Assessing the value, ethical implications, and impact of innovation

This chapter will discuss research that aims at assessing the value and possible impact of innovations. Particularly the way ethical values can be assessed will be discussed. As in Chapter 1, a reductionist approach will be avoided. Reducing ethics to consequences seems to be attractive, as consequences are mostly (at least partially) researchable. But that approach overlooks values that cannot be captured in consequences, and for those values, virtue and duty ethics have to come into the picture. Technology assessment as a widely used research approach for investigating possible consequences of innovations for the sake of innovation management will be discussed in this light.

Assessment as a responsibility in product innovation management

In this chapter, the assessment of proposed product designs will be discussed. This will be done in the broader context of the assessment of technologies for the sake of policy making. Before deciding about the various options for a new product, an assessment is desirable of the possible impact that the design will have. The scope of this assessment can be limited to the expected market position of the new product, but that is a rather narrow approach. The product will do much more than just be sold and bought. It may have an impact on social relations, national economies, globalization, the natural environment, and other aspects of life. Ideally a broad assessment is set up, of which the outcomes can still affect the product innovation management. It may lead to sophisticated choices between alternative designs or production processes, changes in the design, and certain market strategies. In a certain way, this can be seen as a social responsibility of the company. For this, the term Socially Responsible Innovation (SRI) has been introduced. The abbreviation SRI is also used for Socially

Responsible Investment, but that is much narrower than the topic of this chapter. SRI requires a multidimensional approach to innovation management in which scientific-technological and socio-economic issues are included (Flipse et al. 2014), and also, it cannot be a matter of industrial companies only but also entails political involvement (Rip, 2018). SRI brings us in the realm of ethics. In this chapter, an ethics that goes beyond risks and, in general, consequences will be proposed. Although a focus on consequences is attractive because consequences can be predicted through research to some extent, there are other relevant ethical concerns that need to be raised, related to more fundamental questions about what is morally permissible and what is to be rejected morally.

Technology assessment: forms and limitations

Although the term ‘technology assessment’ originates from a governmental context, this type of study is also relevant for product innovation management. It entails a systematic study into possible impacts of a new technological development. It usually has a broad scope and encompasses all sorts of impacts: on employment, economy, social relations, and the natural environment. It uses methods such as trend analysis and impact trees - methods that aim at investigating the future, based on the past and the present. Just like any other method, it has assumptions that need to be fulfilled in order for the method to yield reliable outcomes (see also Chapter 5). In this section, a distinction will be discussed that is rarely taken into account in current literature, yet is very important for a proper appreciation of what technology assessment can and cannot do. To explain it, we turn again to the aspects of reality that were introduced in Chapter 2, Section 2.2). In these aspects, two types of regularities (or ‘laws’) can be distinguished: ‘natural’ regularities and intentional regularities. The natural regularities are found in the ‘lower’ aspects (the numerical, spatial, kinematic, physical, and biotic). These regularities are studied in disciplines such as mathematics, physics, chemistry, and biology. These regularities do not depend on human intentionality. The actual number of parts a machine has does not depend on who counts them and with what purpose. The same holds for the space the machine occupies, the force it exerts on the factory floor, and the chemical properties of the materials it is made of. Similarly, the natural regularities of living organisms (such as cell behavior) also do not depend on the intentionality of the living being. I cannot influence the functioning of my cells. I can do things that make my heartbeat go up, but I cannot influence the mechanism through which that happens. These regularities have a high level of consistency and therefore allow for relatively accurate predictions. When I drop a screwdriver from a certain height, the laws of physics allow me to give a fairly accurate estimation of how long it will take for the screwdriver to hit the ground and with what force. In technology assessment, these regularities form part of the basis for trend analyses and impact trees. When we know current parameters and the change we have put into motion, these natural ‘laws’ allow us to predict the future, assuming that there will be no unexpected new parameters emerging. We happily use the fact that natural phenomena ‘behave’ in a strictly orderly way.

This is less the case with regularities that are based on phenomena in which human intentionality plays a role. Intentionality is a philosophical term that indicates not just intentions (purposes) but also attitudes, knowledge, emotions, efficacy, and the like. This sort of phenomena can be found in the ‘higher’ aspects. The ‘laws’ of psychology are not as absolute as those of physics, as people’s behavior is not as regular as nature’s behavior is. In psychology, models for relations between attitudes and behavior are developed, for instance. But such models cannot claim that the relations are absolute. Sometimes people let attitudes determine their behavior to a large extent, but sometimes people behave inconsistent and do things that go against their attitudes. 1 can have a very negative attitude toward smoking and yet be a stubborn smoker. This means that psychologists can do research that leads to expectations about customer behavior and later it can appear that customers do not behave according to the ‘laws’ that were found in psychology. The same holds for economy. That is why it is so difficult to predict the behavior of stock exchanges. Sometimes people panic and behave irrationally and do not act as could be expected from economic theories and models. Yet, technology assessment also depends on these kinds of regularities. It is important that the predictive value of different parts of a technology assessment is carefully evaluated by analyzing the type of regularities that were used. Predictions based on natural regularities can ascribe a high level of reliability, but predictions based on intentional regularities should be seen as much less accurate and certain.

The predictive value of technology assessment studies should also be evaluated against the knowledge of the factors that may have an impact on developments. This knowledge is never complete, but particularly in the early stages of a development it is difficult to establish which factors need to be taken into account (and about which regularities are known already or yet to be found). Unfortunately, this is

Value, implications & impact of innovation 55 also the period in which the decisions made, based on the outcomes of a technology assessment study, have the largest impact. As time goes on, it becomes more and more evident which factors are at stake. But also, the development goes on and the impact of decisions on the development becomes increasingly marginal. In technology assessment literature, this is called the Collingridge dilemma: either one makes decisions early on and they will have a great impact but are based on limited knowledge, or one waits until later when more knowledge is available but decisions have less impact as the technology has already taken shape and position. It is clear that the value of Collingridge’s theory is limited in that it does not give clues about how to deal with this dilemma and therefore more is needed to deal wisely with this dilemma (Genus and Stirling, 2018). In Section 7.4, the need to complement the focus on impacts and consequences with other approaches in ethics will be spelled out as an answer to that need.

 
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