Responsibility Reliability Trust Liability Trustworthy Concept Responsible Research

Research can be more responsible with the right partner

Drivers and impacts of RRI in EU-funded projects identified

This week, the Go4 Conference in Brussels will discuss the findings of several research projects focused on Responsible Research and Innovation (RRI). RRI is one of the underlying cross-cutting issues of the Horizon 2020 Framework Programme defined by the European Commission. The idea is to better align both the research and innovation process and its outcomes with the values, needs, and expectations of society. During the conference, the GREAT project will reveal the results of its investigation of the factors influencing the uptake of responsible research aspects in EU-funded research and innovation using an agent-based simulation approach. Results concerning the involvement of Civil Society Organisations (CSOs) are not as expected.

Societial interface with research

Societal actors—such as researchers, citizens, policy makers, businesses, and third sector organisations—need to work together during the whole research and innovation process. Specifically, RRI literature and EC policy papers have identified a strong pattern suggesting that CSOs are crucial to realising the ‘societal perspective’—or RRI aspects—in current research and innovation processes. Therefore, policy programmes try to foster their participation and inclusion.

In contrast, our own empirical work outlined below strongly questions this previously identified pattern. In the GREAT project, we identified the current implementation degree of RRI aspects at the organisational and project level. For this, we focused on a particular funding scheme under the 2007-2013 Competitiveness and Innovation Programme of the European Commission (CIP) using data on 213 funded projects under the Information and Communication Technologies Policy Support Programme of the CIP (CIP-ICT/PSP). The particular relevance of this programme consists in its aim to increase the global competitiveness of the European Union by addressing “societal challenges”. Typical challenges addressed are the provision of sufficient healthcare for the EU’s ageing population, protecting the environment by improving energy efficiency, and providing more inclusive and efficient public services.

Results showed that CSOs participate in more than 50% of the CIP-ICT/PSP projects due to their specific content-related expertise and due to their good access to important data. They are the more influential the less these contributions are provided by other consortium partners. Only 19% of all projects report that CSOs participate to contribute general societal perspectives or ethical aspects. Project coordinators even claim that universities and Small and Medium Enterprises (SMEs) are the most active partners in promoting RRI functions within consortia. Summarising, the role of CSOs in realising and implementing RRI functions seems to be much less central than previously assumed.

There might be a good explanation for the phenomenon that other organisations than CSOs are major drivers of RRI: EU funding programmes and calls (FP6, FP7 and Horizon2020) have long required the integration of societal and ethical aspects in research and innovation. They also promote the inclusion of heterogeneous actors in projects to ensure multiple perspectives. Only proposals, and proposal consortia, which fulfil these requirements, are awarded with research grants. This means that policy and incentive structures generally postulate and foster RRI among all research associates.

It can be safely assumed that all research actors–especially universities and research organisations, but also big and small firms–have adapted to this requirement landscape, and that “learning” has taken place on a big scale among these actors. In the meantime, RRI competence belongs to the standard profile of most of the organisations participating in EU research. Last but not least, RRI competence “diffuses” in projects among consortium partners. Partners without any track record in RRI learn in projects. This means that RRI competence diffuses and grows in the research and innovation landscape by multiple participations of organisations in different projects.

These explanations for our empirical findings are plausible but difficult to check. They rely on so-called empirical “un-observables”, which are difficult to observe and to measure: knowledge stocks (RRI capabilities), knowledge flows, and RRI learning. This is a typical application area for agent-based simulation.

Agent-Based Simulation

In our agent-based model GREAT-SKIN, which is based on the SKIN simulation platform, agents represent all the actors of the research and innovation process such as universities, research centres, small and medium enterprises, large multinational corporations, and CSOs. These agents exhibit the behaviour and interaction of actors in the EU-funded research and innovation system. The model is informed by empirical data to make it as realistic as possible. In the case of GREAT-SKIN, the model was calibrated with empirical data from the CIP-ICT/PSP funding scheme.

Our model encompasses the following aspects of RRI elements: 1) anticipation—the agents’ and projects’ ability to anticipate the consequences of research and innovation for society— 2) reflection—the agents’ and projects’ suitability to address the requirements of the funding call— 3) participation—mirrors the requirement for RRI-sensitive agents such as CSOs to be matched by the actual funded projects— and 4) responsiveness—reflects the degree of strategy change during the projects. Each project participant is allocated a score for each of these aspects, leading to an RRI score of each organisation, and for each research project.

This agent-based model makes it possible to check for aspects of RRI dynamics, which cannot be observed empirically. Thanks to simulations, we could observe and measure the “RRI capabilities” of various agent types and their ability to perform “RRI learning” or to exchange RRI-related knowledge between them.

Our simulation model is a computational representation of how research and innovation takes place in EU-funded projects. Relying on this model, we first set out to evaluate whether CSOs are the main facilitators of RRI among project participants. We also examined whether CSOs are chiefly responsible for the “spread” of RRI in the research and innovation system via the paths we labelled RRI learning among actors and RRI diffusion in the system. For this, we changed the level of CSOs involvement in various projects.

First, we experimented with a scenario where there are “No CSOs”, or only a dramatically reduced number of them. It showed that the number, identity and role of CSOs are not critical to the simulation outcomes.

In another experiment, dubbed the “Attractive CSOs Experiment”, we gave the initial CSOs more or less material expertise in scientific fields: it tested and confirmed our hypothesis that CSOs are considered as attractive partners in projects not only as society representatives, but also – and sometimes rather – for their domain and knowledge expertise in specific areas of research. The experiment provided causal insights and measurable effects for this.

Finally, the so-called “Hybrid CSOs Experiment”, which played around with different balances between scientific capabilities and RRI capabilities provided more detail on the diffusion patterns of RRI: it showed that special RRI capabilities of CSOs are increasingly adopted and then contributed by other agent types, and via the same learning mechanisms, CSOs increasingly adopt and then contribute scientific capabilities.

With these results, our study contributed to the analysis of the RRI-led turn to co-creation, transdisciplinary and transformative science in European research and innovation. It especially sheds light on the role and involvement of Civil Society Organisations, which were expected to change the research and innovation system towards RRI functions. Instead, we found that it was the capability of any of the project participants to do research responsibly which is paramount. Further research is necessary to help describe how to best make organisations involved in research behave more responsibly.

Petra Ahrweiler

Petra is the Director of the EA European Academy of Technology and Innovation Assessment in Bad Neuenahr-Ahrweiler, Germany, which is a partner of the GREAT Project.

Featured image credit: via Sutterstock

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