Pandemic Surveillance and Racialized Subpopulations: Mitigating Vulnerabilities in COVID-19 Apps

Debates about effective responses to the COVID-19 pandemic have emphasized the paramount importance of digital tracing technology in suppressing the disease. So far, discussions about the ethics of this technology have focused on privacy concerns, efficacy, and uptake. However, important issues regarding power imbalances and vulnerability also warrant attention. As demonstrated in other forms of digital surveillance, vulnerable subpopulations pay a higher price for surveillance measures. There is reason to worry that some types of COVID-19 technology might lead to the employment of disproportionate profiling, policing, and criminalization of marginalized groups. It is, thus, of crucial importance to interrogate vulnerability in COVID-19 apps and ensure that the development, implementation, and data use of this surveillance technology avoids exacerbating vulnerability and the risk of harm to surveilled subpopulations, while maintaining the benefits of data collection across the whole population. This paper outlines the major challenges and a set of values that should be taken into account when implementing disease surveillance technology in the pandemic response

Patient‐led innovation and global health justice: open‐source digital health technology for type 1 diabetes care

Health innovation is mainly envisioned in direct connection to medical research institutions or pharmaceutical and technology companies. Yet, these types of innovation often do not meet the needs and expectations of individuals affected by health conditions. With the emergence of digital health technologies and social media, we can observe a shift, which involves people living with illness modifying and improving medical and health devices outside of the formal research and development sector, figuring both as users and innovators. This patient-led innovation has been celebrated in innovation studies and economics as a “bottom-up” type of innovation. In this article, we take a closer look at open-source patient-led innovation in the context of type 1 diabetes care. In our inquiry, we pay particular attention to the social and ethical dimensions of this innovation, building on empirical material. Upon exploring the notion of patient-led innovation and its socio-political context through the lens of intersectional and global health justice, we argue that a proactive strategy is needed to ensure that open-source patient-led innovation will be more globally accessible, center the health needs of the most underserved populations, as well as facilitate equitable and just health benefits. To support this aim, we provide a range of examples of different initiatives addressing the persistent inequalities that have so far inhibited patient-led innovation from more fully materializing its innovative potential

The Deadly Business of an Unregulated Global Stem Cell Industry

In 2016, the Office of the State Coroner of New South Wales released its report into the death of an Australian woman, Sheila Drysdale, who had died from complications of an autologous stem cell procedure at a Sydney clinic. In this report, we argue that Mrs Drysdale's death was avoidable, and it was the result of a pernicious global problem of an industry exploiting regulatory systems to sell unproven and unjustified interventions with stem cells.Research for this paper was supported with the funding from an Australian Research Council Linkage Project Grant (LP150100739) and the National University of Singapore, Office of the Deputy President (Research and Technology)—Humanities and Social Sciences Research Fund (WBS: R-171-000-055-646)

Digital contact tracing and exposure notification: ethical guidance for trustworthy pandemic management

10.1007/s10676-020-09566-8Ethics and Information Technology233285-29

Fair and equitable AI in biomedical research and healthcare:Social science perspectives

Artificial intelligence (AI) offers opportunities but also challenges for biomedical research and healthcare. This position paper shares the results of the international conference “Fair medicine and AI” (online 3–5 March 2021). Scholars from science and technology studies (STS), gender studies, and ethics of science and technology formulated opportunities, challenges, and research and development desiderata for AI in healthcare. AI systems and solutions, which are being rapidly developed and applied, may have undesirable and unintended consequences including the risk of perpetuating health inequalities for marginalized groups. Socially robust development and implications of AI in healthcare require urgent investigation. There is a particular dearth of studies in human-AI interaction and how this may best be configured to dependably deliver safe, effective and equitable healthcare. To address these challenges, we need to establish diverse and interdisciplinary teams equipped to develop and apply medical AI in a fair, accountable and transparent manner. We formulate the importance of including social science perspectives in the development of intersectionally beneficent and equitable AI for biomedical research and healthcare, in part by strengthening AI health evaluation