Community Research and Development Information Service - CORDIS

FP7

GREAT Report Summary

Project ID: 321480
Funded under: FP7-SIS
Country: Belgium

Final Report Summary - GREAT (Governance of REsponsible innovATion)

Executive Summary:
The GREAT project has investigated on which grounds responsible research and innovation can and should be understood with respect to research and innovation activities. This has been researched by conceptualising responsible innovation in the overall theory of research governance. Three main methodologies have been adopted in order to achieve such a result. A theoretical analysis of the concept of responsibility together with its understanding in current theories has been undertaken, showing the main common features, their weaknesses, strong aspects and, most of all, their underlying premises. The mapping of the theoretical landscape of research governance has generated a grid of analysis adopted as a tool for analysing examples of research with a special focus on ICTs.
The analytical grid has been applied to a variety of empirical data gathered through a qualitative social science approach (mixed methods) geared towards grounded theory.
The case study approach, focus groups, document analysis, workshops and interviews have proven to be a fundamental methodology for understanding existing perceptions and practices in research and innovation processes, and to validate and improve the analytical grid.
Another methodology adopted by the GREAT Project is agent-based simulation, which managed to apply GREAT’s presuppositions concerning the RRI categories suggested in the project and discovered through the empirical work. Simulations conducted with the GREAT-SKIN simulation model experimented with policies for implementing responsible innovation strategies in research, and evaluated future scenarios.
This interdisciplinary and complementary methodological path has led to the proposition of a model of RRI useful for policy-makers, research organizations and CSOs, in their various forms. Such a model is based on a deliberative approach to participation focused on unveiling the institutional conditions underlying research and innovation practices through a second-order reflexivity (as opposed to a first-order reflexivity, which is focused on the contents of the decision making processes themselves). Several potential practical tools are indicated as a means to promote, and eventually achieve, such a reflexive stance without the ambition of exhausting all the possibilities that could, and surely will, be developed in the future. However, the GREAT Consortium believes that its model will itself generate new tools and practices contributing to the implementation of ethical practices, boosting the economy without endangering social and sustainable development.
This model has also been translated into simple and clear guidelines that draw on the work of GREAT and beyond. This resulted in a usable and practical handbook of guidelines to facilitate the understanding and adoption of RRI principles for researchers and those involved in all aspects of research and innovation. The guidelines provide an accessible starting point for both academic and non-academic researchers to reflect on and address the issues of RRI in their own discipline. The handbook was devised to be clear, concise and easily navigable, to encourage engagement with RRI in a way that is seen as neither prescriptive nor overly burdensome.
Project Context and Objectives:
Context

The EU Commission has recently adopted the concept of responsibility in order to steer research and most of all, the new economic imperative: innovation. Responsible Research and Innovation represents the conceptual reference point for sustaining research, boosting innovation and re-launching the economic activities of Europe in a new more sustainable manner. Research has often been conceived as a separate domain following technical rules, and in need of freedom from normative constraints. However, as emphasized by several authors, research would not be possible without the community in which is embedded. “Not only do social and political forces affect the directions of research, science itself also affects greatly societal developments. The impact of science, now extending to nearly all fields of knowledge and its applications, has contributed immensely to society, even though its results can be and have been misused at times” (The EU Code of Conduct for Research Integrity, 2011). The optimism in this statement is counterbalanced by scientific positions stating the emergency scenario produced by the misuses of research results, and by a general perception of threat stemming especially from the development of new technologies. Independently from the perspective we want to adopt, research has shown to have a string connection and impact on societal dynamics changing the common way of interactions.

Innovation is a concept that has been promoted in order to meet several grand challenges. The two most important aspects grounding the necessity of innovation are connected to the over-consumption process that has led to a lack of resources and dangerous climate change. If development remains a social and economic imperative the ways in which it will be conceived and achieved need a radical change towards sustainability. The most powerful methodological tool for promoting sustainable development is to use existing resources in original manners. Accordingly the classic concept of innovation as developed by Schumpeter appears to be able to kill two birds with one stone, to face environmental challenges and to boost economic development. The latter, according to Schumpeter, “consists mostly of the different employment of existing resources, in doing new things with them, without considering if these resources have increased or not” (Schumpeter, The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest and the Business Cycle, translated from the German by Redvers Opie, Transaction Publishers, New Brunswick (U.S.A) and London (U.K.), 1934, p.70). Innovation is composed of three main aspects for Schumpeter: “a spontaneous change”, within a “dynamic theoretical apparatus” incarnated in the figure of the “entrepreneur”. Economic development and innovation coincide for Schumpeter. Innovation can invest all sorts of fields given its breadth. For Schumpeter innovation is an operation of shuffle and inter-disciplinary transposition of a “method”, a “product”, “market”, “supply source”, or “[re]organization”.
Accordingly innovation can be adopted as a methodological tool to favour economic development without endangering the sustainability of the process.

