perrolle 1986 - intellectual assembly lines

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Computers and the Social Sciences 2 1986Paradigm Press, Inc.

Intellectual Assembly Lines: The Rationalizationof Managerial, Professional, and Technical Work

Judith A. Perrolle

Abstract This paper examines recent trends incomputer technology in the context of the theo-retical argument that intellectual labor is beingsubjected to the same processes of rationalizationand control that affected manual labor during theindustrial revolution. It is argued that expert sys-tems and other products of knowledge engineer-ing are being developed as mechanisms to ration-alize and mechanize the mental labor of individu-als in technical, professional, and managerial oc-cupations. Because there are at present very fewapplications of intelligent software, empiricalevidence of their effects is meager. However, de-bates about the impact of computerization on thelabor process must take into account the theoret-ical potential for automating expert knowledge,professional judgment and managerialdecision-making.

Developments in the computer eld becomingknown as knowledge engineering offer the tech-nical means to create intellectual assembly linesfor managerial, professional, and technical occu-pations. An intellectual assembly line is a divisionof labor in which the rationality ofthe bureaucrat-ic organization acquires the mechanized efcien-cy of the factory, and in which mental labor is sub-jected to both the rationalization ofits knowledgeand the gradual automation of its productive ac-tivity. Technical, professional, and managerialwork all involve the exercise of expert knowledge.Also involved in professional and managerial jobsare autonomous professional judgments based

upon experience. Managerial activityin addition

judith A. Perrolle teaches at NortheasternUniversity.

includes the evaluation and control of the workof others. To argue these mental activities can beorganized in assembly line fashion presumes thatcomputers can perform as technical experts, canacquire a kind of judgment based upon generalprinciples and experience, and can make mana-gerial decisions. These are precisely the claimsof the research area known as articial intelli-

gence, which is part of the emerging eld ofknowledge engineering.

Knowledge engineering includes efforts to or-ganize intellectual activity into a set of computer-coordinated tasks by means of data managementand decision-support systems Hayes-Roth, 1984 .It also involves attempts to mechanize actualdecision-making and knowledge production ac-tivities using expert systems and other types ofarticial intelligence software Coombs, 1984;Winston and Prendergast, 1984 .

While theoretical debates about the prospectsfor automating thought processes are foundin avariety of disciplines, social theories of the effectsof computing for a review, see Kling, 1980generally neglect the issue of articial intelli-gence. Although there are enormous discrepan-cies between optimistic claims thatknowledgeengineering can embody intellectual activity incomputer systems and the actual performance ofintelligent software, there are enough successesto demonstrate that machines can perform whatwere previously human mental activities Pylyshyn, 1980 . Although there are fewer than200 commercial expert systems in operation

Frenkel,1985 , the rapid spread of robotics in in-

dustry and the growing business and military sup- 1

port for the fth generation technology are in-8

dicators that, despite theoretical reservations of


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philosophers and cognitive scientists articial in-telligence is becoming a social fact.

The Deskilling DebateDebates about the effects of computerization onthe labor process involve differing assumptionsabout both the nature of intellectual work andmanagement strategies. Theorists who see ageneral trend toward the subordination of intellec-tual work predict deskilling Cooley, 1980 , whitecollar proletarianization Wright and Singelmann,1982; Salaman 1982 , and a declining middleclass Kuttner, 1983 They share the viewpresented in Bravermans Labor and MonopolyCapitalism 1974 that a devaluation of intellec-tual work to reduce the costs and power of laboris in the interests of business and industrialmanagement They also tend to agree that thestructural consequences of such a devaluationwill be to reduce the size, status and power of thewhite collar middle-class occupations Abercrom-bie and Urry, 1983; Goldthorpe, 1982 .

Claims that professional, managerial, and tech-nical work will be deskilled assume that thedifferent experiences of highly skilled and lessskilled mental labor with computerization so farare due to the lack of means to subordinatehigher-level work. These in turn rest on the as-sumption that Taylorism is the ideology behindthe choice of technology under capitalism andthat capital is ultimately extracted from subordi-nated

labor. Under this set of assumptions, wecould expect intellectual assembly lines to de-velop as the techniques of articial intelligenceimprove upper managements ability to controlthe mental labor process. Articial intelligencewould be viewed as a labor-saving technology,performing professional and middle-level mana-gerial tasks. The replacement of highly paidprofessionals by computer systems operated byless skilled labor would be considered an improve-ment in labor organization.

