1.1 Introduction
Responsible Research and Innovation (RRI) has gained prominence in the academic debate in the last decade. Introduced in order to provide an operational framework for enabling communication between science and society, it has undergone a consistent number of analyses to understand its value and relevance for such operation (Burget et al. 2017). However, despite this large number of attempts, clarity about its efficacy is still far from being reached. Accordingly, initial enthusiasm has started to fade in favor of alternative, more specific regulatory measures. This chapter aims to evaluate the scientific and democratic relevance of RRI beyond skepticism about the acronym, in order to understand if it can still play a role in the dialogue between science and society.
In order to do so I will operate an analysis, on the basis of a pragmatist perspective, of the main features and challenges faced by science and democracy, in order to then extract their main objectives and principles. I will then introduce the evaluation phase with a brief analysis of the concept of responsibility so to offer a theoretical background that summarizes the dynamic nature of RRI. One of the puzzling aspects of RRI is in fact the difficulty to obtain a common understanding on what responsibility means and implies. This preliminary assumption appears often fragmented or controversial, making it difficult to obtain a homogeneous approach to RRI. In a following step, I will then be able to start the evaluation of the scientific and democratic relevance of RRI. In order not to lose the conceptual power of the principles embedded in the framework, instead of concentrating on the acronym, I will focus on the six keys (engagement, gender, open access, science education, ethics, governance) adopted by the European Commission (EC), which will reasonably last even beyond RRI. It will finally emerge that RRI has a high scientific and democratic relevance.
1.2 Science and society
When it comes to RRI, one of the most intuitive doubts is about the capacity of an ethical framework to increase or at least maintain the scientific relevance of research and innovation. Scientists and innovators might still believe that a pure technical process, one apparently devoid of any extra scientific consideration, can represent an efficient methodology to make their research progress. Even amongst those who are not explicitly supporters of technological determinism, it is possible to find caution about the value of a non-technical integration into the research process, at least at an earlier stage.
It would be hard to affirm that technology, and science more generally, does not have an impact on societies.1 The intuition of PoincarĂ©, demonstrated only much later by Edward Lorenz, that an infinitesimal variation has potentially infinite sets of consequences, has nowadays become evident also to non-specialists (Jasanoff 2016; Lorenz 1963; Turing 1950).2 Besides, studies on complexity have demonstrated how linear models are not apt to explain effects springing from systems behavior (Bridgman 1927). The âbutterfly effectâ is exactly what poses scientists with challenges that are not only technical, but ethical and, in the end, political.
It is difficult not to recognize that current societies and thus scientific research are complex and have to deal with a growing âhyper-complexityâ (Qvortrup 2003). According to Funtowicz and Ravetz (1993), science is now developed in a âpost-normalâ scenario. For Gorgoni (2018), the intensification of consequences in terms of both time and space has shifted foresight exercises from dealing with uncertainty to navigating in indeterminacy. The transition from a curiosity-driven method to a problem-oriented one, where knowledge and decisions are not detachable, together with the growth of complexity, has made it difficult to exclude values and interests from scientific research (Arnaldi & Bianchi 2016; Funtowicz & Ravetz 2008; Jasanoff 2004).
Following this path, some authors have pointed out that science not only has an indirect and unforeseeable impact on society, but is also a sociopolitical construct. Accordingly, the objectives of scientific research, or rather their topics, are always decided according to political decisions although these are often implicit (Jasanoff 2004, 2016; Wynne 1993).
From a more radical point of view, the relation between nature and society is a coproduction, determining that our representations are inseparable from the ways in which we live (Pellizzoni 2004).
Many authors have justified the necessity to include extra-technical aspects by enumerating recent cases that have generated outrage in public opinion. They have shown the potentially severe consequences that could occur when neglecting a broader perspective in the choice of scientific paths. Several negative examples, like genetically modified organisms, or other episodes connected to chemicals, have shown the limits of adopting a purely quantitative methodology for assessing the impact of a research product (Jasanoff 2016; Von Schomberg 2013, 2014). Besides, many of these events suggest that consequences are often considered to be bad not only in terms of safety, but according to hybrid, dynamic and sociotechnical aspects (Jasanoff 2016). The risks stemming from the bureaucratization of thought and the supremacy of technique over politics urge us to focus on humanistic and social ends (Horkheimer & Adorno 2002).