However, given the intuitive nature of innovation, the uncertainty in which research in general is always embedded (Nowotny 2015), the potential outcomes are impossible to predict in their entirety/extension. Schumpeter himself was aware of the shortcuts of this ambition: “Even with an intense preliminary work we cannot exhaustively grasp all the effects and repercussions of the plan. The length of such prevision would be theoretically impossible, according to the environment and the occasion, when we dispose of unlimited means and time, poses difficulties that are practically insurmountable” (Schumpeter, 1934 p. 83).

The same goes for research, the applications of which cannot be exactly listed. This is true not only for explicit misuses but also and especially for unattended refusal of apparently good innovations. The example of nanotechnologies or the on-going GMO debate, are only two amongst the most important ones, but several ‘smaller’ technologies have to undergo the same acceptance process.

These facts highlighted two concomitant aspects. The first one is that the consequences of R&I cannot be predicted but only imagined, and the second one is that not only the consequences as a neutral category but also the impact as an economic indicator cannot be entirely assessed. However, the more the innovation or the research is disruptive the more it will contribute to social and hopefully economic development. At the root of this scenario we then find a sort of performative contradiction where the attempt of regulating the future coincides with the necessity of disclosing unexpected possibilities.

After the crisis of 2008, with the revolutionary paradigm of innovation emerged also several limits and counter effects. Innovation needed to be supported in order to adjust its possible shortcuts. Therefore, the EU had to find ways to steer research and innovation’s development highlighting once again how their management cannot be pursued as independent from society. Something flexible enough to take in the right consideration the different claims. The concept of responsibility perfectly responded to the needs arising from society and the necessity of a reflective and considered development. Responsibility in fact has several great advantages because it embraces both a collective and individual effort; it does not require particular changes; it can be applied in different fields; and tackles the problem of sustainable development. The flexibility embedded in the concept of responsibility and its historical usages (Ewald, Ricoeur, Jonas, Beck) prove the potential role it could play in the development of research and innovation. Responsibility has at least 10 different understandings. Responsibility as: 1) cause, 2) blameworthiness, 3) liability, 4) accountability, 5) task (or role), 6) authority, 7) capacity, 8) obligation. 9) responsiveness, 10) virtue (care). Besides, responsibility can be considered an epistemic capacity, a normative framework or a reason for action. It can be conceived as an individual task or a collective effort and it can be adapted according to the intersubjective context of reference. All these different aspects contribute to make responsibility the perfect concept in order not only to defend social aspects, but also to promote research and innovation as social features.

In sum, responsible research and innovation is a notion that can in principle address the grand challenges of our time by proposing an ethical and sustainable development.

However, the flexibility that we have emphasised can also generate ambiguity and confusion. Social scientists now adopting the concept of RRI as a main grounding for the analysis and development of new processes and products often do so in a different manner, someone taking up the Commission ‘s indications some others Owen et al., and others Von Schomberg’s definition. This generates some difficulties for a European development of the notion and for its application. This is partly caused by conceptual problems, as key terms are contested. There is also a disagreement on the definition of responsibility, on the role and definition of the actors involved, and on the way in which governance can promote, foster or judge the presence of responsibility in research and innovation practices. The theoretical benefits and disadvantages of responsible research and innovation are disputed and there is a lack of empirical evidence of the effect of the integration of responsible practices.

If, on the one hand some of the current research projects adopting or developing RRI have shown discrepancies in their understanding, also the single ‘key-aspects’ of RRI still need to find a deeper response. Engagement, Open Access, Science Education, Gender, Ethics and Governance are generally agreed as crucial aspects for RRI but the proposed actions for developing them are still a matter of discussion. Furthermore, some commentators suggests confuse the ‘key-aspects’ with dimensions composing RRI, ending up with additions like social justice or sustainability.