Different assumptions are made by those whoargue that computers will enhance the quality

and working conditions of intellectual labor free-ing humans from the drudgery ofroutine men-tal activity and freeing them for creative thought.The projected social consequences of this ar-rangement have been stated most optimisticallyby Daniel Bell 1980: 204-205 , who envisions a

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growing egalitarianism as a large class of knowl-edge elite acquires computer-enhanced skills.The theoretical argument that intelligent soft-ware will enhance mental work assumes thatcreative intellectual activity is uniquely humanand can never be automated. Routine thoughtprocesses that are amenable to mechanization areconsidered mental drudgery; optimizing highlyskilled human capital is believed to be the ap-propriate managerial strategy for dealing with in-tellectual labor. Under this set of assumptions,knowledge engineering applications should notreduce the wages, autonomy, or skill of employeesin the professional, managerial, and higher-leveltechnical categories.

Available evidence on the deskilling debate ismixed and poorly supported by empirical re-search Attewell and Rule 1984 . Deskillingclaims are best supported for the lower levels ofmental workskil1ed blue collar, clerical andtechnician jobs Ayres and Miller, 1983; Downing,1980; Gottfried, 1982; Shaiken 1984; Straw andFoged, 1983 . For managerial, professional, andmore highly skilled technical occupations, skilland autonomy enhancement or at least the sub-jective impression of it tend to be reported. Evenamong clerical workers, however both skillingand deskilling evidence has been reported Kling,1985 . Even when jobs are deskilled the peopleperforming those jobs may not be as when un-skilled workers enter low-skill computerized jobs,

improving their relative position. It is clear thatcomputer technology itself does not automaticallyhave a single effect upon conditions of work. Newmeans to rationalize intellectual activity and toembody technical skill, professional judgment,and decision-making logic in computers will notnecessarily lead to intellectual assembly lines.They will, however extend the deskilling debateto higher levels of the stratication system.

The Rationalization of Mental LaborThe idea of using computer technology as ameans to rationalize intellectual labor dates back

at least to the end of the seventeenth century,when Leibniz wrote:It is unworthy\of excellent men to lose hourslike slaves in the labor of calculation whichcould be safely relegated to anyone else ifmachines were used. 1959: 156-164


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INTELLECTUAL ASSEMBLY LINES 113

Charles Babbage, whose 1833 design for theanalytical engine was the prototype of the mod-ern digital computer, developed factories or-ganized around the principle that

Human labor is similar to capital, raw materi-als, etc. It is therefore subject, or ought to besubject, to similar input/output analyses, meas-urement, standards and controls. Babbage,1982

Although not a direct precursor of Frederick Tay-lor s work, Babbage was interested in the samesort of time and motion studies that became thehallmark of Scientic Management Gideon,1982:114 .

The substitution of machinery for labor was anearly part of the industrialization process. KarlMarx

197 32110-126 agreedwith

Babbagesde-

nition of a machine as a division of labor in whicha single engine links particular operations performed by a single instrument. Although Marxis often misquoted as having said that the handmill produced feudalism and the steam millproduced capitalism, his theory was not one ofsimple technological determinism. Before newmachinery could be introduced, he argued, thosewho have the power to redene tasks andproducts must reorganize work to accommodatethe equipment. While Marx applied his theory tothe reorganization of manual labor under capital-

ism, the subject ofrationalized intellectual laborwas taken up by Max Weber and later theoristsof bureaucratic organizations. Today, the automa-tion of bureaucratically rationalized mental laborby computers is made possible by an extension ofindustrialization which Norbert Wiener called aSecond Industrial Revolution in which thesporadic design of individual automatic mechan-isms is replaced by communication betweenmachine and machine 1967:208 .

Wieners cybemetics is the study of communi-cation and control in humans and machines.Based on the theoretical work of Willard Gibbs whose research institute became a model for thecontemporary division of labor in science , cyber-netics made intellectual assembly lines theoreti-cally possible, with coordination of rationalizedmental tasks performed by communication andcontrol technology. However, because computers

can accommodate multiple tasks occurring atdifferent tempos and sequences, intellectual as-sembly lines need not look like factories. Com-puters can be used to coordinate work performedby geographically dispersed individuals workingat their own pace without direct human supervi-sion. In theory, the rationalization of mental la-bor which characterizes the intellectual assemblyline could integrate individual efforts into largerhuman projects as -easily as it could subordinatetheir mental activity to alienating working situa-tions. Thus, the way in which computerized workis rationalized depends more upon who is able todene whom as excellent men or anybodyelse than upon purely technological possibilities.

