Discourses and metaphors
Co-producing knowledge and RRI in emerging fields | Ryuma Shineha
I conduct trials of real-time technology assessment on emerging sciences (e.g. stem cell science and molecular robotics) as a form of RRI. By examining a number of sociotechnical imaginaries through media analysis and horizon scanning, this study helps us to understand how particular imaginaries relating to emerging sciences become dominant in society. I also explore ways of managing communication among various stakeholders, including not only scientists and engineers but also journalists, policymakers, and the public, and extract lessons for planning education and developing guidelines for RRI.
Temporalities and histories
Where science communication and RRI meet | Erika Szymanski
Science communication is sometimes linked to responsible research—beyond having a responsibility to communicate beyond disciplinary confines, the principle of ‘responsible language use’ would have scientists think about possible interpretations across wider audiences when they choose terminology such as ‘gene editing.’ More fundamentally, however, because scientific knowledge is constructed in language, the words—the discourse tools—that scientists employ shape the possible uses of science and how scientific knowledge participates in value- and power-laden relationships in social contexts. In my work, I suggest understanding science communication as intrinsically connected to RRI via, for example, reflecting on ‘debugging’ and other metaphors for engineering biology—asking not what language is most accurate, but what language enacts the future we want to bring about.
Temporalities and histories
RRI ‘in the wild’ | Koichi Mikami
My research explores a historical case of multi-stakeholder collaboration, which resulted in an important health policy in Japan, namely the program of newborn mass screening. As the case took place long before the notion of RRI was coined, I consider it as an exemplar of RRI ‘in the wild’, which could help us assess what roles, if any, social scientists can play in making RRI happen in the present and the future.
Boundary work of risk and responsibility | Ken Kawamura
My research focuses on the emerging technology of molecular robotics (molbot) and how the experts in the field talk about the assumed risks. By examining their vocabularies, rhetorical devices, and arguments, I aim to shed light on the way the molbot experts draw boundaries around the “intrinsic” risk of the technology, and thus clarify whether and how arguments on the social responsibility of science, which still retain an influence on today’s RRI discussions, have reflexively shaped the perspectives of scientists.
Holding key moments open | Robert Smith
In the UK the cycle is familiar: A new technology, a new need for a roadmap, and a new need for public discussion of it. Since the turn of the century a lot of energy has been spent on creating ‘upstream engagements’ that provide an opportunity for scientists, social scientists and various public groups to discuss. Despite their prevalence, there is scant evidence that such discussions actually create more ‘responsible’ innovations that are somehow better aligned with diverse notions of public value and produce more evenly distributed benefits than is the norm. The social studies of science can help here because they illustrate how science, technology and society co-evolve in uneven and skewed ways. One example of this skewed development, particular ‘compressed moments’ resonate over time because they set important precedents, create standards or build infrastructure. In these moments there are often forces that close down debate and discussion. I would like to find these spaces and generate methods to ‘hold them open’.
Locating ‘responsibility’ in artificial intelligence | Robin Williams
Artificial intelligence (AI) is not a technology—it is a journey. This makes it hard to apply traditional conceptions of RRI derived, for example, from synthetic biology or nanotechnology, because AI is a matter of incremental change through which adaptive systems may gradually become adopted, contested, and eventually taken for granted. Consequently, downstream assessment and governance of AI applications is more important and upstream governance less critical. For AI, ‘responsibility’ means addressing not just AI-based tools, but the extensive information infrastructures in which they are implicated.
