Science and Engineering Ethics最新文献

Frameworks for ascertaining the societal dimensions of research and innovation (R&I), such as the Societal Readiness Thinking Tool (SRTT), have supported reflection on ethics and responsibility but often risk reducing reflexivity to procedural checklists or impact assessments. This paper develops an enhanced version, the reflexive SRTT 2.0 process, by incorporating concepts of epistemic reflexivity and ethnomethodological sensitivity. We introduce the concept of reflexive societal readiness, which understands readiness as a situated, ongoing accomplishment shaped by both local practices and institutional "relations of ruling." Drawing on ethnomethodological observations, reflexive questionnaires, and an initial workshop in the Horizon Europe project AGRO4AGRI, we examined how researchers engaged with reflexivity in practice. Our findings reveal three recurring patterns: reflexivity was often deflected through reliance on methodological safeguards, outsourced to societal impact experts or stakeholders, and substituted with compliance to regulatory frameworks or dominant imaginaries of sustainability and competitiveness. These practices uphold internal project orders and limit the potential for interdisciplinary learning and critical engagement. To address these obstacles, SRTT 2.0 proposes a reflexive process combining (a) observation of situated practices, (b) reflexive questioning that foregrounds individual positionalities, and (c) workshops that foster collaborative and institutional learning. This design enables researchers to critically interrogate their assumptions, engage more meaningfully with inclusion, and question the sociotechnical imaginaries shaping their work. We argue that embedding such reflexive processes into project lifecycles can extend and strengthen Responsible Research and Innovation (RRI) frameworks by cultivating collaborative, empathetic, and institutional learning. While challenges remain, SRTT 2.0 offers a transferable pathway for fostering more reflexive and responsible innovation practices.

Autonomy is a fundamental ethical principle in artificial intelligence (AI) ethics. Current discussions regarding autonomy-related risks in human-AI interaction, as well as potential mitigation strategies, have mainly focused on recommendation systems and algorithmic decision-making systems. However, systematic analyses of the autonomy issues posed by newly emerging generative AI or chatbots (such as ChatGPT) remain scarce. This paper aims to bridge this gap and proposes a Socratic method-based chatbot, herein designated SocrAI, as a potential countermeasure informed by recent technological advancements. We identify two primary forms of autonomy risk associated with generative chatbots-false mental states and cognitive deskilling-and, through an examination of their underlying causes, argue that the Socratic method offers a plausible means of mitigation. The paper further assesses the feasibility of employing the Socratic method within generative chatbots to preserve and support users' autonomy and outlines the prospective implementation of SocrAI together with directions for future work. SocrAI represents a novel attempt to strengthen human agency, one that encourages users to become self-initiating inquirers who, with the assistance of AI, actively engage their abilities in the pursuit of answers.

Should developers be held responsible for the predictions of their neural networks-and if not, does that introduce a responsibility gap? The claim that neural networks introduce a responsibility gap has seen significant pushback, with philosophers arguing that the gap can be bridged, or did not exist in the first place. We show how the responsibility gap turns on whether we can distinguish between foreseeable and unforeseeable neural network predictions. Empirical facts about neural networks tell us we cannot, which seems to force developers to either assume full responsibility or no responsibility at all, introducing a responsibility gap-unless, of course, the same empirical facts hold true of humans, in which case there is no gap, but the trouble is simply with the classical notion of responsibility. We revisit and revise Mele's Zygote, as well as the famous Palsgraf case, and argue that in fact, what complicates responsibility assignment for neural networks also complicates responsibility assignment for humans, and humans seem to confront us with the same all-or-nothing dilemma. Thus, we agree there is no technology-induced responsibility gap (there was no gap in the first place), but for slightly different reasons than our predecessors.

While research in the ethics of artificial intelligence (AI) has grown recently, the relationship between AI's ethical and economic dimensions is under-researched. This is surprising, given the considerable investments in AI by Big Tech companies (e.g., Microsoft, META and IBM) and their ambiguous role in today's public debate on AI. After the second Trump election, this ambiguity has resulted in industry opposition to rules and regulations (e.g., disinvestments in moderation facilities at social media platforms and calls for deregulation). AI ethics must respond to the economic underpinnings of this situation.While economics in AI ethics has also been seen in recent funding schemes (e.g., investment in 30 ethical, legal, and social (ELSA) labs), there is a ambiguity in how these AI ELSA labs should respond to economic aspects. This paper examines the role of economics in responsible AI research, using the case of the ELSA lab approach. The four features of ELSA (proximity, anticipation, interdisciplinarity, and interactivity) serve as a point of departure to demonstrate how economics can be integrated within the ELSA framework of AI. This paper proposes that economics should be integrated within these four ELSA features to implement responsible AI successfully.

There is a need for cross-disciplinary researchers and professionals in the radiological sciences who can navigate complex interconnected ethical-social-technical issues, communicate across a wide audience in consideration of multiple stakeholder perspectives, and remain self-critical, aware, and reflective of the field with the intent of continuous improvement within the broader profession. Given that traditional curriculum related to the nuclear and radiological sciences emphasizes the technological, scientific aspects of radioactivity and ionizing radiation, a graduate-level course in "nuclear culture" was developed that employs various forms of art, expression, and material culture as a vehicle for encouraging deeper, dedicated reflection on related social and ethical issues. This paper provides a description of course structure and representative content, along with discussion of student perceptions, as a case study in the use of an arts-informed approach (that is, a STEAM-based approach) to guiding students through perspective-taking, self-expression, and authentic and critical evaluation of broad issues surrounding current and historical use of radiation. The course consists of discussions, reflective writing, and projects, supplemented with hands-on activities. Student perceptions of the course, elucidated through thematic analysis of post-hoc surveys, revolved around: novel educational approaches; student engagement and validation; ethics, morals, and empathy; and the societal impact of nuclear. Review of student and instructor perceptions suggests that art in various forms can be incorporated into graduate-level curriculum to improve the educational experience of nuclear-focused students and promote deeper reflection and understanding of social and ethical issues related to their chosen field.