, the human operator supplied the initiative, the direction, the integration, and the criterion. The mechanical
parts of the systems were mere extensions, first
of the human arm, then of the human eye. These systems certainly did not consist of “dissimilar organisms living together . . . ” There
was only one kind of organism-man-and the rest was there only to help him.
In one sense of course, any man-made system is intended to help man, to help a man or men outside the system. If we focus upon the human
operator(s) within the system, however, we see that, in some areas of technology, a fantastIc change has taken place during the last few
years. “Mechanical extension” has given way to replacement of men, to automation, and the
men who remain are there more to help than to be helped. In some instances, particularly in
large computer-centered information and control systems, the human operators are responsible
mainly for functions that it proved infeasible to automate. Such systems (“humanly extended
machines,” North might call them) are not symbiotic systems. They are “semi-automatic” systems,
systems that started out to be fully automatic but fell short of the goal.
Man-computer symbiosis is probably not the
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(2) J. D. North, “The rational behavior of mechanically
extended man,” Boulton Paul Aircraft Ltd.,
Wolverhampton, Eng.; September, 1954.
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ultimate paradigm for complex technological systems. It seems entirely possible that, in due course, electronic or chemical “machines” will
outdo the human brain in most of the functions we now consider exclusively within its province. Even now, Gelernter’s IBM-704 program for
proving theorems in plane geometry proceeds at about the same pace as Brooklyn high school students, and makes similar errors.(3) There are, in
fact, several theorem-proving, problem-solving, chess-playing, and pattern-recognizing programs (too many for complete reference – 15)

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(3) H. Gelernter, “Realization of a Geometry Theorem
Proving Machine,” Unesco, NS, ICIP, i.6.6, International
Conference on Information Processing, Paris, France; June, 1959.
(4) A. Newell andJ. C. Shaw, “Programming the logic
theory machine,” Pro(. WJCC, pp. 230-240; March,1957.
(5) C. Gilmore, “A Program for the Proquction of Proofs
for Theorem.s Derivable. Within the First .Grqer Predicate
Calculus fr:qm, Axioms,” Unesco, NS,” ICI.p, ‘1,6.14,
International. Conference on Information Processing, Paris,’ France;
June, 1959.
(6) B. G. ‘p~lfleyand W. A. Clark, “Simulation of self-organizing systems by digital computers,” IRE TRANS, ON
INFORMATION THEORY; vol. IT-4i pp. 76~84; September; 1954.
(7) R. M. Friedberg, “A learning machine: Part l,”lBM Journal of Res. & Dev., vol. 2, pp. 2-13;January, 19
(8) 0, G. Selfridge, “Pandemonium, a paradigm.for
le,arning,” Proc Symp. Mechanisationof Thought Processes,
Nat!. Physical Lab., Teddington, ~ng.; November, 1958.
(9) W., W. Bledsoe and L Browning, “Pattern Recognition
and Reading by Machine,” presented at the East~rn Joint
Computer Conf., Boston, Mass., December, 1959.
(10) C.E. Shannon, “Programming a computer for playing
chess,” Phil. Mag., vol. 41, pp.256-75; March, 1950.
(11) A.Newell, “The chess machine: an example of dealing
with a complex task by adaptation,” Proc. WJCC, pp. 101-
108; March, 1955.
(12) A. Bernstein and M. deV. Roberts, “Computer versus
chess-player,” Scientific American, vol. 198, pp. 96-98; June,
1958.
(13) A. Newell, J. C. Shaw, and H. A. Simon, “Chess-playing
programs and the problem of complexity,” IBM J. Res. &
Dev., vol. 2, pp. 320-335; October, 1958.
(14) H. Sherman, “A Quasi-Topological Method for
Recognition of Line Patterns,” Unesco, NS, ICIP, H.L.5,
Internatl. Conf. on Information Processing, Paris, France;
June, 1959.
(15) G. P. Dinneen, “Programming pattern recognition,” Proceedings of the Western JCC, pp. 94-100; March, 1955
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capable of rivaling human intellectual performance in restricted areas; and Newell, Simon, and Shaw’s( 16 ) “general problem solver-“may remove
some of the restrictions., In short, it seems worth while to avoid argument with (other) enthusiasts for artificial intelligence by conceding
dominance in the distant future of cerebration to machines alone. There will nevertheless be a fairly long interim during which the main intellectual
advances will be made by men and computers working together in intimate association.
A multidisciplinary study group, examining future research and development problems of the Air Force estimated that it would, by 1980 hefore
developments in artificial intelligence make it possible for machines alone to do much thinking or problem solving of military significance. That
would leave~ say, five years to develop man-computer symbiosis and 15 years to use it.. The 15 may be 10 or 500, but those years should be intellectually
the most creative and exciting in the history of mankind.