Despite the many activities to stimulate and implement responsible research and innovation, there is currently no agreement on how to evaluate what it means. Briefly, there is currently no mechanism or procedure that will allow evidence-based planning, implementing and evaluating responsible research and innovation.

Objectives:

The GREAT project has been asked to analyse the outlined scenario and answer to some of its problems by proposing a governance framework for the development of RRI.
The main overall objective was to develop an empirically based and theoretically sound model of the role of responsible research and innovation governance by:
• exploring the dynamics of participation in research and innovation, and investigate the characteristics of responsible practices
• investigating the nature of new partnerships among various stakeholders, researchers and policymakers that are developing within innovation networks and the influence that these developments have on knowledge production and policy.
This has analytically been done by:
a. determining the characteristics of research and innovation

b. involving diverse groupings and
c. determining the social processes involved in responsible research and innovation practices.
In doing so, the GREAT project addressed all three issues requested in the call:
• to explore the knowledge and research potential of multi-stakeholder approaches in research;
• to investigate how responsible innovation is involved in research processes and

• to use this knowledge to inform policy makers on how to integrate responsible innovation in
further research activities.

Project Results:
Methodology:

The GREAT project has developed an empirically based and theoretically sound model of the role of responsible research and innovation governance.
GREAT has investigated on which grounds responsible research and innovation can and should be understood with respect to research and innovation activities. This has been researched by conceptualising responsible innovation in the overall theory of research governance. Three main approaches have been adopted in order to achieve such a result. Firstly, it has been undertaken a theoretical analysis of the concept of responsibility together with its understanding in current theories, showing the main common features, their weaknesses, strong aspects and, most of all, their underlying premises. Such theoretical reconnaissance has generated a grid of analysis adopted as a tool for analysing examples of research with a special focus on ICTs.
Secondly, the analytical grid has been applied to a variety of empirical data gathered through a qualitative social science approach (mixed methods) geared towards grounded theory. The case study approach, focus groups, document analysis, workshops and interviews have proven to be a fundamental methodology to understand existing perceptions and practices in research and innovation processes, and to validate and improve the analytical grid.
The third approach adopted by GREAT to validate its perspective was the agent-based simulation which managed to apply GREAT’s presupposition concerning the RRI categories suggested in the project and found by the empirical work. Simulations conducted with the GREAT-SKIN simulation model experimented policies for implementing responsible innovation strategies in research and evaluate future scenarios.
This interdisciplinary and complementary methodological path has led to the proposition of a model of RRI useful for policy-makers, research organizations and CSOs, in their various forms.

Great’s governance model for RRI is based on three main features.

• Responsible approaches must be participatory by design, foreseeing active and significant inclusion of different stakeholders.
• Participatory approaches must be developed on the basis of a two-order reflexivity, meaning that participants should be able to reflect on specific issues, but also on the institutional conditions that enabled the reflexive process itself. This operation can be promoted by a co-constructive model of governance as the one suggested by GREAT.
• Finally, responsible approaches to research and innovation must be focused on the ethical values and norms that define what responsibility means contextually. However, given the polysemy of responsibility and the meaning of ethics, the relation amongst the different understandings of responsibility must be kept in a constant, dynamic equilibrium avoiding any of these understandings being disregarded.

Several potential practical tools are indicated as a means to promote, and eventually achieve, such a reflexive stance without the ambition of exhausting all the possibilities that could, and surely will, be developed in the future. However, the GREAT Consortium believes that its model will itself generate new tools and practices contributing to implement ethical practices boosting the economy without endangering social and sustainable development.
This model has also been translated into simple and clear guidelines that draw on the work of GREAT and beyond. This resulted in a usable and practical handbook of guidelines to facilitate the understanding and adoption of RRI principles for researchers and those involved in all aspects of research and innovation. The guidelines provide an accessible starting point for both academic and non-academic researchers to reflect on and address the issues of RRI in their own discipline. The handbook was devised to be clear, concise and easily navigable, to encourage engagement with RRI in a way that is seen as neither prescriptive nor overly burdensome.