The Mechanization of Thought ProcessesThe eld of computer science known as articial

intelligenceinvolves the

designof

computer pro-grams and automated equipment, such as indus-trial robots, with a limited capacity to behave inways that at least resemble human thoughtprocesses for a technical survey, see Barr andFeigenbaum, 1982; Hayes-Roth, 1983; orCoombs, 1984; for a sympathetic popular histo-ry, see McCorduck, 1979 . Information from theoutside world can be sought, interpreted, andused asthe basis for heuristic decisions whichin humans would be called best guesses. Theprogram can within the narrow range of theworld to which they are applied, draw inferences,

suggest solutions to previously unsolved prob-lems, select relevant information according totheir own internal criteria, and modify their ownbehavior as a result of the outcomes of their previ-ous actions.

The theoretical possibility of representing hu-man knowledge and decision-making processes incomputer programs has been ercely debated onboth scientic and moral grounds, with the stron-gest objections coming from the philosopherHubert Dreyfus in What Computers Can t D0 1972 and the articial intelligence expert JosephWeizenbaum in Computer Power and HumanReason 1976 . One important issue is the degreeto which human decision-making is believed to berational and logical. Intelligent software has beenmost successful for those applications in which theknowledge of human experts is characterized bygreat rationality; to claim that such programs can


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perform in any area of human expertise is essen-tially to dene all areas ofhuman expertise as ra-tionalizable. Such arguments are best received byindustrial and professional managers interested inroutine applications of knowledge and techniqueand by those who subscribe to the Taylorist prin-ciple that successful management involves max-imum rationalization and control over labor.

Automated programming, industrial planning bymachine, and mechanization of the professionswere topics on the agenda of a 1958 internationalconference on the emerging eld of articial in-telligence National Physical Laboratory, 1959 . Inaddition to Leibniz goal of saving the labor of ex-cellent men managerial control and protabilitywere among the reasons advanced for supportingA.I. During the next twenty-ve years, articial in-telligence was transformed from academic re-

search projectsto

widely publicizedcommercial

applications Feigenbaum and McCorduck, 1983;Hayes-Roth, 1984 . Expert system developerspromise that their software will capture theknowledge of experts in programs that enable aless skilled person to achieve expert results:

Knowledge is a scarce resource whose rene-ment and reproduction creates wealth. Tradi- tionally the transmission of knowledge fromhuman expert to trainee has required educa-tion and internship years long. Extractingknowledge from humans and putting it in com-

patible forms can greatly reduce the costs ofknowledge reproduction and exploitation. skill means having the right knowledge and us-ing it effectively. Knowledge engineering ad-dresses the problem of building skilled com-puter systems, aimed rst at extracting the ex-perts knowledge and then organizing it in aneffective implementation. Hayes-Roth, Water-man and Lenat, 1983:5, 13

While the debate between those who argue thatmachines can think and those who argue thatthey can t is quite complex for reviews, seeBoden, 1977 and Haugeland, ed;, 1981 , thepractical success of intelligent programs thatplay chess, infer chemical structures frommolecular data, and diagnose illnesses indicatesquite clearly that articial intelligence is being

put to wor at industrial and professional tasks,despite the reservations of many theorists. Themost ambitious practical proposals involving ex-pert systems are those for the new fth genera-tion supercomputers Feigenbaum and McCor-duck, 1983 Promising higher industrial produc-tivity and greater national security, the proposalscall for many areas of military and civilian expertdecision-making to be turned over to the faster,soon-to-be smarter machines. In his thoughtfulcritique of the fth-generation idea, JosephWeizenbaum questions Feigenbaums assertionthat computers willproduce the future knowledgeof the world, asking how are we to understandjust what information a computer actuallyproduces and how it does so Weizenbaum, 1983 .But if information itself is seen as a commodityproduced for prot by the rational organizationand mechanization of intellectual

labor,then in-

formation can be produced by the computer in thesame way that products were made by the facto-ry machinery of the rst industrial revolutionthrough the alienation of laborers from theproduction process Perrolle, 1985 .

