Handbook of Ethics, Values, and Technological Design: Sources, Theory, Values and Application Domains

677 Pages·2014·10.012 MB·English

by  Jeroen van den Hoven, Pieter E. Vermaas, Ibo van de Poel (eds.)

HandbookofEthics,Values,andTechnologicalDesign
DOI10.1007/978-94-007-6994-6_1-1
#SpringerScience+BusinessMediaDordrecht2014
Modeling in Design for Values
SjoerdD.Zwart*
TUEindhoven,Eindhoven,Netherlands
Abstract
This chapter addresses societal implications of models and modeling in engineering design. The
more standard question about well-known technical and epistemic modeling values, such as safety
and validity, will be left to the standard literature. The sections “Introduction” and “Values in
Modeling: Framing and Standard Views” discuss relevant societal norms and values and the ways
inwhichtheyaremodelrelated.Additionally,standardpointsofviewarediscussedaboutthevalue-
ladenness of models. The section “Value-Related Issues Emerging in Model Building and Use”
shows various ways in which engineering models may turn out to have unforeseen societal
consequences. An important way to avoid such consequences and deliberately model for values in
apositivesenseistotakemodelsasspecialkindsofartifacts. Thisperspectiveenablesmodelersto
applydesignermethodsandtechniquesandviewamodelingproblemasinneedofanexplicitlistof
designspecifications.Doingso,modelersmayapplyformsofstakeholderanalysisandparticipatory
design. Additionally, they may apply well-known, hierarchical means-end techniques to explicate
and operationalize the relevant values; doing so, they support discussions about them within and
outside the design team. Finally, the model-as-artifact perspective stimulates modelers to produce
technicaldocumentationanduserguides,whichwilldecreasethenegativeeffectsofimproperuse.
Thechapterendswithachecklistofissues,whichthedocumentationshouldcoverifamodelingfor
values is taken seriously.
Keywords
Model; Value-ladenness; Instrumental and derivative values; Engineering, modeling, and societal
and environmental values; Accountability; Affordance; Model as artifact; Modeling practices;
Participatory design, value identification, and implementation; Value hierarchy; Model
documentation
Introduction
In(2002),Jean-PierreBransencouragedalloperationsresearch(OR)professionalstotakeTheOath
ofPrometheus,whichishisversionoftheOathofHippocrates,wellknowninthemedicaltradition.
After having done so, the OR modeler as decision-maker should not only try to achieve her or his
own private objectives but should also be committed to “the social, economic and ecological
dimensions of the problems.” These objectives should be met “within the limits of sustainable
development.”Moreover,themodelershouldrefusetoprove“informationortools,whichin[her/is]
opinion could endanger the social welfare of mankind and the ecological future of Earth.”
*Email:[email protected]
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This imperative of Brans is closely related to avoiding Robert Merton’s third possible cause of
“unanticipated consequences of purposive social action,” viz., the “imperious immediacy of
interest,” which will be discussed in the section “How to Identify and Address Value-Related
Modeling Problems.” On the engineering side, the National Society of Professional Engineers
(NSPE) expects its practitioners to exhibit the highest standards of honesty and integrity and act
under the highest principles of ethical conduct. As engineering has a direct and vital impact on the
qualityoflifeforallpeople,it“mustbededicatedtotheprotection ofthepublichealth, safety,and
welfare.”AccordingtotheAmericanSocietyofMechanicalEngineers,integrityandethicalconduct
are core engineering values, just as are the diversity and respect, the dignity, and the culture of all
people. According to engineering codes, practitioners should nurture and treasure the environment
and our natural and man-made resources.
Tofulfilltheexpectationsofengineeringsocieties,thischapterdoesnotfollowBrans.Itwillnot
formulate an Oath of Epimetheus or Hephaistos. Instead, it concentrates on forging a common
groundforunforeseenvalue-relatedissuesregardingmodelconstructionanditsuseontheonehand
andvaluesinengineeringdesignontheother.TofulfilltheNSPErequirements,forinstance,design
engineersshouldhaveanideaofwheretolookforvalue-relatedissues,andtheyshouldknowhow
toidentifyandmanagethem.Thepurposeofthischapterthereforeistohelpthesemodelerstogetto
grips with these underexposed questions about value-ladenness of engineering models. Modeling
forvaluesinengineeringdesignasjustsketchedisalargesubject,anditwillbedelimitedasfollows.