The project has explored the dynamics of participation in research and innovation, and investigated the characteristics of responsible practices. It also emphasized the nature of new and original partnerships among various stakeholders, researchers and policymakers that are developing within innovation networks and the influence that these developments have on knowledge production and policy. The analysis carried out by GREAT followed a triadic methodology, namely a theoretical analysis of the features of RRI, an empirical investigation of the obstacles and promising actions, and an agent-based model for ex-ante evaluation of research and innovation networks fed by empirical outcomes.
The GREAT project’s aim was neither to find a common definition of RRI to settle interpretative quarrels, nor to make a heterogeneous collection of the stakeholders perceptions of it. It was not even to accumulate all the existing (sometimes conflicting) key responsible activities that could be covered by a kind of meta-responsibility. If all can be useful, our ambition was bigger. We took into account three sorts of representations (Aristotle mimesis): a) what the things are, b) what people say they are and c) what they have to be. Because responsibility is a strong normative concept, it would not have been enough to depict existing practices (a) or to interview appropriate actors (b). Indeed, a cumulative approach could confront uses with a range of different approaches and conceptions without any criteria to assess them. Moreover, the so-called axiological neutrality is useless, as moral sociologists have shown, avoiding on the one side poor descriptivism and, on the other one, normatively decontextualized judgement.
According to the current state of art and its shortcomings, we have to pass from the analysis and understanding of moral (mores) to the one of ethics focused on responsibility. With a stance that focuses on the question of normativity connected to responsibility. We should possess the capacity to analyse the ways RRI, not only as a norm but with its normativity (reflexive stance in the condition of norm construction) is understood and implemented by different actors in their contexts, to be effective. This dynamic is an on-going process of adjustment between a normative horizon and between contextualised norms and values.
Thus, it is too limited and arbitrary to select one definition, trying to impose it, especially in the fluctuant domains of research and innovation in its tension/complementarity with responsibility. Therefore our method followed a procedural-comprehensive (reflexive equilibrium) approach, context-adaptive and normatively-sensitive regarding the embedded agents. It analytically explored the possible choices to deal with the problem, with a back and forth between empirically informed and theoretical research.
In GREAT, the question of RRI was closely connected with governance, not reduced to regulation, nor to democratic rules, because they were not specific enough for responsibility (ethically understood). Governance is focused on framing of the context, the normative horizon used by the actors to understand their situation and the RRI normativity within it. This horizon is ethically pluralist and not only because of a general fragmentation of social authorities in modern societies and the heterogeneity of normative sources or comprehensive doctrines. Accordingly, we considered different levels of contexts: a) real context (too rich to be depicted) of the actors, b) the conditions of its framing (reflexivity on different ways to frame it), with an intertwining of the epistemic and the normative horizon conditions. Practically the actors find the normative resources via dialectic between their rich real context and an ethical one (counterfactual) that could help them to reframe their understanding of their context and their action to change it. If the context is limited to the practical constraints, it would be inefficient to speak of responsibility or of ethics, or it will stay on a discursive level. Beyond that, different governance tools pass through different de-contextualisation and re-contextualisation (i.e. citizen conferences convening experts and citizen). That makes a plea for of a theoretical approach seeking a generality ascent tacking into account the epistemic and normative pluralism of different referential spheres (science, economy, law, ethics, personal values...).
The shift to responsibility, with the notion of RRI, changes the configuration of the pairing innovators – (who create problems, directly or indirectly, potential and sometimes real) - vs. opponents in society (from Civil Society Organizations or without any affiliation), laying on different conceptions of responsibility. This couple takes part in a quarrel of improvements (technological and ethical).
Therefore responsibility becomes a positive concept (with three sides). “My” actions make “me” epistemologically and ethically responsible from the very beginning in front of the others. “I” participate (commitment) when “I” act. Intersubjectivity and reflexivity let me discover the weight and load of potential consequences of my actions. This is stronger in innovation and research process. Here, the concept of full collective deliberation is perhaps a promising hypothesis in its individualistic, intersubjective and systemic (deliberative inter institutional system) dimensions matched with a co-dependent epistemic and normative evaluation on possible futures (forecast and quarrels on possibilities).
If RRI requires participation of stakeholders, this participation is not flat (simple) but qualified (effective and specified). Therefore, our research question has been the following: what are the conditions of reflexivity while considering responsibility in innovation to be effective? Implying that we needed to consider the different patterns of governance and what they offer in term of social reflexive outputs. Indeed, we analysed participative tools or systems organized in various ways (accountability and responsiveness), opening up differently responsible agents (role, capacity). And they should try to reach a relevant responsibilities sharing, to avoid dilution and poor involvements and contributions. Taking seriously governance with reflexivity in context permits to depart from governance of RRI to responsible governance of RRI. This move from sciences for society to science within society implicitly plays with the different meanings of responsibility: Responsible actors in responsible governance system.