II. Aims of Man~Computer Symbiosis
Present-day computers are designed primarily to solve preformulated problems or, to process data according to predetermined procedures. The
course of the computation may be conditional upon results obtained during the computation, but all the alternatives must be foreseen in advance.
(If an unforeseen alternative arises, the whole process· comes to a halt and awaits the necessary extension of the program.) The requirement
for preformulation or predetermination is sometimes no great disadvantage. It is often said that programming for a computing
machine forces one to think clearly, that it disciplines the thought process. If the user can think his problem through in advance, symbiotic association
with a computing machine is not necessary. However, many problems that can be thought through in advance are very difficult to
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(16) A. Newell, H. A. Simon, and J. C. Shaw, “Report on a
general problem-solving program,” Unesco, NS, ICIP,
1.6.8, Internatl. Conf. on Information Processing, Paris,
France; June, 1959.
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think through in advance. They would be easier to solve, and they could be solved faster, through an intuitively guided trial-and-error procedure
in which the computer cooperated, turning up flaws in the reasoning or revealing
unexpected turns in the solution. Other problems simply cannot be formulated without computing-
machine aid. Poincare anticipated the frustration of an important group of would-be
computer users when he said, “The question is not, ‘What is the answer?’ The question is, ‘What
is the question?’ ” One of the main aims of man-computer symbiosis is to bring the computing
machine effectively into the formulative parts of technical problems.
The other main aim is closely related. It is to bring computing machines effectively into processes of thinking that must go on in “real time,”
time that moves too fast to permit using computers in conventional ways. Imagine trying, for
example, to direct a battle with the aid of a computer on such a schedule as this. You formulate your problem today. Tomorrow you spend with
a programmer. Next week the computer devotes 5 minutes to assembling your program and 47
seconds to calculating the answer to your problem. You get a sheet of paper 20 feet long, full
of numbers that, instead of providing a final solution, only suggest a tactic that should be explored by simulation. Obviously, the battle
would be over before the second step in its planning was begun. To think in interaction with a computer in the same way that you think with a
colleague whose competence supplements your own will require much tighter coupling between
man and machine than is suggested by the example and than is possible today.

III. Need for Computer Participation in
Formulative and Real-Time Thinking
The preceding paragraphs tacitly made the assumption that, if they could be introduced effectively
into the thought process, the functions that can be performed by data-processing machines
would improve or facilitate thinking and problem solving in an important way. That assumption
may require justification.

