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OI)UCI'IVI]Y IN THE SPACE STATION Raymond S. Nickerson ~)I3tJCIION Cat is productivity? How do we measure it, predict it and control it on earth? To what extent can that knowledge be extrapolated to a space con ~ c? What do we not know about productivity on earth that might be found out--and is worth finding out--through research? How might the expected findings be applied to space? How should the research be directed to ensure its applicability to space? Are there important questions about productivity In space that earth-based research is not likely to held answer? d I wish I could promise to answer these questions here. Unhappily, I cannot. These are the kinds of questions that I have had In mind, however, in preparing this paper. In what follows ~ will focus first on the notion of productivity and on how it has been measured and manipulated in earth environments, and then turn to the question of productivity in space, or more specifically, the Space Station. The paper ends with a set of recommendations for research. WED IS ~OOtJCr~? Productivity is an elusive concept. It seems straightforward enough when one begins to consider it. It is Gary to think about the productivity of chickens or dairy cons in terms of eggs laid or milk produced per unit time; here we are dealing with output in a very literal sense. And it does not tax one's imagination to think about comparing the output of the one producer with that of the other. To do this we need a way to describe eggs and milk quantitatively in the same terms. whichis not difficult. Since eggs and milk are valued as foodstuffs, we could describe them both with respect to their nutritional ingredients. But quantifying productivity only In terms of output is not very useful from an economic point of view, and as it relet== to chickens and cows as producers it would be grossly unfair to the chickens; we must also take into account how much chickens and cows consume IN order to produce a given amount of nutritive capital by means of eggs and milk respectively. And to round out the picture we must factor into the equation not only what the producers -at, but 31

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32 other resources upon which the Or continuing production depends. To do all this we may find it convenient, since not all the factors that must be considered are nutritional, to quantify everything in monetary terms. But this gives us no serious problem. The situation is still fairly simple concepts ally: chickens and coos produce foodstuffs that can be given a monetary value, and to do so they consume resources that have a monetary cost; productivity can be thought of in terms of the value of what is produced and the cost of producing it. This all makes intuitive sense. When one tries to apply the same type of thinking to human productivity, one has no trouble as long as the human activity involved is analogous to laying eggs and giving milk, in the sense of producing tangible goods that can be Bled to satisfy basic human needs, and consuming resources in the process of doing so. The picture gets Aces clear quickly, however, when what is produced is not so tangible--perhaps not even readily identifiable--and not easily quantified in monetary terms. How does one measure the productivity, for example, of the teacher, the scientist, the poet, the philosopher, the salesperson, the physician, the corporate executive, the athlete, the entertain~ror the astronaut? Lack of definitional precision has seldom been a great deterrent to the use of words, and "productivity" is no exception On this regard. It is a popular word in economics, and like "truth" and "keautv.~' ~ ~ ~ ~ __ _ . _= . _ = ~ = _ _ ~= . ~ _. ~ ~ , , ,~l~l~ =~1~1 of mu=1 w == "~ -em, was amp- 1~ menu=. Within the literature pertaining to space exploration, one finds references to Increases in the productivity Of spacecraft crews resulting fans charges ~ displays, control pry or other variables, but seldom is it clear ~c~y ~t this means. the word is also seen ~ughout ache human factors li~ture more generally; although Muckier (1982) has changed that ache unconstrained way in which it is use here mans ; - c mar A; PP;~10 - ~ A;c~ ;~ ~ A;= ~~' =~ ^. &~ - ~' ~ =~ - - ~ ~11 ~1 ~''~ ~11~e ~ petit, pr~uctivi~ is often use more or less as a synonym for performance; if performance improves, by nearly any criterion, productivity is did to go up; if performance degrades, productivity is said to go da an. Sometimes the word is given a precise quantitative mean mg by virtue of the variables that are involved in its measurement. Indices of productivity are typically expressed as a ratio where the numerator is some measure of output (what is produced or the value of same) , and the denom m ator is some measure of input (what is amp up in the production process or the cost of same). What constitutes input and output, and how they are quantified, differs considerably frwu case to case, however; and changes in productivity indices over time can sometimes be difficult to Interpret (Badly, 1986). Moreover, often the word is used as though it were intended to connote a quantitative entity, but there is no clue as to what the input and output variables are or how they could be measured. go concepts that are closely plated to productivity are Chose of Production and efficien - . ~uctivi~r implies production, or more specifically, product arid pricer. Activity is an attribute of a producer; and a producer, by definition, is one who prices sc~thir~. At is product may be tangible (paper clips, a household