Technology and science more generally are artifacts that confront humans with new challenges and possibilities. Emerging technologies like artificial intelligence, genomics or synthetic biology are fascinating gamechangers in the future of humanity.3 However, Dewey reminds us that scientific artifacts are not simply there in some kind of naturalistic or deterministic fashion; they are the results of interactions â socially conditioned phenomena resulting from accumulated culture (Dewey 1991, Ch. 3). To paraphrase the American philosopher, we do not naturally need them, but we want them (p. 106). Therefore, also the assessment of emerging technologies becomes more complex and needs to take into account a broader ârange of values that humans care about when contemplating the futureâ (Jasanoff 2016, p. 58). Also for Funtowicz and Ravetz (1993), in a situation of post-normal science, and in order to deal with the major challenges arising in our societies, the epistemic dimension should be integrated with an axiological one, meaning that values should complement technical aspects.
Apart from the easily understandable reactions to negative episodes, though, it is important to put in evidence that science has a proactive power in increasing the well-being of humankind. In a recent analysis, Jasanoff has stated that technologies, as the current focus of science, are âdevices with which modern societies explore and create potentially more liberating and meaningful designs for future livingâ (Jasanoff 2016, p. 242). In this respect, there is a growing amount of literature and evidence about the advantages of the integration of broader perspectives into science. Extending knowledge can bring benefits to scientific investigations because it increases the possibility of solving problems by including additional and new information (Pellizzoni 2004; Stilgoe et al. 2013). Although, as pointed out by Blok and Lemmens (2015), transparency claims can be seen as highly naĂŻve or counterproductive (Blok 2018), it is also true that external information can but enrich the general level of knowledge needed to progress in scientific research and innovation.
It has been noticed that scientific research has consistently turned to a contextualization of knowledge production (Nowotny 2015; Pavie et al. 2014) which is often aimed at the âcreation of wealthâ (Krishna 2013). In this sense, although basic research still plays a prominent and prestigious role, we do witness a proliferation of small-scale laboratories and research group targeting specific, and often already existing, problems. This is probably due also to the fact that technologies mutate along with the societies in which they operate (Jasanoff 2016). Therefore, it has been shown that successful technologies are often those that adapt and respond to particular needs (Bijker et al. 1987).
A connected reason is the change in the production process, economic growth and the consequent advantages of a âproductiveâ research and innovation process (Godin 2015). According to Blok and Lemmens, âmost innovations take place in commercial or industrial settingsâ and products need to be profitable (Blok & Lemmens 2015, p. 20). Also research increasingly faces challenges arising from the necessity of meeting criteria of excellence that can be measured and that can produce growth. However, Mazzuccato has reminded us that, although this is easily overlooked, private successes often have public origins and therefore researchers and innovators should deal with these political origins (Mazzuccato 2015). What she points out is that often science (and innovation) cannot be totally implemented without a whole series of other inputs and measures often generated by institutional mechanisms, which then raise the question of the criteria for decision-making. The question of âframingâ of research trajectory appears for many scholars to be inextricable from the ontology of products and processes (Gianni & Goujon 2018; Goffman 1974; Maesschalck 2017).
If we recap the different aspects of the question, we can see that nowadays science has to deal with an increasingly growing complexity, which requires innovative, experimental and broader methodologies. This has been practically urged by negative happenings, but also the potential advantages are seen as highly relevant.
The ways in which to implement such broadening are mostly targeting participation and deliberative processes in the wake of democratic models (Guston 2001). Although it might be argued that more innovative and bottom-up instruments are needed (Bucchi & Neresini 2008; Flipse 2012; Gottweis 2008; Pansera & Owen 2018), the aim is nevertheless to establish a discussion with a sufficiently extended range of different perspectives, which can then feed the trajectory of science research. The relevance of different angles concerns the quantity of agents potentially affected by the outcomes, as well as the whole âworlds of relevanceâ of the actors considered (Arnaldi & Bianchi 2016; Jasanoff 2016; Limoges 1993), and their influence in the decision-making process (Fung 2006; Gianni & Goujon 2018). The necessity to enlarge perspectives towards narratives is considered to be important to not reduce the inputs in the discussion to ârationalisticâ ones, which would fall back into the same limited epistemic framework that they are supposed to abandon (Dewey 1991 [1927]; Funtowicz & Ravetz 1993; Ricoeur 2000; Wynn1993). However, it has been highlighted that the competence of participants to express their interests is also crucial. This means that they have to be able to adopt a mature view in order to be able to fully understand some of the technical aspects in question (Kitcher 2011). Furthermore, participants should be willing to accept a common set of rules for deliberating (Bohman & Regh 1997; Fishkin & Laslett 2003; Hajer & Wagenaar 2003; Reber 2016). This last indication highlights the necessity to promote bilateral relations between science and democracy. If the former is called to open the discussion on the overall objectives because of endemic and epidemic reasons, the tools pertaining to the latter should also be deployed with a greater scientific attitude.
