With the widespread use of artificial intelligence, it becomes crucial to provide information about these systems and how they are used. Governments aim to disclose their use of algorithms to establish legitimacy and the EU AI Act mandates forms of transparency for all high-risk and limited-risk systems. Yet, what should the standards for transparency be? What information is needed to show to a wide public that a certain system can be used legitimately and responsibly? I argue that process-based approaches fail (...) to satisfy, as knowledge about the development process is insufficient to predict the properties of the resulting system. Current outcome-based approaches [Mitchell et al., 2019; Loi et al., 2021] are also criticized for a lack of attention to the broader socio-technical system and failure to account for empirical results that show that people care about more than just the outcomes of a process [as reported by Meyerson et al. (Procedural justice and relational theory: Empirical, philosophical, and legal perspectives, Taylor & Francis, 2021)]. Instead, I propose value-based transparency, on which the information we need to provide is what values have been considered in the design and how successful these have been realized in the final system. This can handle the objections to other frameworks, matches with current best practices on the design of responsible AI and provides the public with information on the crucial aspects of a system’s design. (shrink)

Synthetic biologists design and engineer organisms for a better and more sustainable future. While the manifold prospects are encouraging, concerns about the uncertain risks of genome editing affect public opinion as well as local regulations. As a consequence, biosafety and associated concepts, such as the Safe-by-design framework and genetic safeguard technologies, have gained notoriety and occupy a central position in the conversation about genetically modified organisms. Yet, as regulatory interest and academic research in genetic safeguard technologies advance, the implementation in (...) industrial biotechnology, a sector that is already employing engineered microorganisms, lags behind. The main goal of this work is to explore the utilization of genetic safeguard technologies for designing biosafety in industrial biotechnology. Based on our results, we posit that biosafety is a case of a changing value, by means of further specification of how to realize biosafety. Our investigation is inspired by the Value Sensitive Design framework, to investigate scientific and technological choices in their appropriate social context. Our findings discuss stakeholder norms for biosafety, reasonings about genetic safeguards, and how these impact the practice of designing for biosafety. We show that tensions between stakeholders occur at the level of norms, and that prior stakeholder alignment is crucial for value specification to happen in practice. Finally, we elaborate in different reasonings about genetic safeguards for biosafety and conclude that, in absence of a common multi-stakeholder effort, the differences in informal biosafety norms and the disparity in biosafety thinking could end up leading to design requirements for compliance instead of for safety. (shrink)

The growth of responsible innovation scholarship has been mirrored by a proliferation of RI definitions and practices, as well as a recognition of the importance of context for RI. This study investigates how researchers in the field of nanotechnology for food and agriculture define and practice RI, as well as what motivations they see for pursuing RI. We conducted 20 semi-structured interviews with nano-agrifood researchers from industry and academia in the USA, where we asked them to describe their RI definitions, (...) practices, and motivations. We analyzed the emergent themes from these interviews, including how the themes aligned with four prominent RI principles. We found that nano-agrifood researchers largely focused their descriptions of RI definitions, practices, and motivations around a narrow envisioning of the RI principle of anticipation — emphasizing product safety, efficacy, and efficiency. We also found noteworthy tensions surrounding the less frequently mentioned RI principles. For example, some researchers envisioned inclusion as a way to align products with industry interests while others saw it as a way to align products with the public good. Concerning motivations for RI, some researchers viewed RI as a way to protect one’s reputation and avoid lawsuits while others viewed it as a way to improve human well-being and solve societal problems. Given these findings, future efforts to foster RI within nano-agrifoods should promote discussions among researchers concerning what it means to responsibly innovate and what practices this could entail, particularly beyond ensuring product safety, efficacy, and efficiency. (shrink)

Humans are powerful and clever, and also more ignorant than they know. As a result, they too often fail to acknowledge or even recognize their limitations, and are more arrogant than humble regarding their capabilities. Education that explicitly recognizes and addresses the context of science and technology, their inherent values and ethical implications and concerns, and their problematic as well as beneficial impacts can potentially rescue the human species from itself.

Safe-by-Design (SbD) is a new concept that urges the developers of novel technologies to integrate safety early on in their design process. A SbD approach could—in theory—support the development of safer products and assist a responsible transition to the bioeconomy, via the deployment of safer bio-based and biotechnological alternatives. Despite its prominence in policy discourse, SbD is yet to gain traction in research and innovation practice. In this paper, we examine a frequently stated objection to the initiative of SbD, namely (...) the position that SbD is already common practice in research and industry. We draw upon observations from two case studies: one, a study on the applicability of SbD in the context of bio-based circular materials and, two, a study on stakeholder perceptions of SbD in biotechnology. Interviewed practitioners in both case studies make claims to a strong safety culture in their respective fields and have difficulties differentiating a SbD approach from existing safety practices. Two variations of this argument are discussed: early attentiveness to safety as a strictly formalised practice and early attentiveness as implicit practice. We analyse these perceptions using the theoretical lens of safety culture and contrast them to the aims of SbD. Our analysis indicates that professional identity and professional pride may explain some of the resistance to the initiative of SbD. Nevertheless, SbD could still be advantageous by a) emphasising multidisciplinary approaches to safety and b) offering a (reflective) frame via which implicit attentiveness to safety becomes explicit. (shrink)