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33 appliance, an airplane) or intangible (an educational service, entertainment). A producer may be a person, a person-machine system, a team, a factory, an industry, an economic sector (agriculture), a nation, the world. But although productivity and production are closely related concepts they are not the same. AS we have noted, productivity is usually expressed as a ratio of some measure of output or product value to same measure of input or production cost, and the goal, in most cases, is to make this ratio as high ~= possible. Production usually refers only to output quantity. Given these connotations, it is Busy to imagine production Increasing or decreasing independently of changer in productivity. If, for example, a manufacturer produced 10 percent more items in a given year than in the preceding year, but doing so required a 15 percent increase in the number of employees, we might my that production increased while the productivity of the employees declined. The concept of efficiency, like that of productivity, relates Output to the resource consumed in obtaining it. Efficiency has to do with getting the mast out of given resources; the challenge is to organize a production process so as to munlmize wasted effort. A process is said to be made more efficient when the unit costs of output are decreased or when the consumption of a fixed amount of resources yields a greater output than before. Techniques for measuring the efficiency of assembly line workers were among the earliest contributions of engineering psychology to the manufacturing process and have been used expensively in the work place. These have typically involved analyzing production tusks into observable components. The development of tack-analysis techniques Hal received considerable attention from human factors engineers (Van Cott and Kincaid, 1972; Woodson, 1981~. Such techniques have been more readily applied to psychomotor tasks than to basks that are primarily cognitive in nature or even those that have major cognitive components. Attention has been focused increasingly, however, on the problem of analyzing cognitively-demandin; tasks, as an increasing percentage of the tasks performed by people in the work force are defined more by cognitive than by psychomotor demands. We cannot hope to settle terminologies issues here. More Over, definitions are of limited utility when dealing with terms that are widely used, with a variety of connotations, within a field. For present purposes, prcOuctivity will be taken to be very close, but not quite identical, in meaning to efficiency. An entity (person, group, system) will be considered highly prc*uctive when it uses its resources to = advantage in accomplishing its goals. One can be efficient in the sense of not wasting resources simply by using those resources very sparingly, but that type of efficiency could be counterproductive if resources are husbanded to the point of precluding getting the task done. To be productive one has to use one's resources and use them well. As a working definition of productivity I will use: effective and efficient use of resources in accomplishing a goal. The emphasis is on both effectiveness and efficiency. A prc~uctive system is one that

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34 gets the Intended job done and does so with a munlmum of wasted effort and resources. I do not mean to split hairs here in making a distinction between efficiency and productivity; if one's idea of efficiency incorporates effectiveness, then ~ see no objection to thinking of efficiency and productivity as more or less synonymous. Effort and rescuracs can be wasted as a consequence of many factors, such as poor training, lack of motivation, mismanagement, faulty organization, mlsscheduling, and a host of others. Productivity will be said to increase when either more is accomplished with no increase in consumed resources or the same objectives are attained with a smaller expenditure of resources. These are still somewhat imprecise notions, but not so imprecise as to be useless. In the Space Station context, as elsewhere, when modifications in design or operating prcce~ures have big effects on productivity, there probably will be no difficulty in getting a consensus that productivity has really been improved. When Masks are performed more easily, more reliably, and with