First, the chapter will not sketch an overview of how to achieve standard modeling values, such as
verification, validation, robustness, etc. Regarding these well-known subjects, it will refer to the
standardliterature.Second,itdoesnotembarkuponsurveyingtheliteratureonclassicalengineering
valuessuchassafety,risk,reliability,costs,andsecurity.Third,wewillnotgointoethicalquestions
aboutwhethersomeexplicitmodelingpurposeismorallyacceptableornot.Thatisageneralethical
question,whichisnotthetopicofthischapter.Here,itisassumedthatthepurposeoftheengineering
model is morally acceptable.
Instead, this chapter embarks upon the questions of how to identify and solve the more hidden
societal and environmental implications of modeling in engineering design. Answering these
questions serves the purpose of helping model builders and users to develop more explicit ideas
aboutthevalue-ladennessofmodelproductionanduse.Thelatter involvestopicslikewhichkinds
ofvalue-relatedissues possibly emergeinengineeringmodels,where tolookforthem, and howto
address them proactively in the modeling process. To achieve this end, in the section “Values in
Modeling: Framing and Standard Views,” we analyze the most relevant ideas and introduce some
standard positions regarding the value-ladenness of models. Next, in the section “Value-Related
IssuesEmerginginModelBuildingandUse,”wewilldiscusssomeempiricalfindings.Theypresent
examplesofunanticipatedvalue-relatedissuesinthepracticesofengineeringdesignandhowthese
values emerge in model construction and use. Then, in the section “How to Identify and Address
Value-Related Modeling Problems,” we will discuss how to handle these values in a responsible
way. The main advice in this chapter is to view models as special kinds of artifacts. Consequently,
the method advocated here to design for values will be to take advantage of existing design
methodologies while modeling. Here, we will consider, for instance, the four-phase design cycle
to operationalize, put into effect, and document model-related values in a systematic way.
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Values in Modeling: Framing and Standard Views
Models and Modeling in Engineering Design
Modelscomeunderallformsandsizes.Almostanyonecantakealmosteverythingtobeamodelof
anything else. This is perhaps the reason that until today all endeavors to provide an explicit
definition of a model using necessary and sufficient conditions have failed. In their “Models in
Science”lemmaintheStanfordEncyclopedia,FriggandHartmann(2012)donoteventrytogivea
definition. Morgan and Morrison (1999) confess: “We have very little sense of what a model is in
itself and how it is able to function in an autonomous way” (p. 8). In this chapter, models in
engineering design are supposed to be (1) approximate (2) representations of the target system,
whichistheactualorfutureaspectofrealityofourinterest.Moreover,itisassumedthatmodelsare
constructed and usedfor (3)an explicit goal that not always needs tobe epistemic. Models may be
used for constructions, for explorative purposes, for making decisions, for comparison, etc. In this
chapter, “model” is taken to be a notion of family resemblance such as “game” or “science” for
which the three characteristics mentioned are important ingredients.1 This model concept does not
cover all the ways in which the model notion is used. Notably, people use the “model” notion in
explorative contexts in which the representation element is less explicit such as in artificial life
models or agent-based models. Sometimes “model” seems even to refer to something similar to a
paradigm. This chapter does not cover these uses of the word model. Although the above model
characterization may seem conservative, it nevertheless emphasizes the purpose of a model, which
traditional engineering definitions often seem to ignore. Take, for instance, the IEEE 610 Standard
Computer Dictionary. It defines a model as “[a]n approximation, representation, or idealization of
selectedaspectsofthestructure,behavior,operation,orothercharacteristicsofareal-worldprocess,
concept, or system” (Geraci 1991, p. 132).
Embarking on the questions regarding values in modeling in engineering design requires some
explicitframingoftherelationbetweenvalues,models,artifacts,theirauthors,andusers.Tosketch
myframe,Istartwithaone-leveldescriptioninwhichanartifactisproducedandused.Onthislevel,
theartifact istheobject(oritsdescription) thatcomesoutofasuccessful designprocess.Themost
obviouswayvaluescomeaboutonthislevelisthroughthegoalsoftheartifact:istheartifactmade
to promote the good or to inflict harm? Values also come in, however, because an artifact is the
outcome of a design process, and this outcome is applied in society. Questions therefore arise, for
example, about the designers properly considering all the relevant stakes or about the users
neglecting the user plan and inflicting (un)intentionally societal harm by way of the artifact’s
unintended application.