• Work-Package 2

The WP 2 objectives were to establish robust and relevant conceptual tools for empirical research on responsible innovation. Mainly theoretical, this part of the project has mapped the main conceptions, often implicit, in the work of the most prominent analysts of RRI. More precisely, one of the aims of this WP was to analyse and assess the various conceptions of innovation and responsibility that have been used in RRI existing theories. To this end, we first provided an historical account for the emergence of RRI and shown the most critical limitations of Corporate social responsibility (CSR), Sustainable development, Participatory technological assessment approaches.
This conceptual work has been processed through an interdisciplinary confrontation. One if its originality was based on the consideration of moral and political philosophy resources, to go at the core of RRI : responsibility. From these works combined with some other in moral philosophy we have proposed ten different understandings of responsibility that can be reached. Responsibility as: 1) cause, 2) blameworthiness, 3) liability, 4) accountability, 5) task (or role), 6) authority, 7) capacity, 8) obligation. 9) responsiveness, 10) virtue (care).
Therefore participation is not only assessed by political criteria but relationally to the production processes and the products themselves.
Del 2.3. had the aim of providing the criteria or, better to say, the parameters necessary for processing applied approaches. To accomplish such a task it has outlining what the problems are with regard to RRI, gaining knowledge from the previous “Theoretical Landscape”.
The parameters that were developed are 8 and summarize the most important aspects that need to be detected, both in qualitative and quantitative terms, in the chosen case: 1) Tools, 2) Product, 3) Process, 4) Epistemic Tools, 5) Risk Assessment (among the methods Precautionary Principle), 6) Participatory approach, 7) Assessment, 8) Cultural differences, 9) Norm/Law relations.
Many scientific publications and communication have been developed in the line of these works. A Series in French and English (London, ISTE and New York, Wiley; Bernard Reber editor) dedicated on RRI has been launched (2015-2017), in 13 volumes mainly written be philosophers to take responsibility seriously.

• Work-Package 3
WP 3 has developed an empirically grounded understanding of the context of Responsible Research and Innovation, identified governance patterns, created a related taxonomy of common approaches, and developed methods and approaches for assessing and evaluating outputs of the project with user communities. A range of qualitative methods have been applied, and various activities for the engagement of multiple stakeholders have been undertaken (document analysis, semi-structured interviews, focus groups and workshops), in order to test, validate and improve the theoretical approach developed in WP 2. This also supported the ‘gap analysis’ conducted in WP 5. Special emphasis has been put on five key principles of RRI - anticipation, transparency, responsiveness, inclusion and reflexivity - and in particular the Analytical Grid, a framework including these five principles as well as further parameters for assessing the realisation of RRI in practice.

The Grid proved to be a useful assessment tool. For instance, the Grid has helped in specifying whether and how EU funded projects such as, CIP ICT PSP projects, realise responsible governance (see also WP 4 on the CIP ICT PSP). Hardly any project we studied achieved the ideal of co-construction. However, nearly all projects showed efforts going beyond the ‘Standard’ governance model, which would be the most ‘irresponsible’ governance approach according to the Analytical Grid.

WP 3 also found that the Grid contains various thick concepts such as, reflexivity, and in particular second-order reflexivity, which are important but also rather demanding in the sense that they require quite some prerequisite understanding of the RRI discourse. The RRI discourse consists of multiple voices and evolves constantly, which implies that the Analytical Grid is a window into a large problem space, which remains hard to navigate.

There is still practical use to the Grid though. If the Grid is to be considered a normative framework for assessing RRI, one of the central tenets of GREAT, and in particular WP 2, needs to be applied to the framework itself: for norms (of RRI) to be accepted and effective in a given local and empirical context, they need to be closely discussed and reinterpreted with local participants. Where necessary, (RRI) norms also need to be adjusted to context-specific perceptions, concerns and practices. This implies, for the Grid, that it should be understood as a ‘living’ tool for not simply assessing, but rather encouraging continuous multi-stakeholder dialogue.