The Transformation of Technical Skill: Ration-alization and Mechanization in SoftwareProductionIn its short history, computer programming hasbeen transformed from a manual task of wiringboards performed by women clerical workers to

a romanticized craft popularly believed to be one9

of the major sources of future high-tech employ-ment. Today, however, software production is be-ing rapidly rationalized into routine work Kraft1977; Kraft and Dubnoff, 1983 The word com-puter rst described the jobs of women who per-formed calculations and wired hardware for thepioneering ENIAC, and only later came to meanthe machines that replaced them. The manualand routine mental work of the women was tak-en over by machines; the creative component wastransferred to male mathematicians who becameknown as programmers. This process simultane-ously produced both skill enhancement and deskilling as the intellectual work was differen-tiated into design and execution tasks. The designphase was redened as creative work; the rou-tinized mental labor was devalued in symbolic


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INTELLECTUAL SSEM LY LINES 115

and monetary terms and viewed asthe appropri-ate target for automation.

From the compilers of the 195 s to contem-porary structured programming, relational data-bases application generators, and expert sys-tems technological developments in softwareproduction have all been applied to the routiniza-tion of programming, even though most were in-troduced to spare humans from mental drudgery.In 1958, Commander Grace Murray Hopperreported two consequences of her recently invent-ed compiler: rst U.S. Naval ofcers found totheir satisfaction that the new computer tech-niques gave project managers better control overthe activities of programmers; second, experi-ments indicated that a new division of labor inprogramming, with highly skilled systemsanalysts producing owcharts and clerically

trained high school graduates producing code,was the optimal use of the new techniques.Programmers who at rst opposed the change forfear of losing their jobs found that the new divi-sion of labor provided them with upward mobili-ty while creating new low-level jobs for the coders Hopper, 1959 . Analyses of software productionin the 1960s and 1970s have documented theemergence of a hierarchical division of labor simi-lar to that in blue collar industries Kraft, 1977;Kraft and Dubnoff 1983 .

Today, structured programming and its exten-sions offer new control mechanisms at a time

when data security from high-tech crimes is agrowing concern in economic institutions. Itoffers a way to replace temperamentalprogrammer-craftsmen with better disciplinedand less expensive technical laborers organizedinto intellectual assembly lines. Structuredprogramming began with a 1967 paper by theDutch computer scientist Edgar Dijkstra, whomay become known as the Henry Ford of com-puter programming. He offered an elegant mathe-matical approach to the problem of program com-plexity and thus the hope of bug-free software Olson, 1984 By rationalizing the process of soft-ware design and coding, structured programmingoffers rms a 10 percent to 20 percent increasein program productivity McClure, 1984 How-ever, there is at present no good empirical re-search supporting these claims Vessey and We-ber 1984

Structured programs are easy to understand,x, modify and divide into separate parts. Well-dened tasks for programmers that can be in-tegrated into larger programming projects are thesoftware equivalent of interchangeable parts. Ac-cording to the software engineer FrederickBrooks, Jr., the major impact of structuredprogramming has been to introduce the conceptof control structures into program design 1982:144 . But such control structures also con-trol programmers by limiting the scope of theiractivity. An extension of the concept to databasedesign has produced the relational database,which maintains data in forms that can be usedwithout being directly accessed Codd, 1982 Al-though this introduces important technical im-provements in data security, task coordination,and software reliability, the restructured workingconditions restrict the

autonomyand responsibil-

ity of programmers.When combined with research on programmer

knowledge cf. Soloway and Ehrlich, 1984 , struc-tured programming techniques can be used in ap-plication generators. While application generatorsare not, strictly speaking, expert systems, they doenough reasoning to enable a relatively inex-perienced programmer to produce software Keller and Townsend, 1984 In a recent surveyof one small company 50 programmers whichconverted to application generators, productivitydid increase markedly over a ve-year period

while real wages fell. Younger programmers wereenthusiastic about them reporting that theirskills were enhanced. More experiencedprogrammers, however, reported beingdeskilled Perrolle, et al., 1986

Many articial intelligence experts believe thatsoftware production will soon be largely per-formed by expert systems Wenger, 1984;Frenkel, 1985 According to Bruce Buchanan Shurkin 1983:7 7 , a major problem in softwareproduction is the time it takes programmers toconvert the acquired knowledge into programs.Implementation of knowledge acquisition sys-tems connect the expert directly with the com-puter and save all that programmer labor.Programmer labor however is a signicant partof those expanding high-tech jobs which propo-nents of the information revolution are promising.