To finish the conceptual frame, I propose models to be special kinds of artifacts, which, in
engineeringdesign,aimatbeingappliedtothedesignofanotherartifact.Thisresultsinatwo-level
description. The modeler produces a model, which will be used by the engineer, the user of the
model, to produce a second artifact that again will be applied in society. In such a process, values
come in various ways. We should consider the intrinsic values of the model and artifact and the
1Notethataccordingtomycharacterization,amathematicalmodel“isnotmerelyasetof(uninterpreted)mathematical
equations, theorems and definitions” (Gelfert 2009, p. 502). They include their interpretation rules that define the
relation between the equations and some features of the target system. “Mathematical model” is therefore a thick
concept.
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instrumental values related to the production and the use of the model and the artifact.2 Moreover,
thesituation becomes evenmore complicatedif werealize thatthe secondartifactcould beagaina
model to produce still another artifact or the model may be used for more than one artifact. I will
leave these possibilities out as they can be reduced to the previous situation.
The two-level description reveals the complexity of the relation between values, modeling
processes, and the products of these processes. Users apply models as a means to achieve some
end, which again may be the construction of another artifact, or even a model, with again different
values.Thecascadeofmeans-endrelationsintroducesagamutofvalues;inaddition,allthemodel
and artifact means-end relations are open to questions about collateral damage of the model or
artifact and about more efficient waysto solve the design problem. Moreover, the actions ofall the
modelers and designers are amenable to normative assessments as well. In this chapter, we will
observe that the traditional idea according to which professionally appropriate modeling will
automatically produce morally correct models does not hold. The model-as-artifact perspective in
combination with the means-end cascades undercuts this idea.
Two-leveldescriptionshelptodisentanglethewaysinwhichmodelsandvaluesarerelated.Letus
first consider the case where models are constructed as artifacts for their own sake, the first-level
description. Models, then, are designed for some specific purpose and they should come with a
manual.Wemay,therefore,atleastdistinguishbetweentheintrinsicandtheinstrumentalvaluesof
themodel.Thefirstmaybehistoric,symbolic,esthetic,orfinancialvalues,etc.,sincetheymakethe
model good in themselves, and the second relate to the purpose of the model, such as decision-
making, exploration, communication, simulation, etc. If on top of that a model is developed to
designanartifact,thedesignofthemodelshouldbedistinguishedfromthatoftheartifact.Insucha
case, we should consider at least three different ways in which values and models are related.
Like in the first-level case, in second-level descriptions, a model may have intrinsic and instru-
mentalvalues,whichrelateto(andsometimesmayevenequatetheintrinsicvaluesof)thedesigned
artifact. Third, however, and this is new in comparison with the first-level case, the instrumental
values of the designed artifact often become distinctive consequences of the model with the aid of
which this artifact is constructed. These may therefore be called the model’s derivative values.
Considertheparadigmaticexampleoftheinternalcombustionenginepollutiondesignedbymeans
of a model that relates and predicts the parameters of this engine (and its polluting features). The
modeling for values in engineering design explored in this chapter mainly concerns the model’s
instrumentalandderivativevalues.Themodel’snormativeimpactisprimarilyconsideredduetoits
own instrumental values and to the instrumental values of the artifact it helps to develop.
Various Values
Whatare the valuesthis chapter doesfocus on? Interestingly, the two codesin theIntroductionput
the values of honesty, integrity, and ethical conduct at the top of their lists. If we cannot count on
modelers and engineers to respect these values, the discussion of modeling for values would not
2Inthischapter,IwilladoptFrankena’s(1973)definitionofintrinsicandinstrumentalvalues.Thefirstare“thingsthat
aregoodinthemselvesorgoodbecauseoftheirownintrinsicproperties,”andthelastare“thingsthataregoodbecause
theyaremeanstowhatisgood”(p.54).