A. A PRELIMINARY AND INFORMAL TIME-AND MOTION
ANALYSIS OF TECHNICAL THINKING
Despite the fact that there is a voluminous literature on thinking and problem solving, including
intensive case-history studies of the process of invention. I could find nothing comparable to a
time-and-motion-study analysis of the mental work of a person engaged in a scientific or technical
enterprise. In the spring and summer of 1957, therefore, I tried to keep track of what one
moderately technical person actually did during the hours he regarded as devoted to work. Although
I was aware of the inadequacy of the sampling, I served as my own subject.
It soon became apparent that the main thing
I did was to keep records, and the project would have become an infinite regress if the keeping of
records had been carried through in the detail envisaged in the initial plan. It was not. Nevertheless,
I obtained a picture of my activities that gave me pause. Perhaps my spectrum is not typical-
I hope it is not, but I fear it is. About 85 per cent of my” thinking” time
was spent getting into a position to think, to make a decision, to learn something I needed to
know. Much more time went into finding or obtaining information than into digesting it. Hours
went into the plotting of graphs, and other hours into instructing an assistant how to plot.
When the graphs were finished, the relations were obvious at once, but the plotting had to be
done in order to make them so. At one point, it was necessary to compare six experimental determinations
of a function relating speech-intelligibility to speech-to-noise ratio. No two
experimenters had used the same definition or
measure of speech-to-noise ratio. Several hours
of calculating were required to get the data into
comparable form. When they were in com~arable
form, it took only a few seconds to determme
what I needed to know. Throughout the period I examined, in short,
my” thinking” time was devoted mainly to activities that were essentially clerical or mechanical:
searching, calculating, plotting, transforming, determining the logical or dynamic
consequences of a set of assumptions or hypotheses, preparing the way for a decision or an
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insight. Moreover, my choices of what to attempt
and what not to attempt were determined to an
embarrassingly great extent by considerations of
clerical feasibility, not intellectual capability.
The main suggestion conveyed by the findings
just described is that the operations that fill
most of the time allegedly devoted to technical
thinking are operations that can be performed
more effectively by machines than by men. Severe problems are posed by the fact that these
operations have to be performed upon diverse variables and in unforeseen and continually
changing sequences. If those problems can be solved in such a way as to create a symbiotic relation
between a man and a fast information retrieval and data-processing machine, however,
it seems evident that the cooperative interaction would greatly improve the thinking process.

B. COMPARATIVE CAPABILITIES
OF MEN AND COMPUTERS
It may be appropriate to acknowledge, at this
point, that we are using the term “computer”
to cover a wide class of calculating, data-processing,
and information-storage-and-retrieval machines.
The capabilities of machines in this class
are increasing almost daily. It is therefore hazardous
to make general statements about capabilities
of the class. Perhaps it is equally hazardous
to make general statements about the capabilities of men. Nevertheless, certain genotypic differences
in capability between men and computers do stand out, and they have a bearing on the
nature of possible man-computer symbiosis and the potential value of achieving it.
As had been said in various ways, men are noisy, narrow-band devices, but their nervous
systems have very many parallel and simultaneously active channels. Relative to men, computing
machines are very fast and very accurate, but they are constrained to perform only one or a
few elementary operations at a time. Men are flexible, capable of “programming themselves contingently” on the basis of newly received information. Computing machines are singleminded,
constrained by their II preprogramming.” Men naturally speak redundant languages organized around unitary objects and coherent actions and
employing 20 to 60 elementary symbols. Computers “naturally” speak non-redundant languages, usually with only two elementary symbols and
no inherent appreciation either of unitary objects or of coherent actions.
To be rigorously correct, those characterizations would have to include many qualifiers.
Nevertheless, the picture of dissimilarity (and therefore potential supplementation) that they
present is essentially valid. Computing machines can do readily, well, and rapidly many things
that are difficult or impossible for man, and men can do readily and well, though not rapidly,
many things that are difficult or impossible for computers. That suggests that a symbiotic cooperation,
if successful in integrating the positive characteristics of men and computers, would be
of great value. The differences in speed and in language, of course, pose difficulties that must be overcome.

