This chapter discusses principles, frameworks, and steps for designing a roadmap to implement Responsible Research and Innovation (RRI) in industrial practices. It is based on invaluable experience gathered from the EU-funded PRISMA project, in which a trans-disciplinary group of experts from research, industries, and policy developed guidelines to include relevant societal values in the development strategy of innovative products. These guidelines are built on existing corporate social responsibility (CSR) and quality, risk and innovation management standards and policies. Fundamentally, they provide a management standard (Plan-Do-Check-Act cycle) that could help companies to introduce structural changes in their usual business practices toward more anticipatory, inclusive, and RRI practices (responsibility-by-design). The guidelines can be used by researchers, businesses, and innovators to develop long-term strategies (roadmaps) for Responsible Innovation, which, in turn, help organizations identify and achieve technologies geared toward ethically and socially desirable outcomes.

Responsible Research and Innovation and Responsible Innovation, as academic endeavours, have grown substantially since their birth in the previous decades. They have been used as synonyms on a structural basis, and both concepts have been studied from various disciplinary backgrounds. This paper identifies Responsible Research and Innovation's and Responsible Innovation's shared research topics, knowledge base, and academic organisation as a common ground for scholars to further their individual or joint research. It does so by conducting a keyword analysis and a collaboration analysis, combined with a reference analysis of their academic literature. This paper discusses the most influential references in chronological order and sheds light on the accumulation of knowledge. The results suggest that Responsible Research and Innovation and Responsible Innovation have matured into an increasingly cumulative and interconnected research trajectory following the footsteps of similar, more mature research areas.

This chapter provides a political and philosophical analysis of the values at stake in ensuring cybersecurity for critical infrastructures. It presents a review of the boundaries of cybersecurity in national security, with a focus on the ethics of surveillance for protecting critical infrastructures and the use of AI. A bibliographic analysis of the literature is applied until 2016 to identify and discuss the cybersecurity value conflicts and ethical issues in national security. This is integrated with an analysis of the most recent literature on cyber-threats to national infrastructure and the role of AI. This chapter demonstrates that the increased connectedness of digital and non-digital infrastructure enhances the trade-offs between values identified in the literature of the past years, and supports this thesis with the analysis of four case studies.

This work aims to re-investigate different aspects of a variety of filters and filtration processes within diverse realms of knowledge from an interdisciplinary point of view, and develops a comprehensive Active Model of Filter that accommodates the phenomena in its entire diversity and complexity. The Active Filter Model proposes to take Filter-from various fields and scales operating at material and symbolic level-not as mere objects, but as difference-producing phenomena that need to be addressed as complex active systems within event-based boundaries. The model underlines a systemic, operative, performative, and negentropic nature to the phenomena that invites one to; recognize various elements and intra-actions within a filter system; follow chains of operations and processes that render the activity; take the performative and ecology building aspect of the filter activity into consideration; and acknowledge the negentropic, order-producing nature of filtering phenomena. The Active Filter Model is meant to serve as a foundation for further analysis and synthesis in various fields dealing with Filter, and the research approach is put forward as a paradigm for how seemingly disciplinary concepts such as Filter can be rethought through interdisciplinary methods, and mutually complement research questions within active matter, biology, information philosophy, data science and sustainability discourses.

There is now almost a decade of experience with RRI (Responsible Research and Innovation), including a growing emphasis on RRI in industry. Based on our experiences in the EU-funded project PRISMA, we find that the companies we engaged could be motivated to do RRI, but often only after we first shifted initial assumptions and strategies. Accordingly, we formulate six lessons we learned in the expectation that they will be relevant both for RRI in industry as well as for the future of RRI more broadly. These lessons are: (1) Strategize for stakeholder engagement; (2) Broaden current assessments; (3) Place values center stage; (4) Experiment for responsiveness; (5) Monitor RRI progress; and (6) Aim for shared value.

Responsible research and innovation (RRI) is an approach to research and innovation governance aiming to ensure that research purpose, process and outcomes are acceptable, sustainable and even desirable. In order to achieve this ambitious aim, RRI must be relevant to research and innovation in industry. In this paper, we discuss a way of understanding and representing RRI that resonates with private companies and lends itself to practical implementation and action. We propose the development of an RRI maturity model in the tradition of other well-established maturity models, linked with a corporate research and development (R&D) process. The foundations of this model lie in the discourse surrounding RRI and selected maturity models from other domains as well as the results of extensive empirical investigation. The model was tested in three industry environments and insights from these case studies show the model to be viable and useful in corporate innovation processes. With this approach, we aim to inspire further research and evaluation of the proposed maturity model as a tool for facilitating the integration of RRI in corporate management.

Responsible research and innovation (RRI) has become an important topic in the academic community and in policy circles, but it has not yet been systematically included in the innovation process of companies. We discuss how companies can integrate RRI into their corporate social responsibility (CSR) policies and business strategy. To this end, we developed a conceptual model that links a company's RRI strategy to its context, and that helps to translate the RRI strategy into activities that result in RRI outcomes. We also propose a process for developing company-specific RRI key performance indicators (KPIs) that can support companies to measure RRI outcomes.