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even get off the ground. Assuming these personal attributes of the main actors, we discern the
followingvaluesamongthosethataregenerallyseriouslytakencareofwithinengineeringpractices:
safety, risk, reliability, security, effectiveness, and costs of the artifacts. I will call them the
engineering values. Within the professional model building practices, among the values explicitly
recognized are, at least, verification, validation, robustness, effectiveness, and adequateness of the
model;Iwillrefertothosebythetermmodelingvalues.Aswetakemodelstobespecialinstancesof
artifacts,thefirst-levelmodelingvaluesshoulddirectlyservetheengineeringones,whichisindeed
thecase.Manyofthemaredirectlyrelatedtothevaluereliability.Withinasecond-leveldescription,
thederivativevaluesofamodelalso(indirectly)concerntheinstrumentalvaluesoftheartifactthatis
based on that model such as this artifact’s safety, reliability, effectiveness, and costs.
Values less universally taken into account in the technical practices of modelers and engineers
mainly cluster around three subjects: the quality of individual life, of social life, and of the
environment. The first concerns the health and well-being of human beings (and animals), their
freedom and autonomy, and their privacy. More specifically, even the user-friendliness of artifacts
falls within this cluster. The second cluster of values involves the social welfare of humankind,
protection of public health, equality among human beings, justice, and the diversity and dignity of
theculturesofallpeople,andsoon.Finally,thethirdsetofvaluesclusters aroundournatural (and
even artificial) environment and concerns sustainability and durability, sustainable development,
andtheecologicalfutureoftheearthsuchthatweshould“nurtureandtreasuretheenvironmentand
our natural and man-made resources.” Let us call these three clusters together the societal and
environmental values.
As this chapter is concerned with the values related to models and modeling, let us consider the
instrumental and derivative values of models in engineering design. First, we may consider the
technicalqualitiesofamodelinisolationwithoutconsideringthecontentsofitspurpose.Themodel
should be built to serve its purpose without breaking down. An important quality discussed in the
literature at length is, for instance, the models’ verification. For a model as a set of equations, the
latter implies, for instance, that these equations are dimensionally homogeneous, or for computer
models this quality means the model should not have bugs. Other important technical model
qualities are, for example, the model’s robustness – the model should behave smoothly under
small external disturbances – orefficacy, which is the model’s ability to produce straightforwardly
the desired effect. Besides these sheer technical properties, we can take the model’s goal into
account. If the latter is epistemic, an important epistemic value is its validation, which in many
contexts comes down to the question whether the model gives an approximately true account of
reality. And to what extent the model’s predictions are approximately true determines its accuracy.
Traditional modelers would probably also count the objectivity of a model as one of its epistemic
values.Thetechnicalandepistemicvaluesofmodelsarefirst-levelpropertiesofthemodelitselfand
have been extensively investigated and described in the standard literature on models and model-
ing.3Thepurposeofthischapteristohelpmodelbuildersanduserswithissuesofvalue-ladenness
of model production and use. Consequently, regarding questions about first-level technical and
epistemic values, I can with good conscience refer the reader to the standard literature.
A problem less frequently addressed in this literature and therefore part of this chapter is, for
instance, how different values should be weighed against each other, provided that they are
3See,e.g.,Zeigleretal.(2000);Sargent(2005);Barlas(1996);Rykiel(1996),etc.
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commensurable at all. For instance, how should avoidance of type I errors (claiming something is
truewhereasinfactitisfalse)bebalancedagainstavoidingerrorsoftypeII(claimingsomethingis
falsewhereasinfactitistrue)?Inscience,thefirstisconsideredmuchmoreimportantthanthelatter,
but this need not be the case in societal contexts (Cranor 1990). To illustrate the technical and
epistemic values of a model and the moral problem of balancing them against each other, let us
consider the case of the ShotSpotter.4
The ShotSpotter is a system that detects and positions gunshots by a net of microphones and is
mostlyusedinUSurbanareaswithahighcrimerate.Itissuccessfulindrawingtheattentionofthe
police to gunshots. Trials suggest that people hardly report gunshots to the police, while the
ShotSpotter immediately reports the time and place of a putative shot. Central to the system is a
model that aims at distinguishing gunshots from other noises. If a sound largely fits the represen-
tativecharacteristicsofagunshot,thesoundisreportedasagunshot.Themodeliswellverifiedifit
workswellateveryoccasionitisdrawnuponandnevergetsstuckintheprocess;itiseffectiveifit
doesnottaketoomuchtimetoproducethesereactions.Ifthemodeldiscriminateswellbetweenthe
soundsofshotsoffirearmsandotherbutsimilarsounds,itiswellvalidated,whichimplies thatthe
modelavoidstypeIandtypeIIerrorsasmuchaspossible.Statistically,however,avoidingerrorsof
thefirsttypeimpliesanincreaseoftheerrorsofthesecondtypeandviceversa.So,wantingtodetect
everygunshotimpliesmanyfalsepositives,anddecreasingfalsepositivescausesthepolicetomiss
morerealgunshots.Thequestionoftheappropriatesensitivityofthemodelhasthereforeimportant
societal implications, and its answer is not to be found in the technical literature (Cranor 1990).