IV. Separable Functions of Men
and Computers in the Anticipated
Symbiotic Association

It seems likely that the contributions of human
operators and equipment will blend together so
completely in many operations that it will be difficult
to separate them neatly in analysis. That
would be the case if, in gathering data on which
to base a decision, for example, both the man
and the computer came up with relevant precedents
from experience and if the computer then
suggested a course of action that agreed with the
man’s intuitive judgment. (In theorem-proving
programs, computers find precedents in experience,
and in the SAGE System, they suggest
courses of action. The foregoing is not a farfetched
example.) In other operations, however,
the contributions of men and equipment will be
to some extent separable. Men will set the goals and supply the motivations,
of course, at least in the early years. They will formulate hypotheses. They will ask
questions.
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They will think of mechanisms, procedures, and models. They will remember that
such-and-such a person did some possibly relevant work on a topic of interest back in 1947, or
at any rate shortly after World War II, and they will have an idea in what journals it might have
been published. In general, they will make approximate and fallible, but leading, contributions,
and they will define criteria and serve as evaluators, judging the contributions of the
equipment and guiding the general line of thought.
In addition, men will handle the very-Iowprobability
situations when such situations do
actually arise. (In current man-machine systems,
that is one of the human operator’s most important
functions. The sum of the probabilities of very-low-probability alternatives is often much too large to neglect.) Men will fill in the gaps,
either in the problem solution or in the computer program, when the computer has no mode or routine that is applicable in a particular circumstance.
The information-processing equipment, for its part, will convert hypotheses into testable models and than test the models against data (which the human operator may designate
roughly and identify as relevant when the computer
presents them for his approval). The equipment will answer questions. It will simulate the mechanisms and models, carry out the procedures,
and display the results to the operator. It will transform data, plot graphs (“cutting the
cake” in whatever way the human operator specifies,
or in several alternative ways if the human
operator is not sure what he wants). The
equipment will interpolate, extrapolate, and
transform. It will convert static equations or logical
statements into dynamic models so the human
operator can examine their behavior. In
general, it will carry out the routinizable, clerical
operations that fill the intervals between decisions.
In addition, the computer will serve as a
statistical-inference, decision-theory, or gametheory
machine to make elementary evaluations
of suggested courses of action whenever there is
enough basis to support a formal statistical analysis.
Finally, it will do as much diagnosis, pattern matching, and relevance recognizing as it profitably
can, but it will accept a clearly secondary status in those areas.

V. Prerequisites for Realization
of Man-Computer Symbiosis

The data-processing equipment tacitly postulated in the preceding section is not available. The
computer programs have not been written. There are in fact several hurdles that stand between
the nonsymbiotic present and the anticipated symbiotic future. Let us examine some of them
to see more clearly what is needed and what the chances are of achieving it.

A. SPEED MISMATCH BETWEEN MEN
AND COMPUTERS

Any present-day large-scale computer is too fast and too costly for real-time cooperative thinking with one man. Clearly, for the sake of efficiency
and economy, the computer must divide its time among many users. Time-sharing systems are
currently under active development. There are even arrangements to keep users from II clobbering”
anything but their own personal programs. It seems reasonable to envision, for a time
10 or 15 years hence, a “thinking center” that will incorporate the functions of present-day libraries
together with anticipated advances in information storage and retrieval and the symbiotic
functions suggested earlier in this paper. The picture readily enlarges itself into a network of
such centers, connected to one another by wide band communication lines and to individual users
by leased-wire services. In such a system, the speed of the computers would be balanced,
and the cost of the gigantic memories and the sophisticated programs would be divided by the number of users.

B. MEMORY HARDWARE REQUIREMENTS
When we start to think of storing any appreciable fraction of a technical literature in computer memory, we run into billions of bits and, unless
things change markedly, billions of dollars.
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The first thing to face is that we shall not store all the technical and scientific papers in computer memory. We may store the parts that
can be summarized most succinctly-the quantitative parts qJ;l.d. the. reference citations-but not
the whole. Books are among the.’ most beautifully
engineered, and human-engineered, components in existence, and they will continue to
be functionally important within the context of man-computer· symbiosis. (Hopefully, the computer will expedite the finding, delivering, and returning of books.)
The second point is that a very important section of memory will be permanent: part indelible
memory and part published memory. The computer
will be able to write once into indelible memory, and then read back indefinitely, but the
computer will not be able to erase indelible memory. (It may also over-write, turning all the
Os into 1s, as though marking over what was written earlier.) Published memory will be “read only”
memory. It will be introduced into the
computer already structured. The computer will be able to refer to it repeatedly, but not to change it. These types of memory will become more and more important as computers grow
larger. They can be made more compact than core, thin-film, or even tape memory and they
will be much less expensive. The main engineering problems will concern selection circuitry. In so far as other aspects of memory requirement are concerned, we may count upon the
continuing development of ordinary scientific and business computing machines. There is some prospect that memory elements will become as fast as processing (logic) elements. That
development would have a revolutionary effect upon the design of computers.

