Abstract
This chapter discusses a methodological problem that advocates of design for values have to face. In order to take into account moral values in designing technology, these values have to be operationalized or made measureable; otherwise it will not be possible to evaluate various design options with regard to these values. A comparison of the operationalization of values with the operationalization of physical concepts shows that certain conditions that enable the operationalization of physical concepts in objective measurement procedures are not fulfilled for the operationalization of values. The most significant difference is that physical concepts are embedded in networks of well-tested theories and operational procedures, which is not the case for moral values. We argue that because of this second-order value judgments play a crucial role in the operationalization of values and that these value judgments seriously undermine any claim that values may be measured in an objective way. The absence of objective measurement of values, however, does not imply that the operationalization and measurement of values in design is arbitrary. In our opinion technical codes and standards may play a major role in coming to a reasonable or justified consensus on how to operationalize and measure moral values in design.
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Notes
- 1.
See, for instance, Sayre-McCord (2011).
- 2.
Here we have to point out an important caveat. If the overall moral goodness of a design option is not directly measurable but is the aggregated result of the assessment of that design option on various criteria each of which is separately objectively measurable, then in general it will not be possible to compare various design options with regard to their overall moral goodness. In that case the notion of the morally best design option makes no sense. This is due to issues in multiple criteria analysis (see below). What we have in mind here is the assessment of various designs against a “monolithic” moral criterion, that is, a criterion that is not itself the aggregated result of multiple measurable sub-criteria and that may be directly measured in an objective way.
- 3.
Note that the fact that a value is pursued for its own sake does not exclude that it may also be pursued for other reasons.
- 4.
Of course, it is possible to correct for systematic errors of measuring devices such that the corrected outcome is determined only by features of the object(s) on which the measurement is performed (for instance, one may correct the outcome of a measurement with scales for the fact that the arms of the scales are not of the same length). In our opinion, however, we are then dealing with two different kinds of measurement methods, the original one and one with a correction procedure.
- 5.
For an interesting discussion of the notion of transparency of experimental equipment, including measurement devices, see Lelas (1993).
- 6.
- 7.
- 8.
- 9.
In the literature accuracy is often taken to be part of the notion of validity; see, for instance, Carmines and Zeller (1979). Conceptually, however, a distinction can be made between the questions whether a measurement method measures the intended quantity (e.g., temperature) of the system under consideration or not and if so, how accurate the measurement method is. That is the reason why we prefer to distinguish between validity and accuracy. In specific cases, however, it may be difficult to distinguish between accuracy and construct validity (see below for the notion of construct validity). Consider the case in which someone tries to measure the temperature of a liquid with a mercury thermometer. Suppose that the amount of heat transferred from the liquid to the tip of the thermometer is small compared to the total amount of heat in the liquid. Then, the smaller the heat transfer from the liquid to the tip of thermometer is, the more accurate the measurement will be. But now suppose that the amount of heat transferred becomes more or less equal to or less than the amount of heat in the liquid (e.g., someone tries to measure the temperature of a drop of water with an ordinary mercury thermometer). Then the measurement becomes less accurate or even construct invalid, for in the extreme case of a very small amount of liquid compared to the mercury in the tip of the thermometer, one no longer measures the temperature of the drop of liquid but of the ambient temperature in which the thermometer is kept. This example shows that under certain conditions, very inaccurate measurements may become construct invalid.
- 10.
Reproducibility does not mean that if the measurement is repeated by the same person, exactly the same result will come out. Due to (random) measurement errors, the outcomes will be distributed according to a certain probability function. Reproducibility requires that this probability function over the outcomes is the same when the measurement is performed by another person.
- 11.
They speak of objectives but these are similar to what we call evaluation criteria.
- 12.
Note that, similar to second-order value judgments in the case of the operationalization of values, second-order epistemic value judgments are important in the operationalization of physical concepts. In general, however, these second-order epistemic value judgments appear not to undermine the construct validity of measurement procedures for physical concepts; we will not enter here into a discussion of why this is the case.
- 13.
At least reproducibility and accuracy are not fundamentally more problematic than in the case of physical quantities because the attributes are, at least in this case, all physical quantities. It may not always be possible to operationalize values in terms of physical quantities, and in such cases reproducibility and accuracy are more of an issue. But even, then, we would argue the real issue is validity.
- 14.
ASHRAE is American Society of Heating, Refrigerating and Air-Conditioning Engineers; ANSI is American National Standards Institute.
- 15.
We leave in the middle here when a consensus is justified, but one might think here of John Rawls’ idea of an overlapping consensus (Rawls 2001).
- 16.
See the chapter “Conflicting Values in Design for Values” for a detailed description of this multi-criteria problem for choosing the morally best design option.
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Acknowledgments
We thank Maarten Franssen for valuable comments on an earlier version of this chapter.
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Kroes, P., van de Poel, I. (2015). Design for Values and the Definition , Specification , and Operationalization of Values. In: van den Hoven, J., Vermaas, P., van de Poel, I. (eds) Handbook of Ethics, Values, and Technological Design. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6970-0_11
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