Since models are artifacts, in principle all main engineering values mentioned might become
importantinstrumentalvaluesformodelsaswell.Inthesection“Value-RelatedIssuesEmergingin
Model Building and Use,” we will encounter some ways in which these values might become
relevantinthemodelingprocess.Themodeler,whomightevenbethedesigneroftheartifact,need
not always be aware of the relevant derivative values. Note that many of these engineering values
mentionedbeforeareextensivelytakencareofinthestandardsoftoday’sengineeringpractices.As
withmodelingvalues,hereagainIwillnotsketchanoverviewoftheextensivestandardengineering
literature. Instead, I will refer the interested reader to this literature.5 The same even holds mutatis
mutandisfortechnology-implicatedsocietalandenvironmentalvalues,whichmaynotrejoiceitself
at an extensive treatment in the engineering literature either. Even for these values, this chapter
refrains from embarking on explaining how to model for such values explicitly. I will not help the
reader in finding literature on, for instance, how to model for privacy or sustainability.6
Aswesaw,modelsmayberelatedtotechnical,epistemic,andsocial/environmentalvalues,which
canbeinstrumental andderivative.Thepurposeofthischapterisnowtwofold.First,itistosketch
various ways in which modeling projects might be, or might become, value related in ways
unanticipated by the modelers; in addition, it wants to show how projects may harbor overlooked
tensionsbetweenthoseindividualvalues.Second,itistomakethemodelersproperlyaddressthese
tensions within the modeling team and possibly the users and externally with the client and other
stakeholders.
4TheexampleisfromShelley(2011)whodiscussesseveralexamplesoftechnologicaldesignwithconflictinginterests.
5SuchasHaimes(2005)
6Asmodelsarespecialkindsofartifacts,manychaptersinthepresenthandbookdiscusstheengineering,societal,and
environmental values mentioned in this section and more. They provide important starting points for the standard
literatureIhavebeenreferringto.
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Current Ideas About the Value-Ladenness of Models
Valuesaregenerallyacknowledgedtoplayadecisiveroleinengineeringdesign.7Whatrolevalues
exactly play in modeling, however, is still controversial. Scarce attention has been paid to the
questionofthevalue-ladennessofmodelsinengineeringdesign.Thislackofinterestisremarkable
assoonasoneconsidersthemassivesocialimpactoftechnologyandtheimportantrolevaluesplay
in engineering design, which is the heart of technology. Because of the scarcity in the specific
literature, we will first discuss some opinions about the role of values found in the more general
modeling literature.8
Despite its limited size, the relevant literature displays many different opinions about the value-
ladennessofmodels.Itdisplaysoutrightdeniers,morecautiousadmitters,andmilitantchampionsof
the idea. To start with the first category within the context of operations research, the idea of
objectiveandvalue-freemodelsis,forinstance,expressedbyWarrenWalker.Hemaintainsthatthe
“questionof‘ethicsinmodeling’isreallyaquestionofqualitycontrol,...[and]...asanalyst...the
modeler must make sure that the models are as objective and value-free as possible”
(1994, pp. 226–227). More recently, Walker claims, “...if applied operations researchers (acting
asrational-stylemodelbasedpolicyanalysts,andnotaspolicyanalystsplayingadifferentroleoras
policy advocates) use the scientific method and apply the generally accepted best practices of their
profession,theywillbeactinginanethicalmanner”(2009,p.051),andheargues“thatthequestion
ofethicsinmodelingismainlyaquestionofqualitycontrol”(2009,p.1054).Asimilarwaytogois
to maintain that models themselves are value-free, whereas their alleged value-ladenness is attrib-
utedtotheirgoal.Kleijnen(2001),forinstance,claims:“amathematicalmodelitselfhasnomorals
(neither does it have -say-color); a model is an abstract, mathematical entity that belongs to the
immaterial world. The purpose of a model, however, does certainly have ethical implications”
(2001, p. 224).