C. MEMORY ORGANIZATION REQUIREMENTS
Implicit in the idea of man-computer symbiosis are the requirements that information be retrievable both by name and by pattern and that it be
accessible through procedure much faster than serial search. At least half of the problem of memory organization appears to reside in the storage
procedure. Most of the remainder seems to be wrapped up in the problem of pattern recognition within the storage mechanism or medium.
Detailed discussion of these problems is beyond
the present scope~ However, a brief outline of
one promising idea, “trie memory;” may serve
to indicate the general nature’ of anticipated developments.
Triememory is so called by its originator,
Fredkin (17) because· it is designed to facilitate retrieval of information and because the branching
storage structure, when developed, resembles a tree. Most common memory systems store functions
of arguments at locations designated by the arguments. (In one sense,’ they do not store
the arguments at all. In another and more realistic
sense, they store all the possible arguments in
the framework structure of the memory . ) The
trie memory system on the other hand, stores both the functions and the arguments. The
argument is introduced into the memory first, one character at a time; starting at a standard initial
register. Each argument register has One cell for
each character of the ensemble (e.g., two for information encoded in binary form) and each character
cell has within it storage space for the
address of the next register. The argument is stored by writing a series of addresses, each one
of which tells where, to find the next. At the end of the argument is a special “end-of-argument”
marker. Then ·follow directions to the function, which is “stored” in one or another of several
ways/either further trie structure or “list structure” often being most effective.
The trie memory scheme is inefficient for
small memories, but it becomes increasingly efficient
in using available storage space as memory
size increases. The attractive features of the
scheme are these: 1) The retrieval process is extremely
Simple. Given the argument, enter the
standard initial register with the first character,
and pick up the address of the second. Then go
to the second register, and pick up the address of
the third, etc. 2) If two arguments have initial characters in common, they use the same storage space for those characters. 3) The lengths of the
arguments need not be the same, and need not be specified in advance. 4) No room in storage is reserved for or used by any argument until it

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(17) E. Fredkin, “Trie memory,” in preparation.
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is actually stored. The trie structure is created as
the items are introduced into the memory. (5) A
function can be used as an argument for another
function, and that function as an argument for
the next. Thus, for example, by entering with the argument, “matrix multiplication,” one
might retrieve the entire program for performing a matrix multiplication on the computer. 6) By
examining the storage at a given level, one can
determine what thus far similar items have been
stored. For example, if there is no citation for
Egan, J. P., it is but a step or two backward to
pick up the trail of Egan, James. . . .
The properties just described do not include all the desired ones, but they bring computer storage into resonance with human operators
and their predilection to designate things by naming or pointing.