Limits to social responsibility | Steve Sturdy
In relation to biomedicine, RRI is commonly seen as a means of correcting shortcomings in longer-established areas of medical ethics. These are, in particular: the tendency of ethical perspectives to focus on responsibility towards individuals rather than to society more widely; and the tendency to locate responsibility downstream, by privileging individual choice over whether to engage with the end products of medical research, rather than upstream, by fostering wider societal influence over the direction of medical research. RRI seeks in principle to correct these shortcomings by involving publics, in one guise or another, in steering research investment and research priorities. In practice, however, it remains unclear just how far public engagement and involvement alone are able to achieve social responsibility. Work on RRI needs to pay more attention to the wider political forces and configurations driving research and innovation, which may often also be influential in shaping public attitudes and opinions. And it needs to give more thought to how researchers themselves should take responsibility for the research and innovation in which they are involved.
Questioning the idea of responsibility | Yuko Fujigaki
My research questions the idea of ‘responsibility’: how the history of the word differs in the U.K. and Japan; what differences (and similarities) exist in how the word is used by physicists, biologists, and AI researchers; whether responsibilities are used differently in emerging fields such as AI, synbio, or genetic medicine in comparison to established fields such as nuclear energy, for example. Questions such as these should allow us to explore the multiplicity of the idea in different contexts while at the same time highlighting some common features.
Developing ethical and legal policy for genomic research | Jusaku Minari
With the dramatic development of genome sequencing technologies, it is now possible for researchers to handle genome information on a large scale without difficulty. As a result, the nature of the use of genomic information is being questioned internationally in genomic research. I aim to explore how ethical and legal policies regarding the handling of genomic data in research can be formulated so that they serve for both the objectives of science and the ethical and legal protection of research subjects.
Taking responsibility for hegemonies | Pablo Schyfter
A hegemony is a privileged ideal used to evaluate the correctness of social phenomena—a portrait of what a field should be and what its practitioners should do, for example. In synthetic biology, ‘rationality’ is a hegemonic ideal differentiating the field’s aspirations of systematic and predictable planning and fabrication of biology technologies from previous forms of genetic engineering. As a hegemonic ideal, ‘rationality’ also establishes distributions of worth, power and authority that privilege some people and undermine others. Concern for hegemonies is one form of practitioners being responsible to each other: people are responsible for the hegemonies that they install and follow; people should take responsibility for their ramifications; and people should be held responsible when those ramifications are detrimental.
Environmental choreographies | Niki Vermeulen
Based on explorations of scientific collaboration in the life sciences, I focus on the ways in which the build environment stimulates interaction between different actors, including (social) scientists, policy makers and publics. What are sites of interaction? How are they designed and what types of choreographies do they allow and construct? My work contributes to organizational aspects of research, focusing on interaction between epistemic, social and material dimensions. In the context of RRI frameworks, this generates reflections on ‘responsible’ environments for research and innovation.
Alternatives and interventions
Restructuring the built environment | Go Yoshizawa
My research focuses on modelling and environmental restructuring as under-addressed areas of behaviour change interventions in public engagement with science. Mobilizing human and non-human actors around these topics would not only help to restructure the environment for public engagement and reframe what it means, but it would also allow us to explore counter-hegemonic ways of doing research and innovation and doing RRI research.
Collaborative and competitive development of responsible AI | Arisa Ema
Discussions of the ethical, legal and social implications of artificial intelligence (AI) are taking place among the government, industry, academia, and the public in Japan as well as abroad. Leading figures in the field who engage in such discussions attempt to build ‘ideal’ partnerships on AI. However, such collaborative schemes require close investigation with respect to sectors and countries involved. My research explores the boundary between issues for which collaboration is possible and can be effective and those for which it is difficult and possibly futile, based on international and interdisciplinary workshops and interviews with multiple stakeholders.
RRI as a way of keeping synthetic biology open | Jane Calvert
Social scientists have been involved in synthetic biology for over 10 years. In its early days the field provided opportunities for experimental collaborations between synthetic biologists and social scientists, artists, designers, and other ‘non-scientists’. But as synthetic biology has become more mainstream, such opportunities are becoming increasingly limited. RRI can be understood as a way of keeping these opportunities open by instigating interactions between diverse groups, which can generate alternative understandings of synthetic biology and its possible future paths.