fewer costly errors, most interested observers will probably be willing to describe what has happened as an increase in productivity, and even if not, they a ~ likely to agree that changes for the better have occurred. It seems to be generally assumed, if only tacitly, that anything that improves human performance (increases speed, accuracy, reliability) probably Increases numan pro~uct~v~y. This appears to me to be a reasonable assumption, and a very useful one. Frequently in this paper, the discussion focuses on variables that influence performance, the justification being the assumption that what affects performance for better or worse will affect productivity in a comparable way. ASSESSING PRO WCTIVITY It is helpful in the present context to distinguish between the problem of determining what the level of productivity is at any given time and that of determinirg Nether pr~uctivi~ is Wing, or has Carded. One might assume that the second prowlers is more clifficult than the first, inasmuch as a = of ~e, or difference, is derived frmn the more fi~nt=1 measure of absolute value: to determine whether pr ~ uctivi~r is rare or less this weak than it was last, one simply takes the difference between this week's measure an] last week's. But this is so only if one wishes to know the magnitude of the difference. If one is content to know only the direction of the difference, it may not be necessary to know the individual magnibudes, at least if the magnitude of the difference is relatively large. One does not have to know the precise weight of each of two objects to know which one weighs more, especially if the difference is siz-=hie. Productivity as a Percentage of Capacity ~uctivi~ is sometimes quantified In terms of performance relative taxing. Centesis done, maxi~outputorperformanceis~

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35 as the starers against which to evaluate the actual output or performance, whether the performer is an individual, a system (say a factory), or an economy. Thus one might encounter the claim ~t the pr 0uctivit~r of a given industry In a particular region is currently at about 70 percent, which would mean that that industry is operating at 70 percent of what, under certa m assumptions, is the maximum possible. Economists often refer to how close to capacity factories and other manufacturing facilities are operating. The ability to specify hew close to capacity some entity is operating presupposes a metric in terms of which to quantify the operation. Determining what constitutes maximum capacity can sometimes be a complicated and controversial pr Mess. Further, maximum must be understood as maximum within a particular context. The maximum output of a given factory, for example, could mean maximum obtainable with the present tooling, layout, manpower and stock; alternatively it could refer to what would be obtainable if one or more of these constraints on output were relieved. As applied to individual human beings, capacity con not== the best (which often, but not always, equates to most) one can do ~ a given situation, the limit of human performance--or, more accurately, the limit of the individual performer. Conceptually, there are two ways to determine capacity in any given instance: one is to derive it free theoretical considerations; the other is to measure performance under ideal conditions. Neither works very well. While information theory once provided a basis for the hope of defining capacity theoretically, it prayed to be a false Elope, and psychologists have not yet found or developed an alternative that can do the job. Ideal conditions for performing a given ta~k--which Mold have to include an optimally motivated performer--have proved also to be easy to conceptualize but difficult if not impossible to actualize. Differential Productivity Differential productivity in a business context is sometimes measured in terms of changes In the number of employees or amount of employee time required to get a fixed amount of work done, or conversely by changes in the amount of work accomplished by a fixed staff. Thus a retail company is said to have doubled the productivity of its bill collection departments when it managed, by computerizing its operation, to place the same number of reals with a 50% reduction in staff. And the productivity of an insurance company is described as increasing fivefold when the number of policies issued per employee per year increased by a factor of five (Bower, 1986~. Studies of individual human productivity In specific job situations have often focused on the performance of individuals relative to the performance of other individuals on the same task. It is possible to say that A is more productive than B without saying anything very precise about how productive eight individual is relative to a larger frame of reference. Measures of white-collar productivity typically do not yield absolute quantities, but do permit comparisons among similar