Notalloperationsresearch(OR)colleaguesofWalkerandKleijnenagree.MarcLeMenestreland
Luc Van Wassenhove, for instance, are cautious admitters. In (2004), they distinguish between the
traditional “ethics outside OR models” just described and the more modern and radical “ethics
within OR models” where the various goals of the models are mutually weighted using multiple-
criteria approaches. But because “there will always remain ethical issues beyond the model,” they
optforan“ethicsbeyondORmodels”(2004,p.480).Byallowingandcombiningbothquantitative
andqualitativemodelingmethods,theyarguethat“analystscanadoptanobjectiveapproachtoOR
models while still being abletogive subjective andethical concerns themethodological place they
deserve. Instead of looking for a quantification of these concerns, the methodology would aim at
making them explicit through a discursive approach” (p. 480). Doing so, Le Menestrel and Van
Wassenhove maintain that “we should make [the need for close and on-going communication
betweenthemodelbuilderanduser]explicitlypartofthe[modeling]methodology”(2004,p.480).
Accordingtosomeauthors,LeMenestrelandVanWassenhovedonotgofarenoughanddisagree
withthemaboutthestrengthoftheirargumentthat“therewillalwaysremainethicalissuesbeyond
the model.” According to these proponents of the militant champions, we should opt for an
unconditional “ethics within model” and acknowledge that models are inherently value-laden and
thatweshouldaccordingly.AccordingtoPaulMcNelis,forinstance,“macroeconomicmodeling...
mustexplicitlybuildinandanalyzethevariableshighlightedbypopulistmodels,suchaswageand
incomeinequality...”(1994,p.5).OrasInaKlaasensuccinctlyexpressesthesameissue:“Models
7See,forinstance,PahlandBeitz(1984);Pugh(1990),Jones(1992);RoozenburgandEekels(1995);Cross(2008).
8Relevantliteratureoriginatesininvestigationsintoethicsinoperationsresearchandinvaluesincomputationalmodels.
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are not value-free: moreover, they should not be” (2005, p. 181). From the perspective of science
overall, Heather Douglas takes even a firmer stance and argues: “that because of inductive risk, or
theriskoferror,non-epistemicvaluesarerequiredinsciencewherevernon-epistemicconsequences
of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic
consequences of error can and should be considered in the internal stages of science: choice of
methodology, characterization of data, and interpretation of results” (2000, p. 559). More recently,
sheclaimsthat“inmanyareasofscience,particularlyareasusedtoinformpublicpolicydecisions,
science should not be value free, in the sense just described. In these areas of science, value-free
science is neither an ideal nor an illusion. It is unacceptable science” (2007, p. 121).
Withoutgoingintothediscussionbetweenthedeniers,admitters,andchampions,letusmaketwo
conceptualobservations.First,probablythemeaningoftheword“model”variesfromoneperspec-
tive to the other. Douglas and Klaasen obviously do not discuss Kleijnen’s uninterpreted “mathe-
maticalentitythatbelongstotheimmaterialworld.”Theywillconsidermathematicalmodelstobe
mathematical structures with a real-world interpretation. Moreover, these mathematical structures
canmutuallyweighvariousvalues,andwithreal-worldinterpretationswehavevaluesembeddedin
the model.9 Second, from the deniers’ perspective, the purpose of models is usually considered
epistemicandmodelsarethussimilartodescriptivetheoriesabouttheworldmuchakintoNewton’s
model of mechanics. In this model-as-theory concept, scarce room is left for normative consider-
ations or values, which are often considered subjective. Engineers tend to take a similar point of
view.Theyoftenviewmodelsasobjectiverepresentationsandassuchconsiderthempartofscience
ratherthanofengineering.Theadvocatesofvalue-ladennessofmodelsconceivemodelshoweverto
be instruments that assist in achieving some (often non-epistemic) goal. This model-as-instrument
conception of model is almost inconceivable without leaving considerable room for values and
evaluative considerations.