• Work-Package 4
The objectives of WP4 have been to carry out an empirical investigation into how Responsible Innovation is currently conceptualized, how it is currently considered in research and how the integration could be improved in the future.
WP4 aimed at:
i) providing an empirical foundation on which the theoretical work on Responsible Research and Innovation (RRI) in the GREAT project can be grounded;
ii) providing an empirical foundation and methodological framework based on which further work to be conducted within other work packages of the GREAT project can be undertaken; and
iii) generating empirical data that can provide actionable information to calibrate the agent-based model and simulation to be carried out as part of work in Work Package 4 .
The empirical domain for this was a quantitative survey of a special sample of research and innovation networks in the current CIP Programme of the European Commission. On this basis, a sub-sample was chosen, which was investigated using in-depth case studies. Calibrated by data from the survey and the case studies, WP4 then applied and further developed an agent-based model for ex-ante evaluation of research and innovation networks. The model was extended by the RRI categories suggested in the project and found by the empirical work. Simulations experimented with policies for implementing responsible innovation strategies in research and evaluate future scenarios.
The tasks and relevant deliverables were conducted taking into account the analytical grid and models determined in WP2 and WP4. It was ensured that WP4 respected the methodology of the GREAT project, in particular the connection between WP4 methods, WP2 findings and WP3 testing results.
In a more detailed way, WP 4 consisted of a preparation made in Task 4.1 where the following tasks have been accomplished: develop the questionnaire, carry out web-based survey and database construction and analysis for CIP projects. The results of this task have been used in D. 4.4.

A second fundamental development of this WP has been the Task 4.2 where are presented the findings from five case studies. A ‘case’ is a specific CIP ICT PSP project:

• Case 1: CommonWell – Common Platform Services for Ageing Well in Europe
• Case 2: eSESH – Saving Energy in Social Housing with ICT
• Case 3: SPOCS – Simple Procedures Online For Cross-Border Services
• Case 4: DIEGO – Digital Inclusive e-Government
• Case 5: ImmigrationPolicy2.0 – Participatory Immigration Policy Making and Harmonization based on Collaborative Web 2.0 Technologies

The case study approach (e.g. Yin 2014) included a thematic analysis (Guest 2012) of selected deliverables and other publicly available documents such as homepages and websites of the projects. The five CIP ICT PSP projects for the document-based case studies have been chosen in a way that this approach complemented the choice of interviewees for WP 3. Also, the five projects for the document-based analysis in WP 4 have been chosen because they allowed us to discuss three possible RRI governance models determined in WP 2: the ‘Standard’ model, the ‘Consultation’ and the ‘Co-construction’ model.
In a next step WP4 compared these findings at the project level with the findings from an analysis of the EC programme level. In doing so the document-based analysis was extended to the EC work programmes, or calls, to which each project had to respond. The motivation for this was to find empirical data that would support the following basic reasoning: the more similar the two levels, the more ‘responsible innovation’ would need to be considered as a joint endeavour. In the case at hand ‘responsible innovation’ meant participative governance (engaging external stakeholders and/or taking into account their needs and concerns), but we also took into account other forms of responsible behaviour, and responsibilities, discovered during the analysis.
This approach allowed us to develop a second-order perspective on the broader (political) framing of a given project, which resonates with one of GREAT’s main conceptual and practical contributions. GREAT suggests to introduce the principle of second-order reflexivity (WP 2) to the RRI discourse, and to include related investigations of broader political, societal or economic framings and contexts in concrete RRI assessments.

In a third moment then the SKIN model was adapted to the project scope based on CIP survey and case studies (identify relevant actors in the CIP networks, their decision rules and learning behavior concerning RRI.
The model has also been calibrated with starting networks from CIP (prepare the CIP dataset for modelling, develop a framework for transforming data points to model input) by:

• defining policy-driven experiments for improvement of RRI integration (specify a range of policy relevant scenarios from impact assessment needs;
• detect scenarios which allow policy actors to steer against potential failure and to support successful RRI activities);
• Simulation, Experiments, Scenario modelling (experiment with the model to find a standard scenario, implement “target variables” for policy actors to influence the evolution of the RRI activities; run experiments, develop a database of simulated research and innovation network data); interpretation for RRI policy programs and strategies (analyse and interpret the simulated network data and provide results for future improvement of RRI strategies in CIP projects; visualise results).

In the agent-based model GREAT-SKIN, which is based on the SKIN simulation platform (http://cress.soc.surrey.ac.uk/SKIN/home), 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.