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36 organizations (Drucker, 1986). In the Space Station program, attention will probably be focused primarily on differential productivity (the cost of attaining some production objective in space relative to that of obtaining it on Perth; or the cost at one time relative to that at another). While it would be interesting to be able to relate productivity to some theoretical maximum in this context (e.g. by relating production to some measure of capacity), it is not clear how to do that. Fortunately, it is not necessary to be able to quantify maximum productivity in order to determine whether one is moving toward or away from it. That is not to suggest that assessing differential productivity is likely to be an easy task. Several investigators have commented on the variability of measurements of productivity, especially those that relate to individual'' human productivity, and on the resulting need to make many measurements over a considerable period of time if reliable numbers are to be obtained (Muckier, 1982~. It is especially difficult to measure productivity in intellectual tasks, inasmuch as methods for assessing cognitive performance are not well developed. When a person is staring cut of his office window, it may be impossible to tell whether he is idly daydreaming or is engrossed in "productive" thought. And even if he were known to be daydreaming, it would not follow necessarily that that time was lost from a productivity point of view. One widely held view of p,~blem-solving distinguishes an "incubation" period in the problel`-solving process during which progress is made on a problem in spite of--perhaps because of--the fact that the individual is not consciously focusing on the problem to be solved and there are numerous examples of scientists and other thinkers reporting insights that have occurred when they were not actively engaged in working on the problem. Whatever methods are developed for measuring productivity must take guality--as well sac quantity--of output or work into account in some way. In manufacturing operations, product quality affects measures of productivity to the degree that items that fail to meet a preset standard become rejects. The importance of quality control in this sense is obvious and the difficulties that some industries (e.g. the manufacturing of computer microchips) have had are well known. this type of linkage between quality and quantity is a fairly gross one however. Differences ~ quality tend to be ignored so long as the quality is not sufficiently low to necessitate rejection. In nonmanufacturing activities the relationship between quality an] quantity is even more tenuous, in spite of the fact that here one might expect qualitative dif^=erenm~s In output to be both large and important. Quality will certainly be an important consideration in the Space Station context. m e quality of the experiments that are done, for example, will be at least as important as the number.

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37 Workload and Its Assessment In a complex system the operation of which deperxis on functions performed bar both people end machines and, especially, by people and machines in interaction, high productivity will rehire that workloads be at or near c ~ imal level. Significant overload will r educe productivity through increases in the frequency of human error; significant underload will mean wasted rcsawrocs at best and possibly direct negative impact on productivity resulting from boredom, inattentiveness or other diffim~1 ties arising from feelings of being underutilized or unimportant to the operation. Workload and its assessment will be important considerations, therefore, in efforts to understand, measure, or control productivity In space. As in the case of efficiency, the workload carried by an individual is much easier to measure when the task is primarily physical than when it has major cognitive components. As Wierwille et al. (1985) point out, a major consequence of the increasing automation of modern systems is a shift in the role of the human cgerator away face. manned control and toward monitoring and performance evaluation, and this Hal complicated considerably the problem of quantifying the operator's workload. How can we hope to determine how har5--how close to capacity an individual is working when most of what he is doing is ment=1 activity that is not directly observable? The measurement of mental workload has been recognized by human factors researchers as a major challenge to the field and this recognition has stimulated considerable activity (Chiles and Alluissi, 1979; Eggemeier, 1980; X~lsbeek, 1968; R bray, 1979; Parks, 1979; Sheridan and Simpson, 1979; Singleton et al., 1971; Williges and Wierwille, 1979~. Work in the area is still in the exploratory and formative stages, however, and there has not yet emerged a theory or even a widely agreed upon set of concepts and measurement procedures that are needed to provide a sense of stability and coherence. An