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Expert Systems in the ProfessionsAlthough business analysts report that most oftodays expert syst s are limited in scope andquite costly Alexander, 19842118), specialistswithin the computer industry Hayes-Roth, 1983;dAgapeyeff, 984; Basden, 1984) predict asteady growth in the replacement ofhumans withexpert systems in narrowly dened areas of ex-pertise. About a quarter of the serious expertsystems in use in 1984 were in the professions,as shown in Table 1. Some knowledge engineershave begun to identify their potential for automat-ing professional Work as a problem. Feigenbaumrecently pointed out that Everyone Worriesabout the fate of the blue-collar workers. .its

the highly paid professionals we ought to startworrying about 1984).

Although the use of expert syst s presup-poses, at least initially, that there are human ex-perts to be consulted, in their industrial andprofessional applications expert systems usethose experts as models for work settings inwhich people ofmuch lower skills can achieve thesame results. This implies that the knowledgeelite is likely to be much smaller than usuallypredicted. Also, rather than being composed ofour most creative thinkers, it is likely to be com-posed of those who have most successfully kepttheir knowledge to themselves.

. 1 . 1 . ; o -~ u

TABLE SUCCESSFUL EXPERT SYSTEMS, BY OCCUP TION L RE 1984

PROFESSIONAL Medical 15.9Research 7.2Eng inee r ing 3.7Professional Services 3.6

TECHNICAL Computing 19.6Electronics 6 50 11 and Mineral E x p l o r a t i o n 7.2

M N GERI L Financial S e r v i c e s 3.6

MILITARY 10.9

OTHER 21.8

N=138

Based on data from Ti m Johnson Th e Commercgl_Application of ExpertSystems Technolggy. London Ovum,


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INTELLECTUAL SSEM LY L N S 117

At the 958 international articial intelligenceconference, physician Francois Paycha outlinedthe logic of medical diagnosis and argued thatmechanization could solve some of its difculties.Legal expert Lucien Mehl proposed that

a machine for processing information can bean effective aid in searching for sources of le-gal information, in preparing the decision ofthe administrator or judge, and nally inchecking the coherence of the solutions arivedat. Mehl, 19592757

Although Paycha suggested that we could not an-ticipate the wider social consequences ofmechanized medical diagnosis, Mehl echoedLeibniz belief that the labor of excellent menwould be saved for devotion to research proper,

to true scientic thought. He further arguedthat although judicial machines would be suitedto conducting legal argument, they could neverreplace human legal experts because they wereincapable of formulating precepts.

In the next decades, medical and legal knowl-edge became the subject ofintensive efforts to de-velop intelligent databases and software. Whileexpert systems developers would claim that com-puters do have the technical capabilities to replacemany of the functions of lawyers, the trends incomputer usage indicate that they are beingadopted in ways which facilitate the existing ar-

rangements of legal practice. Although computerprograms could be developed to render rationaljudgments for some sorts of cases the humanquality remains an almost sacred element in theadministration of justice; we are thus unlikely toexperience computerized judges. Most legal ex-perts would agree with Joseph Weizenbaum 1976 that any conceivable intelligence on thepart of a computer would lack the element of hu-man wisdom. Even using computers as infor-mants or providers of expert testimony is con-troversial Marx and Richman, 1984; Jenkins1979 .

What we can expect is accelerated use of com-puters to process court cases now terribly back-logged in most jurisdictions and to provide legalresearch services for attorneys. We may also ex-pect computer law to become a professionalspecialization; by 985 over 1000 lawyers be-

longed to national and regional computer law or-ganizations Connolly, 1985 . The Lexis andWestlaw systems are examples of specializeddatabase services for legal research Bander andSweetgall, 1983 . Their use may lead to concen-tration of power in larger law rms, which areable to afford these services. Centralization ten-dencies could be avoided by making legal infor-mation services available inexpensively to in-dividuals and small law rms.