D. THE LANGUAGE PROBLEM
The basic dissimilarity between human languages and computer languages may be the
most serious obstacle to true symbiosis. It is reassuring, however, to note what great strides have
already been made, through interpretive programs and particularly through assembly or
compiling programs such as FORTRAN, to adapt computers to human language forms. The “Information
Processing Language” of Shaw, Newell, Simon, and Ellis (18) represents another line of rapprochement. And, in ALGOL and related
systems; men are proving their flexibility by adopting standard formulas of representation
and expression that are readily translatable into machine language.
For the purposes of real-time cooperation
between men and computers, it will be necessary,
however, to make use of an additional and
rather different principle of communication and
control. The idea may be highlighted by comparing
instructions ordinarily addressed to intelligent
human beings with instructions ordinarily
used with computers. The latter specify precisely
the individual steps to take and the
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(18) J. C Shaw, A. Newell, H. A. Simon, and T. O. Ellis, “A
command structure for complex information processing,”
Proc. WICC, pp. 119-128; May, 1958.

sequence in which to take them. The former present or imply something about incentive or
motivation, and they supply a criterion by which the human executor of the instructions will
know when he has accomplished his task. In short: instructions directed to computers specify
courses; instructions directed to human beings specify goals.
Men appear to think more naturally and easily in terms of goals than in terms of courses.
True, they usually know something about directions in which to travel or lines along which to
work, but few start out with precisely formulated
itineraries. Who, for example, would depart
from Boston for Los Angeles with a detailed specification
of the route? Instead, to paraphrase Wiener, men bound for Los Angeles try continually
to decrease the amount by which they are not yet in the smog.
Computer instruction through specification
of goals is being approached along two paths. The
first involves problem-solving, hill-climbing, sel£organizing
programs. The second involves realtime
concatenation of preprogrammed segments
and closed subroutines which the human operator
can designate and call into action simply by
name.
Along the first of these paths, there has been promising exploratory work. It is clear that,
working within the loose constraints of predetermined strategies, computers will in due course
be able to devise and simplify their own procedures for achieving stated goals. Thus far, the
achievements have not been substantively important; they have constituted only “demonstration
in principle.” Nevertheless, the implications are far reaching.

Although the second path is simpler and apparently capable of earlier realization, it has
been relatively neglected. Fredkin’s trie memory provides a promising paradigm. We may in due
course see a serious effort to develop computer programs that can be connected together like the
words and phrases of speech to do whatever computation or control is required at the moment.
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The consideration that holds back such an effort, apparently, is that the effort would produce
nothing that would be of great value in the context of existing computers. It would be unrewarding to develop the language before there are
any computing machines capable of responding meaningfully to it.

E. INPUT AND OUTPUT EQUIPMENT
The department of data processing that seems least advanced, in so far as the requirements of
man-computer symbiosis are concerned, is the one that deals with input and output equipment
or, as it is seen from the human operator’s point of view, displays and controls. Immediately after
saying that, it is essential to make qualifying comments because the engineering of equipment
for high-speed introduction and extraction of information has been excellent, and because some
very sophisticated display and control techniques have been developed in such research laboratories
as the Lincoln Laboratory. By and large, in generally available computers, however, there is
almost no provision for any more effective, immediateman-machine communication than can
be achieved with an electric typewriter. Displays seem to be in a somewhat better
state than controls. Many computers plot graphs on oscilloscope screens, and a few take advantage
of the remarkable capabilities, graphical and symbolic, of the charactron display tube. Nowhere, to my knowledge, however, is there anything
approaching the flexibility and convenience of the pencil and doodle pad or the chalk and blackboard used by men in technical discussion.