indication of the magnitude of the problem and of the current status of work on it is provided In the Proceedings of a NATO Conference on Month Workload published In 1979. Johannsen (1979:3) cpened the conference with the observation that "there exist too many conflicting ideas about the definition and measurement of workload", and expressed the hope that the conference would produce a consensus among participants on a definition and on a procedure for workload assessment. In his preface to the conference prcocedings, Moray (1979:VIII), the organizer, acknowledged that these hopes were not realized, but noted that participants from various disciplines did come to "very similar Inclusions about the validity, usefulness, ark promise (or lack of each) for a wide variety of methods for approaching the assessment of workload in the human operator". It is unfortunate that the proceedings does not contain a summary of these conclusions. It does contain, however, a report from each of five participant groups, classified an experimental psychology, control engineering, mathematical modelling, physiological psychology and applications. m e experimental psychologists summarized the fir conclusions this way: " m e concept [mental workload] reflects a genuine dimension or

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38 dimensions of human experience in daily work...it is a concept absolutely required for the adequate analysis and description of such hanks Flasks that are not necessarily physically demanding but that are experienced as exhausting and stressful nonetheless] and for predicting, at the design stage, the future performance of such [automatic and semi-automatic man-machine] systems... On the other hand the concept is at present very ill-def~ned with several probably a; c0; ~~ maim; ~= ~1~- `~ an... There is no satisfactory theory of 'mental workloads' (Johannsen et al., 1979:101). Johannsen et al stress the multidimensional nature of workload, and deny the appropriateness of trying to quantify it as a scalar variable. They specifically rule cut the possibility of meaningfully comparing different tasks with respect to workload, except when the tasks are very similar in structure. The conclusions drawn by the experimental psychologists in the NATO workshop clearly caution against any expectation that the problem of workload measurement will be resolved soon. They are equally clear, however, ~ supporting the view that workload is an essential concept if we are to understand the role of human beings in mcdern systems and design tasks that impose reasonable demands on their capabilities. It could prove to be an especially important concept in the context of the Space Station because of the unusual cognitive demands that that environment will represent. A detailed under standing of those demands insofar as possible in anticipation of the depicyment of the station ~ surely must be a primary objective of the human factors effort In this program. One of the approaches that has been used to identify performance measures that are sensitive to workload has been to take a variety of cancli~te measures in situations in which workload is intentionally varied and SCQ which of then vary with workload manipulation (I i arm Wierwille, 1983; Hicks arx] Wienville, 1979; Wierwi1le arm Connor, 1983; Wier~rille et al., 1985~. =dh of this work has beer done in flight simulators. Candidate n ~ sates that have been studied include opinion scales (subjects' ratings of the task in terms of specified descriptors), physiological measures (heart rate, respiration rate, pupil diameter, eye-blink frequency, eye-fixation fraction), measures of performance on secon ~ tasks (time estimation, tapping regularity), and measures of performance on the primary task. A limitation of this approach is that viable measures, at best, reflect difference= in workload; they do not provide an indication of how herd or how clod to capacity one is working in any particular case. Many of the sues of pilot workload have made use of post flight questionnaires. ~ Ruse this approach is heavily dependent on memory, Rehmann et al. (1983) explored the possibility of having subjects report how hard they are working periodically while performing a tank. Workload judgements did change in this case with controlled changes in task difficulty, but this measurement technique has the disadvantage that it could interfere with the performance of the primary back, especially when the latter is very demanding. The intrusiveness of the measurement process has been a major drawback of many approaches to workload assessment, and especially those that make use of a secondary back (Rolfe, 1971; for a summary of