In the medical profession as well, expert sys-tems seem to be emerging as aids for human ex-perts. While some skills, like using a scalpel, maybe lost to laser surgery Freifeld, 1984 , tech-niques like computer-animated x-rays will givephysicians more skill in diagnosing patients Sczence86 March, 1986:10 . The serious threatto the status of doctors is from institutional pres-

sures of hospital administrations and health careinsurers Anderson and Jay, 1985 . Many govern-ment ofcials and health care administratorswould like to rationalize the mental labor of phy-sicians. But, despite the opinion among knowl-edge engineers that medical diagnosis is a rela-tively straightforward problem, no one has seri-ous plans to automate doctors in the near future.In the long run the impact of computers on thesocial organization of medicine may be as dramat-ic as the telephones and automobi1es contribu-tions to shifting health care out of doctor s ofcesand into hospitals Starr, 1983 . But instead of be-

coming automated, physicians may use computer-based communications networks to move healthcare back out of hospitals.

The effects of computers on relatively power-ful professions like law and medicine depend lessupon technical possibilities for expert systemsthan upon political and economic issues of profes-sional autonomy, credentials, regulation, and therole of paraprofessionals. Mental labor is mostlikely to be subject to rationalization, control, andeventual automation in professions that allowtheir work to be done by less-skilled assistants.This is not a question of whether legal secretar-ies and nurses are capable of performing moreskilled tasks, or even whether they in fact do sounder a doctor or lawyers direction. It is a ques-tion of whether the paraprofessional can bemanaged directly by institutions without the serv-ices of the supervisory professional. As in other


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instances of computerization, skill enhancementmay occur for paraprofessionals as the profession-als lose part of their privileged status.

Spokesmen for professional engineering havewarned for decades that professional status is

reduced by c ha ngethat threatens

expertknowledge:

The engineer who at one time was the educat-ed and elite leader in matching science to so-ciety is fast becoming just another member inthe industrial labor force. Forrester, 1967

A review of the effects of computers on creativi-ty in chemical engineering education Drake andPerrolle, 1984 suggests that the employment ofless expensive and more narrowly trained tech-nical people may exacerbate the problem of ob-

solescence for more experienced engineers. Inaddition it appeared that the mental labor savedby the use of expert systems may be subjected toheavy pressures for higher productivity ratherthan freed for more interesting types of work. In actual implementations, however, intellectual as-sembly line arrangements sometimes prove un-satisfactory, even when initially chosen bymanagement Cass, 1985; Perrolle, et al., 1986 .Engineering problem-solving often calls forbroader understanding and more exible think-ing than can be embodied in even an extremelyintelligent program. In the hands of experts, asin Digital Equipment Corporations most recentchip design project Bairstow, 1985 , expert sys-tems can save the labor of excellent people.

Computerized ecision MakingIn the 1950s, the application of computers tomanagement decision-making was believed to belimited to the performance of routine clericaltasks and to objective decisions based solely oneconomic criteria. While admitting that manage-ment decisions ought to be objective whereverpossible and thus should be subject to automa-tion , Merriman and Wass 1959 afrmed thesubjective nature of managerial decisions as partof the spiritual nature of man. Like doctors andlawyers, managers claimed for themselves a spe-cial and creative role in human decision-making.In the next decades debates over the possibilityand desirability of mechanized thought process-

es it was widely asserted that managers func-tions simply could not be performed by machines.

Today, the capacities of expert systems includesuch domains as nancial services currently per-formed by highly paid managerial employees Sul-

livan, 1984 .As Gio Wiederhold

1984 argues,the

use of knowledge-based systems can move well-understood human decision-making into the com-puter systems. This includes a wide range of mid-dle managerial tasks. Even more important are de-velopments in management information systemsthat allow a concentration of decision-making intothe hands of fewer managers. Despite the opti-mism of Herbert Simon 1985 , Kenneth Arrow 1980 and other economists who have examinedthe impact of information systems on businessdecision-making that centralization will not occur,they recognize the possibility.

In some areas like modern petrochemicalplants and the military the new technological pos-sibilities for centralized decision-making are al-ready being realized. Embedded systems, combi-nations of hardware and software designed tofunction in integrated environments, are alteringmilitary and production technology. In chemicalprocessing plants, integrated management infor-mation systems permit centralized control ofeverything from purchasing decisions on feed-stocks to projected markets, pricing, process de-sign and overall system optimization Drake andPerrolle, 1984; The New Cockpits of Industry,1983 . This industrial trend extends the work-place routinization process to nancial and oth-er middle-level managers who formerly made in-dependent evaluations and decisions in their ownarea of expertise.