From the model-as-theory perspective, one may ask why a modeler should pay attention to the
ethicalandvalueaspectsofherorhiscreation.HowcouldweholdIsaacNewtonresponsibleforthe
V-2rocketsthatcamedownonLondonandAntwerpintheSecondWorldWar?Inthefirstplaceand
perhaps most importantly, modelers are normatively involved in the design process because they
create specific affordances used by the designers during this process. According to Gibson,
affordances are “offerings of nature” and “possibilities or opportunities” of how to act (1986,
p. 18). They are “properties of things taken with reference to an observer” (1986, p. 137). Gibson
extrapolated the scope of affordances and applied them also to technical artifacts such as tools,
utensils, andweaponsandeventoindustrialengineeringsuchaslargemachinesandbiochemicals.
Asmodelsareartifactsandcreatepossibilitiesofhowtoact,sayingthatmodelscreateaffordancesis
clearlywithinGibson’soriginaluseoftheword.Affordancesofartifacts,objects,oranyinstruments
therefore can broadly be conceived as those actions or events that these artifacts, objects, or
instruments offer us to do or to experience. Consequently, models afford us to get knowledge or
to decide about design proposals, which perhaps even did not exist before the model was created.
Generally,wemay saythatcreators ofaffordancesareatleastaccountable fortheconsequences
of these affordances. One may define accountability to be the moral obligation to account for what
happened and one’s role in making or preventing it from happening. In particular, a person can be
heldaccountableforX,ifthepersonhas(1)thecapacitytoactmorallyright(isamoralagent)and
(2)hascausedXand(3)Xiswrong(VandePoel2011,p.39).Accountabilityistobedistinguished
from blameworthiness. An agent can be accountable for an event but need not be blameworthy as
she or he can justifiably excuse herself or himself. Typical excuses are the impossibility to be
9Formoreonthedifferencebetweenembeddedandimpliedvaluesinmodels,seeZwartetal.(2013).
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knowledgeable about the consequences of the event, the lack of freedom to act differently, and the
absence of the agent’scausal influenceon the event (Van de Poel 2011, pp.46–47). For instance, a
manufactureroffirearmsmaybeheldaccountableforthekillingofinnocentpeople.Asthecreator
of the affordance to shoot, she or he may be asked about her of his role in the killings by the guns
madeinherorhiscompany.The typical excuse ofthe manufacturer reads thatsheorhedid notdo
the shooting and therefore is not (causally) responsible for the killing. In this sense, the creators of
affordancesareaccountablebutneednotbeblameworthyfortheconsequencesoftheseaffordances.
Similarly,butoftenlessdramatic,modelersareaccountablefortheconsequencesoftheaffordances,
viz., the design, because they willingly brought into being the affordances of their models.
Consequently, if the capacity, causation, and wrongdoing conditions are fulfilled, modelers are
accountable for the properties of the final design and may even turn out to be blameworthy and
should therefore pay attention to the normative aspects or their creations.
Value-Related Issues Emerging in Model Building and Use
Inthepresentsection,wewillencountervariouswaysinwhichconstructingmodelsmayhavemoral
andsocietalconsequences.10Thesesketchesservetheheuristicpurposeformodelbuilderstocreate
awarenessaboutwhereandhowtolookforthenormativeimplicationsoftheprocessandproductof
modeling. We will see that indeterminacy of the modeling question, the boundaries of the model,
underdeterminacy or the complexity of the modeling problem, lack of knowledge and uncertainty,
andfinallyembeddedvalueassessmentsinthemodelsmayhaveunforeseenvalue-ladeneffects.We
start with the situation where even the concept of the model does not exist yet and where it is even
unclear what the target system should be. Then, we turn to the possible underdeterminacy of a
model,andafterthatwewillconsidercomplexityanduncertaintyaspossiblesourcesofnormativity.
We will end with the necessity to explicate the purpose of a model clearly and to communicate it.
Indeterminacy of Model Building Question and Model Boundaries
Whenamodelingprocessconcernsaninnovation,theinitialformulationofthemodelingproblemis
oftenvagueandindeterminate,whichmeansthattheproblemlacksadefiniteformulation.Ontopof
that,evenitsconditionsandlimitsmaybeunclear(Buchanan1992,p.16).Indeterminateproblems
have a structure that lacks definition and delineation. Herbert Simon (1973) calls these kinds of
problems“illstructured.”Attheoutsetoftheproblemsolvingprocess,anill-structuredproblemhas
unknown means and ends. Often, modeling problems are ill structured to such an extent that they
become “wicked problems” (Rittel and Webber 1973). Wicked problems have incomplete, contra-
dictory, changing, and often even hardly recognizable requirements. Through interactions with the
client and within the modeling team, these problems usually become better structured over time.