Safe-by-Design is an approach to engineering that aims to integrate the value of safety in the design and development of new technologies. It does so by integrating knowledge of potential dangers in the design process and developing methods to design undesirable effects out of the innovation. Recent discussions have highlighted several challenges in conceptualizing safety and integrating the value into the design process. Therefore, some have argued to design for the _responsibility_ for safety, instead of for safety itself. However, this (...) idea has not been developed further. In this article, we develop an approach to Safe-by-Design, grounded in care ethics, which builds on the idea of designing for responsibility and can deal with the complexity that is inherent to the conceptualization of safety. We describe five ways in which care ethics contributes to the conceptualization of Safe-by-Design: (1) It suggests the development of ‘circles of care’ in which stakeholders share the responsibility for safety; (2) it recognizes the importance of considering safety as something that is situated in the surroundings of a technology, instead of as a property of the technology itself; (3) it acknowledges that achieving safety is labour that requires an ongoing commitment; (4) it emphasizes that the way in which we relate to technology impacts its safety; and (5) it recognizes the role of emotions in assessing safety. All these elements combined lead to a broader understanding of safety and a philosophically more substantial and practically more appealing conceptualization of Safe-by-Design. (shrink)

Genetic engineering techniques (e.g., CRISPR-Cas) have led to an increase in biotechnological developments, possibly leading to uncertain risks. The European Union aims to anticipate these by embedding the Precautionary Principle in its regulation for risk management. This principle revolves around taking preventive action in the face of uncertainty and provides guidelines to take precautionary measures when dealing with important values such as health or environmental safety. However, when dealing with ‘new’ technologies, it can be hard for risk managers to estimate (...) the societal or environmental consequences of a biotechnology that might arise once introduced or embedded in society due to that these sometimes do not comply with the established norms within risk assessment. When there is insufficient knowledge, stakeholders active in early developmental stages (e.g., researchers) could provide necessary knowledge by conducting research specifically devoted to what these unknown risks could entail. In theory, the Safe-by-Design (SbD) approach could enable such a controlled learning environment to gradually identify what these uncertain risks are, to which we refer as responsible learning. In this paper, we argue that three conditions need to be present to enable such an environment: (1) regulatory flexibility, (2) co-responsibility between researchers and regulators, and (3) openness towards all stakeholders. If one of these conditions would not be present, the SbD approach cannot be implemented to its fullest potential, thereby limiting an environment for responsible learning and possibly leaving current policy behind to anticipate uncertain risks. (shrink)

Based on fieldwork, this article highlights the unexpected effects of controversies about nanotechnology in France. These controversies stem in particular from a strong challenge to the field by civil society protests and criticism concerning environmental and health risks. One reason for this challenge is the specific difficulties in assessing the toxicity and ecotoxicity of nanomaterials. Civil society organizations have pushed for strictly controlling or stopping academic, industrial, or even basic research. They were not successful in this regard but their activities (...) prompted researchers to think about “safe by design” solutions and this led to new interdisciplinary cooperation. Furthermore, the uncertainty about the risks assessment resulted in a reconfiguration of the relationship between academic research and industrial companies. Researchers have become essential to the shaping of safe products. The risks of nanomaterials have thus been a driving force for new research and innovation practices. (shrink)

Since the beginning of the current hype around Artificial Intelligence (AI), governments, research institutions, and the industry invited ethical, legal, and social sciences (ELS) scholars to research AI’s societal challenges from various disciplinary viewpoints and perspectives. This approach builds upon the tradition of supporting research on the societal aspects of emerging sciences and technologies, which started with the Ethical, Legal, and Social Implications (ELSI) Program in the Human Genome Project (HGP) in the early 1990s. However, although a diverse ELS research (...) community has formed since then, AI’s societal challenges came to be mostly understood under the narrow framing of ethics and disconnected from the insights and experiences of past ELS research. In this article, we make up for this gap and connect insights from past ELS researchers with current approaches to research the societal challenges of AI. We analyse and summarize the history of “ELS programs” (programs that emerged since the HGP to support ELS research in a given domain) as three distinct eras: a genomics era, a nano era, and an RRI era. Each of these eras comprises several achievements and challenges relevant to ELS programs in AI research, such as the setup of independent funding bodies, the engagement of the wider public in research practice, and the increasing importance of private actors. Based on these insights, we argue that AI research currently falls back on self-regulatory, less participatory, and industry-led approaches that trouble ELS programs’ past achievements and hinder opportunities to overcome the still-existing challenges. (shrink)