1) Desk-Surface Display and Control:
Certainly, for effective man-computer interaction, it will be necessary for the man and the computer to draw
graphs and pictures and to write notes and equations to each other on the same display surface.
The man should be able to present a function to the computer, in a rough but rapid
fashion, by drawing a graph. The computer should read the man’s writing, perhaps on the
condition that it be in clear block capitals, and it should iminediately post, at the location of each
hand-drawn symbol, the corresponding character as interpreted and put into precise typeface.
With such an input-output device, the operator would quickly learn to write or print in a manner
legible. to the machine. He could compose instructions and subroutines, set them into proper
format, and check them over before introducing them finally into the computer’s main memory.
He could even define new symbols, as Gilmore
and Savell (19) have done at the Lincoln Laboratory,
and present them directly to the computer. He
could sketch out the format of a table roughly and
let the computer shape it up with precision. He
could correct the computer’s data, instruct the
machine via flow diagrams, and in general interact
with it very much as he would with another
engineer, except that the “other engineer”
would be a precise draftsman, a lightning calculator,
a mnemonic wizard, and many other valuable
partners all in one.
2) Computer-Posted Wall Display: In some
technological systems, several men share responsibility
for controlling vehicles whose behaviors
interact. Some information must be
presented simultaneously to all the men, preferably
on a common grid, to coordinate their actions.
Other information is of relevance only to
one or two operators. There would be only a
confusion of un interpretable clutter if all the information
were presented on one display to all
of them. The information must be posted by a
computer, since manual plotting is too slow to
keep it up to date.
The problem just outlined is even now a critical one, and it seems certain to become more and more critical as time goes by. Several designers
are convinced that displays with the desired characteristics can be constructed with the aid of flashing lights and time-sharing viewing
screens based on the light-valve principle. The large display should be supplemented,
according to most of those who have thought
about the problem, by individual display-control
units. The latter would permit the operators to
modify the wall display without leaving their locations.
For some purposes, it would be desirable
for the operators to be able to communicate
with the computer through the supplementary
displays and perhaps even 1hrough the wall display.
At least one scheme for providing such
communication seems feasible.
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(19) J. T. Gilmore and R. E. Savell, “The Lincoln Writer,”
Lincoln Laboratory, M.I.T., Lexington, Mass., Rept. 51-8;
October, 1959.
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The large wall display and its associated system
are relevant, of course, to symbiotic cooperation
between a computer and a team of men.
Laboratory experiments have indicated repeatedly
that informal, parallel arrangements of operators,
coordinating their activities through
reference to a large situation display, have important
advantages over the arrangement, more
widely used, that locates the operators at individual
consoles and attempts to correlate their actions
through the agency of a computer. This is
one of several operator-team problems in need
of careful study.
3) Automatic Speech Production and Recognition:
How desirable and how feasible is speech communication between human operators and
computing machines? That compound question is asked whenever sophisticated data-processing
systems are discussed. Engineers who work and live with computers take a conservative attitude
toward the desirability. Engineers who have had experience in the field of automatic speech recognition
take a conservative attitude toward the feasibility. Yet there is continuing interest in the
idea of talking with computing machines. In large part, the interest stems from realization that
one can hardly take a military commander or a
corporation president away from his work to teach him to type. If computing machines are
ever to be used directly by top-level decision makers, it may be worthwhile to provide communication
via the most natural means, even at considerable cost.
Preliminary analysis of his problems and time scales suggests that a corporation president would be interested in a symbiotic association
with a computer only as an avocation. Business situations usually move slowly enough that there is time for briefings and conferences. It seems
reasonable, therefore, for computer specialists to be the ones who interact directly with computers in business offices.
The military commander, on the other hand,
faces a greater probability of having to make critical
decisions in short intervals of time. It is easy
to overdramatize the notion of the ten-minute
war, but it would be dangerous to count on having
more than ten minutes in which to make a
critical decision. As military system ground
environments and control centers grow in capability
and complexity, therefore, a real requirement for
automatic speech production and recognition in
computers seems likely to develop. Certainly, if
the equipment were already developed, reliable,
and available, it would be used.
In so far as feasibility is concerned, speech
production poses less severe problems of a technical
nature than does automatic recognition of
speech sounds. A commercial electronic digital
voltmeter now reads aloud its indications, digit
by digit. For eight or ten years, at the Bell Telephone
Laboratories, the Royal Institute of Technology
(Stockholm), the Signals Research and
Development Establishment (Christchurch), the Haskins Laboratory, and the Massachusetts Institute of Technology, Dunn (20), Fant (21), Lawrence (22),
Cooper (23), Stevens (24), and their coworkers, have demonstrated successive generations of intelligible
automatic talkers. Recent work at the Haskins Laboratory has led to the development
of a digital code, suitable for use by computing machines, that makes an automatic voice utter intelligible
connected discourse. (25)

The feasibility of automatic speech recognition depends heavily upon the size of the vocabulary
of words to be recognized and upon the diversity of talkers and accents with which it
must work. Ninety-eight per cent correct recognition of naturally spoken decimal digits was
——————————————————————————–
(20) H. K. Dunn, “The calculation of vowel resonances, and
an electrical vocal tract,” J. Acoust. Soc. Amer., vol. 22, pp.
740-753; November, 1950.