Usually, however, they may leave open many acceptable solutions. This may be due to partial
knowledgeorunderstandingofthemodelrequirements.Itmayalsobeduetotheunderdeterminacy
of the target system when the physical laws applied do not fix the variables involved. Helping to
separate the relevant from the irrelevant aspects of the modeled phenomenon has a normative side.
Besidesweighingepistemicvaluessuchasdeterminingthereal-worldaspectsthatneedtoappearin
the model, the definition of the modeling problem also fixes the scope on the societal effects taken
intoaccount.Forinstance,traditionalthermodynamicoptimizationmodelsforrefrigeratorcoolants
favored Freon-12 because it is stable, energy efficient, and nonflammable (in the volumes used).
10TheexamplesinthissectioncomefromparticipatoryresearchreportedmoreindetailinZwartetal.(2013).
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HandbookofEthics,Values,andTechnologicalDesign
DOI10.1007/978-94-007-6994-6_1-1
#SpringerScience+BusinessMediaDordrecht2014
Fig.1 ModelofchemicalconversionatsteadystatedeterminedbytemperatureTandvolumeV
Whenthemodelincludessustainability,however,thiscoolantlosesitsattractivenessbecauseofits
propensitytodepletetheozonelayer.In1996,theUSAbanneditsmanufacturetomeettheMontreal
Protocol.
Interestingly,questionsaboutvaluesstillariseevenatthestageinwhichthemodelingsituationis
determined and the model can sufficiently accurately describe the behavior of the fixed target
system. The following simplified example shows how a seemingly straightforward application of
amassbalancerelatestosocietalnormsandvalues.Inmost(bio)chemicalprocesses,thegoalofthe
processdesignistheconversionofonesubstanceintoanother.Usually,thedesignrequirementsfix
the product mass flux, i.e., how much substance is to be produced in a given time span. Let us for
simplicity’s sake assume that the conversion rate of a reactor is 100 % and that conversion only
depends onthe reactor volume (V) and the reaction temperature (T).The steady-state mass balance
of the reactor then can be modeled as is depicted in Fig. 1. Under these circumstances, clearly the
modeledsystemisunderdeterminedandthedesignteamisfreetochoosethereactorvolumeorthe
reaction temperature.
Despite its simplicity, the conversion case already raises interesting questions about societal
consequences and thusvalue-ladenness.Although themodelingchoiceofvolume and temperature
is seemingly a factual affair, their trade-off has considerable derivatively value-laden implications.
The larger the reactor, the larger the volume of the contained substance; the larger the possible
amountofpossiblyspilledsubstanceincaseofleakagesorothercalamities,thelargerthevolumeof
substancesmanagedduringtheshutdownandstart-upoftheplant.Moreover,extremelyhighorlow
temperatures can cause major hazards to operators and provide sustainability issues due to high
energy requirements. Thus, fixing the temperature-volume region has societal implications regard-
ingenvironmentalissues,safety,andsustainabilityhazards.Doesthisvalidatetheassertionthatthe
flux model is value-laden, or should the responsibility for these value-related issues be exclusively
put at the feed of the designers of the reactor – provided they are not the same persons?
Answeringthatsomemodelisonlyasetofequationswillnotdo.Followingourcharacterizations
ofamathematicalmodel,thelastincludesrulesofinterpretationandthereforeismorethanjustaset
ofmathematicalequations.Nevertheless,thefluxmodeldoesnotexplicitlyembedavaluejudgment
because it is silent about what combinations of volumes and temperatures are preferable. Quite the
contrary,themodelrefrainsfromanydirectvaluejudgmentandonlydescribestherelationbetween
the variables within some margins of error, and the only value involved is the model’s accuracy.
However, the representation of the situation as only a physical relation between variables without
safetyandsustainabilityconsiderationsalreadyimpliesanevaluativestance.Themodelcouldhave
incorporated information about unsafe volumes and energy consumption. Thus, the choice of the
model’s constitutive parts and the absence of reasonable upper and lower limits render the model
value-laden in the derivative sense. The absence of societal aspect reflects the modelers’ judgment
that they are not important enough to be considered. From the present considerations, we may
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