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39 nearly 150 sties using sorry tasks see Ogden et al., 3979~. One way ~ avoid the use of an intrusive task arx] also dependence on ache subject's merry is to monitor physiological indicants of workload that can be darned automati~A.]ly. Israel et al. (1980) have argued that some of the ~ysiologim=1 measures that have been tried; ~ vanic skin response, heart rate variability, and pupil diameter reflect changes in autonomic nervoll,= system activity and so are sensitive to changes in emotional state independently of their origin. As a physiological measure that is more likely to be indicative unambiguously of Wharves in tile cognitive Innards of a bask, they propose the everlt-related brain potential and, in particular, its Iate positive or p300 eminent. Widens (1979, also has argued for the use of evoked ~ , _ __ ~_~ _~ _ TO ~ ~l _~ fit ^~\ ~ ~ =~_ O~ ~~ ~~_~ pO`ell~lals . Reseal en ad . t 11:1UUJ presently coma [LIEU one e~er~nc supporting the idea that this measure does vary with task demands and that obtaining it need not interfere with the primary task. While it would be imprudent to conclude from these data that electro-physiological monitoring of workload will be effective in the Space Station, the possibility deserves further exploration. Varying workload for experiments purposes is probably not feasible within the Space Station context, or at least the amount of this type Of experimentation that can be done will probably be very limited. It will be essential to attempt to have workloads be as close to ideal as they can be made freon the very beginn mg. Of course when evidence indicates that an initially established workload is not ideal, the workload should be changed ~ the indicated direction, and keeping track of such changes can provide some of the data that would have been obtained from controlled experimentation. The goal must be to minimize the need for such changes, however, which requires being able to predict the effects of different workloads from data obtained In earth environments. DEIERMINPNTS OF PRO WCTIVITY Ah ~ e seems to be a consensus among investigators that productivity is a function of many variables, and that attempts to affect it that focus on one or a small subset of those variables and ignore the others run the risk of doing more harm than good (MucX1er, 1982; Sutermeister, 1976). Among the determinants of productivity that would ~ ve to be included In any extensive list are the following. Human Capabilities and Limitations A great bead of information has been compiled about human Capabilities and limitations and is available in various engineering psychology handbooks. What is known in this regard clearly sets bounds on what ~ . . ~ ~ . ~ . . . ~ ~ numan ne logs Ln general can he expected to co In SpeCl~lC rack situations. Individual differences are also germane to the question of human productivity. People differ widely with respect to both physical and mental capabilities, and the productivity of individuals is bound

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40 to vary with the degree to which then' individual capabilities match the demands of specific Basks. Aptitude testing and job screening and selection procedures are based on these assumptions. Task Demands Evidence supports the intuitively appealing idea that people work best when the demands upon them are neither too great nor too small. This is one form of the "in verted-U hypothesis" regarding the relationship between workload and performance, which holds that performance of a given task is optimal for a workload level that is ~~ermediate between one that is excessively Hugh and one that is so low as to promote ha,... fM~ I h 1~:~ . W^1 If:_ 1 C)7~2 1 C)7A ~ _~. `~-~_~, An_' I_ ~~, '=~. The detrimental effects of overloading are somewhat better documented than are those of underioading (Weiner, 1975; Weiner et al. 1984~. The possibility that underioading can affect performance negatively takes on special significance, however, in the context of systems in which humans function primarily as supervisors of automated processes. Motivation One can hardly doubt that motivation affects performance. It Is cI-a In particular that performance suffers when motivation is very low. What is less clear is how performance is affected when motivation bed untruly high. Merest in = ~ motivation that is relatively law at We outed will at certainly lead ~ i~pr~ed performance, but what has - ns when motivation that is arcade very high is mcreas ~ still further? Is there such a thing as trying too hard? Wanting too badly to succeed? Some investigators believe there is, and that when motivation is extremely high it has a debilitating effect. This is another form of the inverted-U hypothesis mentioned above; except that in this case the performance determinant of interest is motivation rather than task demands. It may be that the detrimental effects associated with Motivation becoming too high are better attributed to anxiety over the possibility of failing; fear, especially den it beds panic, unsubtly can cause performance to deteriorate. Ac cording to thin vicar, if privation becalms arbitrarily high but is not accompanied by such fur, we Ward not nosily expect perforate to fall off. The distir~tion between very high motivation and fear of failure may be an important one in the Space Static context; it scud be helpful ~ have a better understarxlir~ of the rules of these variables as determinants of pr~Ctivi~r and performance. Physiologic State Fatigue has lord been recognized as a factor in ricing proclivity in many settings (Simpson and Weiser, 1976). indeed it he been