The Figure SKIN Workflow has been uploaded as annex

This agent-based model made 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.

• Work-Package 5

The work done in WP 5 has consisted in the re-elaboration of a governance framework for RRI on the basis of the empirical tests accomplished in the previous work packages. Besides, WP 5 has also updated the analysis on RRI theories so to deepen the indications for the adoption of RRI conception in the implementation of European research and innovation. WP 5 has developed along three main steps. A first document emphasising the nature and role of ethics for RRI. Its function within the six ‘keys’ has been indicated as the main context-based value reference to look at in the implementation of RRI.
A second deliverable has been focused on the political tools to implement RRI, namely the analysis of deliberative democracy. Del. 5.2. has in fact presented the main lines of the Theory of Deliberative Democracy (TDD) and a list of requirements robust enough to produce empirical original works. This theory has been indicated as matching two other important requirements for science with and for society: the imperatives of inclusiveness and rationality. These concerns meet the debates of epistemic democracy and more practically the problem of the place of expertise in democracy. Besides, deliberation is seen as matching with the precautionary principle, an important meta-principle for the European Union and for responsibility, thus RRI. The need to make explicit our assumptions jas been part of what we have defended in GREAT project as “second order reflexivity”.
In the GREAT project, we have already used different models of governance, giving different places and roles to the experts. With the TDD we provided a broader framework to place expertise inside a more general perspective, relevant for politics, ethics, and interdisciplinarity. Combined with moral and epistemic pluralism, a stronger TDD model makes stronger too what Owen et alii (2013) called “reflexive capital”. This deliverable has shown that RRI could conversely contribute to TDD. Having taken into account the Owen et alii (2013) request for the enhancement of plurality, it has put clearly in a table the different elements of a normative moral pluralism under three levels. In the same way it has underlined the necessity to match ethical and political deliberation. In this way this deliverable should be not only seen as a critical presentation to take seriously into account their promising proposal, but a contribution to reintroduce some parts of the TDD debates into the RRI discussion and, more over to improve the dimension they call “deliberation”.
The third main document is the one that recaps the enitre project although still without the useful translation represented by the guidelines. In a first step of D.5.3 we have analysed once more, but at the end of a validation trajectory, the current approaches aiming at the definition of RRI. Through a critique based on the equilibrium, between validation and application of norms, and among different social domains, we have highlighted that the most important approaches tend to privilege one particular aspect, mostly validation, i.e., the objective side, overlooking the importance of a contextual and therefore appropriate, i.e., subjective, impact.
Accordingly, instead of focusing on the development of abstract and impersonal procedures, which would fall into the same shortcomings, we proposed a model based on the dialectic between deliberation and a reflexive participation, a remodelled example of comprehensive proceduralism. In this way we have emphasized the importance of promoting a co-constructive or co-creative model of responsible practices.
We have also promoted some practical tools in order to reach this objective. However, it is not simply a tool, or predefined action that could guarantee the successful achievement of RRI, but the contextual development of ethical issues on the basis of a pondered equilibrium among different languages and different social domains.
The six keys, proposed by the EU Commission, can play a concrete role in pursuing such reflexive, complementary and fair attitude.

• Work-Package 6

WP 6 has developed the ‘register(s)’ to translate the findings of GREAT. WP 6 has been based on a highly inclusive methodology, gathering knowledge from a wide range of stakeholders and as well through the substantial help of an on-going literature analysis. The results of this WP reflect the nature of GREAT by setting in motion an engaging process that had an effective role in shaping the guidelines. Accordingly not only the language has been adapted to the needs of different stakeholders, but also the contents of the governance for RRI have been developed in a co-constructive manner, entailing the pluralistic and deliberative reflexivity promoted by GREAT’s approach.
Analytically, WP 6 has prepared the guidelines format on the basis of workshops and consultations with different stakeholders. A workshop was held at DMU on 17th of December 2014 whereby stakeholders (those who could be directly affected by the introduction of guidelines, such as researchers) were asked to analyse, discuss and provide feedback on what could constitute a usable and practical set of guidelines for the governance of RRI.
Beside a set of formal requirements useful for the development of an appropriate language that could be understood in a very specific and contextual way by specific stakeholders, were provided also a series of substantive, content focused requirements.