The U.S. Defense Departments Ada projectand Strategic Computing Initiative represent ma-jor efforts to rationalize, centralize, and automatemilitary decision-making. Since almost all of thepost-World War II developments in computertechnology have been funded by the military At-water, 1982 , Defense Department priorities willprobably drive the development of intelligent soft-ware. The Ada project, intended to produce ahuge standardized language for large-scale intel-ligent software applications, is a step towardpromoting large, centralized control structures for a description of the Ada language, seeBarnes 1982 Technical criticisms of the Ada


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project Skelly, 1982; Ledgard and Singer, 1982;Winchman, 1984; and Hoare 1981 include argu-ments that it is too large and too expensive to beimplemented except by large organizations. Somecritics suggest that it represents a stiing by mili-

taryinterests of other new

programmingideas

Rosenberg, 1983; Begley, 1983 .The Strategic Computing Initiative Ofce of

Technology Assessment 1986; Lin, 1985; Parnas,1985 is diverting expert systems research towardpilots assistants, autonomous tanks, and battle-eld management systems Although there willun ou te ly be non-military spinoffs, the hierar-chical nature of military decision-making maystrongly promote decisioncentralizing softwareas the industry standard. Also, as many oppo-nents of militarized expert systems and struc-tured programming fear, the belief that such sys-

tems can be made bug-free and reliable enhancesthe probability that military decision-making es-pecially in the area of nuclear strategy will beembedded in these structures. Critics believe thatthe risk of an accidental computerized triggering of nuclear war is being signicantly increased bythe Pentagons chosen directions in computerdevelopment.

The Devaluation of Mental LaborIn both an economic and a cultural sense andregardless of the outcome of the deskilling de-bate, the spread of knowledge engineering will

devalue some kinds ofmental labor. In the eco-nomic sense professional, technical and manage-rial employees who do the kind of thinking thatmachines do or that inexpensive labor does withmachines will see a relative reduction in theirwages and salaries unless they can acquire newtasks or protect their existing areas of expertisefrom automation.

As knowledge engineering rationalizes and au-tomates some areas of mental labor, those whoare less successful at nding creative new activi-ties may shift the focus of job satisfaction fromautonomy and real control over the labor processto symbolic gestures of social standing. Alreadythe terminology of computer technology denesworkers subjected to the control of managementsystems as computer users. o titles contain-ing the words manager, designer, and ana-lyst often do not correspond very well to wages

and actual working conditions. Even computerequipment repairers who often replace partswith little understanding of how the machineryworks wear business suits and carry their toolsin briefcases. Among the middle class there is a

growingconcern for what Randall Collins

1979:72 calls a consciousness of formalismdirected away from the material realities of workexperience and into the purely relative values ofcultural currency

In a culture concerned with self and status thevery meaning of work is changing. What one doesin an instrumental sense is being replaced bywhat one displays in terms of symbolic status. Solong as the illusion is maintained that employeeson intellectual assembly lines are managing a sys-tem which enhances their intellectual skills, thesymbolic token may be satisfactory. The con-

tradiction in this arrangement is that if the com-puter software devalues labor in economic terms,the illusion will become increasingly difcult tomaintain. In the long ru capitalist culture mayteach that intellectual skills are not a source of hu-man satisfaction; in the short run downwardlymoble white-collar workers demand for the ma-terial rewards due their middle-class status ispredicted to create a crisis of distribution Leon-tiff, 1980 .

The mechanization of thought processes maybe translated into a cultural devaluation of the ra-tional, logical aspects of human knowledge and

intelligence. Sherry Turkle 1983 nds youngchildren exposed to computerized toys stressingfeelings rather than thinking as the deningcriteria of being alive and human. Critics of ar-ticial intelligence and humanist critics of the so-cial injustices of Western technological society cf. Capra, 1982 tend to agree in condemning in-strumental rationality as a form of tyranny overthe human spirit. These combined assertions thatthe essence of human thought is what machinescan t do and that it is feelings rather than logicwhich make humans human, somewhat paradox-ically help to legitimate turning over instrumen-tal decision-making processes to expert systems programs. The machines are only behaving incoldly instrumental ways which are not true ex-pressions of our humanity. Unfortunately, in-strumental decision-making is at the hear t ofdemocratic political institutions. A devaluation of


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decisionmaking logic may render the democraticprocess even more concerned with emotionalsymbols of group solidarity and less concernedwith rational discussions of issues than it alreadyIS.

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