(21) G. Fant, “On the Acoustics of Speech,” paper presented
at the Third Internatl. Congress on Acoustics, Stuttgart,
Ger.; September, 1959.

(22) W. Lawrence, et al., “Methods and Purposes of Speech
Synthesis,” Signals Res. and Dev. Estab., Ministry of
Supply, Christchurch, Hants, England, Rept. 56/1457;
March, 1956.

(23) F. S. Cooper, et al., “Some experiments on the
perception of synthetic speech sounds,” Journal Acoust. Soc.
Amer., vol. 24, pp. 597-606; November, 1952.

(24) K. N. Stevens, S. Kasowski, and C. G. Fant, “Electric
analog of the vot:al tract,” Journal Acoust. Soc. Amer., vol. 25,
pp. 734-742; July, 1953.

(25) A. M. Liberman, F. Ingemann, L. Lisker, P. Delattre, and
F. S. Cooper, “Minimal rules for synthesizing speech,” Journal
Acoust. Soc. Amer., vol. 31, pp. 1490-1499; November,
1959.
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PAGE 140

demonstrated several years ago at the Bell Telephone Laboratories and at the Lincoln Laboratory. 26, 27
To go a step up the scale of vocabulary size, we may say that an automatic recognizer of clearly
spoken alpha-numerical characters can almost surely be developed now on the basis of existing
knowledge. Since untrained operators can read at least as rapidly as trained ones can type, such
a device would be a convenient tool in almost any computer installation.

For real-time interaction on a truly symbiotic level, however, a vocabulary of about 2000
words, e.g., 1000 words of something like basic English and 1000 technical terms, would probably
be required. That constitutes a challenging problem. In the consensus of acousticians and
linguists, construction of a recognizer of 2000 words cannot be accomplished now. However,
there are several organizations that would happily undertake to develop an automatic recognizer
for such a vocabulary on a five-year basis.
—————————————————————————————————
(26) K. H. Davis, R. Biddulph, and S. Balashek, “Automatic
recognition of spoken digits,” in W. Jackson,
“Communication Theory,” Butterworths Scientific
Publications, London, Eng., pp. 433-441; 1953.
(27) J. W. Forgie and C. D. Forgie, “Results obtained from a
vowel recognition computer program,” J. Acoust. Soc.
Amer., vol. 31, pp. 1480-1489; November, 1959.
They would stipulate that the speech be clear
speech, dictation style, without unusual accent.
Although detailed discussion of techniques
of automatic speech recognition is beyond the
present scope, it is fitting to note that computing
machines are playing a dominant role in the de.;.
velopment of automatic speech recognizers. They
have contributed the impetus that accounts for
the present optimism, or rather for the optimism
presently found in some quarters. Two or three
years ago, it appeared that automatic recognition
of sizeable vocabularies would not be achieved
for ten or fifteen years; that it would have to
await much further, gradual accumulation of
knowledge of acoustic, phonetic, linguistic, and
psychological processes in speech communication.
Now, however, many see a prospect of accelerating
the acquisition of that knowledge
with the aid of computer processing of speech
signals, and not a few workers have the feeling
that sophisticated computer programs will be
able to perform well as speech-pattern recognizers
even without the aid of much substantive
knowledge of speech signals and processes. Putting
those two considerations together brings the
estimate of the time required to achieve practically
significant speech recognition down to perhaps
five years, the five years just mentioned.