• Provide a small number of concise RRI definitions and other key terms that are tightly coupled to the findings from the project.
• Provide links to further definitions of RRI to broaden awareness of RRI principles and to encourage the use of RRI theory to relate to user’s own practice.
• Provide methods to re-assess and challenge the guidelines
• Respond to the EC framework, e.g. intervention logic model (relevance, effectiveness, efficiency and utility)
• To deliberate on possible ways of representing a pluralistic approach without compromising too much on requirement promoting usability.
• If explicit norms of responsible behaviour are expressed in the guidelines, these norms should be established with the participation of stakeholders, and by taking into account their contexts.

The Guidelines have been formalised into a Handbook, which contains and translates all the insights of GREAT. The Handbook has been organised following the instructions gathered during the workshops and the insights accumulated in three years of research. The main recommendations are the following:

1. Doing the Right thing (Ethics)
2. Good and Reflexive Governance
3. Creative Learning (Science Education)
4. Choosing Together (Engagement and Involvement)
5. Unlocking the Full Potential (Gender Equality)
6. Sharing Results (Open Access)
7. Taking Care of Our Planet (Environmental Stewardship)

Potential Impact:
The interdisciplinary and complementary methodology generated a model of RRI useful for policy-makers, research organizations and CSOs, in their various concrete forms. The GREAT model is based on a deliberative approach to participation focused on unveiling the institutional condition underlying research and innovation practices through a second-order reflexivity. Several potential practical tools are indicated as a mean to promote, and eventually achieve, such reflexive stance without the ambition of exhausting all the possibilities that could, and surely will, be developed in the future. However, the GREAT Consortium believes that its model will itself generate new tools and practices contributing to implement ethical practices boosting the economy without endangering a social and sustainable development.
In fact, this model embeds a double nature. On the one hand, it is based on some solid and invariable assumptions, namely that research and innovation require deep forms of engagement by different social actors. Implementing openness will produce new knowledge, useful to enrich research and necessary to produce innovation, but also increase the acceptability and the acceptance of a process or product, so to assure the social and economic value.
On the other hand, the ways in which this model can be applied are highly flexible and context-driven. This flexibility is innate in the model because it is based on the necessity of considering contextual issues and on the adoption of a reflexive stance. Research and innovation are carried on in different sectors calling for a model that can be adapted to specific necessities and technical requirements.
In this way, the GREAT Consortium believes that also and especially innovative products or processes could be developed according to an ethical perspective.
In practical terms, the results of this project will be useful for different purposes:
Consultancy and training will be provided by at least three partners (SIGNOSIS, UNamur, SciencesPO) of the Consortium to different ‘social actors’: policy-makers, industries, SMEs, NGOs, research organisations and associations.
The knowledge and model generated by the GREAT project will be used to implement RRI through its application in different domains of research, with a particular focus to the sectors addressed by the EU Commission (Security, Energy, etc.).

The guidelines developed in the GREAT project represent an outstanding source for future researchers and innovators to integrate RRI principles into their approach and working practices. Underpinned by the theoretical and empirical findings of the GREAT project, the guidelines therefore were designed to embed these findings into the values and approaches of each recommendation.
Practical guidelines that have a measurable effect on the way that research includes and informs responsible innovation practices need to be usable and practicable from the point of view of potential users. In order to ensure that this is the case, the GREAT project held consultation workshops and other sessions with various stakeholders. These expert workshops took place during the development of the guidelines, thus maximising the effectiveness of the specialist input into the discussions, but also allowing time for the modification and development of the guidelines according to the feedback received.

This would give the following (as indicated in the guidelines)
1. Doing the Right thing (Ethics)
2. Good and Reflexive Governance
3. Creative Learning (Science Education)
4. Choosing Together (Engagement and Involvement)
5. Unlocking the Full Potential (Gender Equality)
6. Sharing Results (Open Access)
7. Taking Care of Our Planet (Environmental Stewardship)
In addition, the guidelines act as a signpost to additional resources such as the observatory and common glossary in the RESPONSIBILITY project and the RRI navigator as derived by the RES-Agora project. In this way, the GREAT guidelines handbook provides an accessible and yet theoretically and empirically grounded resource for RRI across the spectrum of research and innovation.

List of Websites:

http://www.great-project.eu

o Robert Gianni robert.gianni@unamur.be
o Philippe Goujon pgo@info.fundp.ac.be

Related information

Contact

Philippe Goujon, (Professor)
Tel.: +32 81725258
Fax: +32 81724967
E-mail
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