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41 defined Operationally as a decrease In performance as a corpulence of pronged activity (~lsb~k, 1971~. Math of the resort on this topic has focus on the problem of schooling rest breaks in such a way as to minimize fatigue (Bechtold et al., 1984; <;anaro and Bechtold, 1985~. The tasks involved in these studio have often been physically strenuous and the results are of limited applicability to tasks that are primarily cognitive in nature. Exceptions include sties of the performance of aircr~rs over extended periods (Carmen, 1971, 1973~. A major question of relevance to productivity in the Space Station is how productivity might be affects by the various physiological effects that can be expected from prolonged living ~ the Space Station environment. Little is yet known about the physiological consequence-= of living in such environments for longer than a few weeks at a time. Training Performance, especially of complex Basks, obviously improves with training and practice. An aspect of the relationship between training and performance that is especially important relative to the Space Station context has to do with the obscuring of differences by ceiling effects. The fact that one has, through practice, gotten to the point of being able to perform a Desk without error is not compelling evidence that one has really mastered the task. The true test may come when that task must be performed under stress or in concert with competing demands on ones resources. To make the point another way, the fact that boo people perform a given bask equally well under acoommo~atlng conditions is not good evidence that they will perform it equally well under stress. Capabilities and T.;m~tations of Machines Just as the capabilities and limitations of the humans in a complex system help determine the productivity of the system as a whole, so do the capabilities and limitations of the machines involved. Unlike the capabilities of human beings, those of the machines that are available for use In the Space Station can be expected to evolve even over the next few derides. Initial plans for the use of technology in the Station take this fact into account. Plans to use artificial Lnt~lligence, for example, explicitly note the unlikelihood that this technology will be used extensively for operational purposes during the initial years of the program. However, provision is being made for its incorporation as the technology matures to the point of being reliably applicable. We would expect that as machine capabilities are extended and improved, a major consequence would be increased productivity of the Space Station as a whole. Nether this proves to be the case and, if so, exactly how rein to be seen.

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71 modifying that model contritely as further relevant data are obtained, esE^:ially from e~rien~ ~ apace. Conditions in space exploration will charge and the durations of says In Apace will Ink ~ se, so the mcdel will have to evolve to acocmrodate those changes. On the assumption that the changes that Drier will be evolutionary and relatively continue us, one can hope for a model that is highly predictive of the situation that is current at any given time and reasonably predictive of the situation as it is anticipated to be in the n-~r-term future. m;~;rIc:F~ AXerstedt, T., and Gillberg, M. 1981 Sleep disturbance and shift work. In A. Reinberg, N. Vieux, and P. Andlauer, eds., Night and Shift Work: Biological and Social Aspects. Oxford: Pergamon Press. Baily, M. N. 1986 What has happened to productivity growth. Science 234:443-451. Bechtold, S. E., Ganaro, R. E., and Sumners, D. L. 1984 Maximization of labor productivity through Optimal rest-break schedules. Management Science 30:1442-1458. Berry, C. A. 1969 Preli ~ clinical report of the medical aspects of Apollos VII and VIIT. Aerospace Medic me 40:245-254. 1970 Summary of medical experience in the Apollo 7 through 11 mart spaceflights. Aerospace Meclicme 41:500-519. Bawen, W. 1986 The pure payoff freon office Muters;. Fortune 5:20-24. advent, D. E. 1971 Decision art Stress. Near York: Academic Press. Backfield, C. A. 1965 Isolation, Clinical and E~riment~1 Approaches. New York: Barton House. Cameron, C. 1971 Fatigue problems in modern ir~ustry. Ergona~nics 14:713-720. 1973 A theory of fatigue. Ergonc~mics 16:633-648. Hi, J. G., and Wierwille, W. W. 1983 A Orison of rating scale, se~rx~ary task, physiological, and primary-task workload estimation ~hniqu~s in a simulated flight task Sizing ~nications load. Oman Factors 25 (6~: 623-641.

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