We discuss the implementation of Responsible Research and Innovation (RRI) within a project for the development of an AI-supported exergame for assisted movement training, outline outcomes and reflect on methodological opportunities and limitations. We adopted the responsibility-by-design (RbD) standard (CEN CWA 17796:2021) supplemented by methods for collaborative, ethical reflection to foster and support a shift towards a culture of trustworthiness inherent to the entire development process. An embedded ethicist organised the procedure to instantiate a collaborative learning effort and implement RRI (...) in a translational context. Within the interdisciplinary setting of the collaboration and with the support of a technoethicist, we successfully identified relevant, project-specific challenges and developed a roadmap with derived actions, thus meaningfully integrating RRI into the development process. We discuss the methodological procedure in terms of its effectiveness and efficiency, the allocation of responsibilities and roles, particularly regarding potential frictions in the interdisciplinary context with embedded ethics, and the challenges of the translational context. We conclude that the responsibility-by-design standard effectively established a productive workflow for collaborative investigation and work on ethical challenges. We reflect on methodological difficulties and propose possible avenues to our approach. (shrink)

In this article we present a new approach to practical artificial intelligence (AI) ethics in heavy industry, which was developed in the context of an EU Horizons 2020 multi partner project. We begin with a review of the concept of Industry 4.0, discussing the limitations of the concept, and of iterative categorization of heavy industry generally, for a practical human centered ethical approach. We then proceed to an overview of actual and potential AI ethics approaches to heavy industry, suggesting that (...) current approaches with their emphasis on broad high-level principles are not well suited to AI ethics for industry. From there we outline our own approach in two sections. The first suggests tailoring ethics to the time and space situation of the shop floor level worker from the ground up, including giving specific and evolving ethical recommendations. The second describes the ethicist’s role as an ethical supervisor immersed in the development process and interpreting between industrial and technological (tech) development partners. In presenting our approach we draw heavily on our own experiences in applying the method in the Use Cases of our project, as examples of what can be done. (shrink)

Sedlakova and Trachsel (2023) argue that on the one hand, conversational artificial intelligence (CAI) does not fulfill the necessary conditions for full attribution of agency, such as having consc...

BackgroundDespite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often absent from discourse on the ethical design, development, and deployment of AI. This study explores the perspectives of birth parents and mothers on the introduction of AI-based cardiotocography (CTG) in the context of intrapartum care, focusing on issues pertaining to trust and trustworthiness.MethodsSeventeen semi-structured interviews were conducted with birth parents (...) and mothers based on a speculative case study. Interviewees were based in England and were pregnant and/or had given birth in the last two years. Thematic analysis was used to analyze transcribed interviews with the use of NVivo. Major recurring themes acted as the basis for identifying the values most important to this population group for evaluating the trustworthiness of AI.ResultsThree themes pertaining to the perceived trustworthiness of AI emerged from interviews: (1) trustworthy AI-developing institutions, (2) trustworthy data from which AI is built, and (3) trustworthy decisions made with the assistance of AI. We found that birth parents and mothers trusted public institutions over private companies to develop AI, that they evaluated the trustworthiness of data by how representative it is of all population groups, and that they perceived trustworthy decisions as being mediated by humans even when supported by AI.ConclusionsThe ethical values that underscore birth parents and mothers’ perceptions of trustworthy AI include fairness and reliability, as well as practices like patient-centered care, the promotion of publicly funded healthcare, holistic care, and personalized medicine. Ultimately, these are also the ethical values that people want to protect in the healthcare system. Therefore, trustworthy AI is best understood not as a list of design features but in relation to how it undermines or promotes the ethical values that matter most to its end users. An ethical commitment to these values when creating AI in healthcare contexts opens up new challenges and possibilities for the design and deployment of AI. (shrink)

Artificial intelligence (AI) has garnered tremendous attention in health care, and many hope that AI can enhance our health system’s ability to care for people with chronic and degenerative conditions, including Parkinson’s Disease (PD). This paper reports the themes and lessons derived from a qualitative study with people living with PD, family caregivers, and health care providers regarding the ethical dimensions of using AI to monitor, assess, and predict PD symptoms and progression. Thematic analysis identified ethical concerns at four intersecting (...) levels: personal, interpersonal, professional/institutional, and societal levels. Reflecting on potential benefits of predictive algorithms that can continuously collect and process longitudinal data, participants expressed a desire for more timely, ongoing, and accurate information that could enhance management of day-to-day fluctuations and facilitate clinical and personal care as their disease progresses. Nonetheless, they voiced concerns about intersecting ethical questions around evolving illness identities, familial and professional care relationships, privacy, and data ownership/governance. The multi-layer analysis provides a helpful way to understand the ethics of using AI in monitoring and managing PD and other chronic/degenerative conditions. (shrink)

The aim of UK-REACH (“The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers”) is to understand if, how, and why healthcare workers (HCWs) in the United Kingdom (UK) from ethnic minority groups are at increased risk of poor outcomes from COVID-19. In this article, we present findings from the ethical and legal stream of the study, which undertook qualitative research seeking to understand and address legal, ethical, and social acceptability issues around data protection, privacy, and information (...) governance associated with the linkage of HCWs’ registration data and healthcare data. We interviewed 22 key opinion leaders in healthcare and health research from across the UK in two-to-one semi-structured interviews. Transcripts were coded using qualitative thematic analysis. Participants told us that a significant aspect of Big Data research in public health is varying drivers of mistrust—of the research itself, research staff and funders, and broader concerns of mistrust within participant communities, particularly in the context of COVID-19 and those situated in more marginalised community settings. However, despite the challenges, participants also identified ways in which legally compliant and ethically informed approaches to research can be crafted to mitigate or overcome mistrust and establish greater confidence in Big Data public health research. Overall, our research indicates that a “Big Data Ethics by Design” approach to research in this area can help assure (1) that meaningful community and participant engagement is taking place and that extant challenges are addressed, and (2) that any new challenges or hitherto unknown unknowns can be rapidly and properly considered to ensure potential (but material) harms are identified and minimised where necessary. Our findings indicate such an approach, in turn, will help drive better scientific breakthroughs that translate into medical innovations and effective public health interventions, which benefit the publics studied, including those who are often marginalised in research. (shrink)

In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towards addressing ethics at the societal level. In this article, we propose a tripartite framework to overcome these (...) difficulties. Our framework analytically decomposes an ethics module into three dimensions. First, there is the ethical dimension, which pertains to the learning goals. Second, there is the moral dimension, which addresses the moral relevance of engineers’ conduct. Finally, there is the political dimension, which scales up issues of moral relevance at the civic level. All in all, our framework has two advantages. First, it provides analytic clarity, i.e. it enables course instructors to locate ethical dilemmas in either the moral or political realm and to make use of the tools and resources from moral and/or political philosophy. Second, it depicts a comprehensive ethical training, which enables students to both reason about moral issues in the abstract, and to socially contextualize potential solutions. (shrink)