On March 22, 2022, Dr. Carrie Figdor (Philosophy, Iowa Neuroscience Institute), spoke on the following topic:

Animal models have long been used to investigate human mental disorders, including depression, anorexia, and autism spectrum disorders. This practice is usually justified consequentially in terms of the benefits (to humans) outweighing the costs (to the animals). Critics have argued that for various reasons the results from experiments with animals don’t translate reliably to the human case, so it seems to follow that the animals are suffering and dying in vain. I’ll consider a number of these criticisms, raise a few of my own, and consider whether severe restrictions on the use of animal models in neuropsychiatry, and medical research generally, might be better for the humans and the animals alike. 

This talk has been postponed, date TBA.

From the Bioethics Program at Icahn School of Medicine, Mount Sinai, Paul Cummins presents on the following topic: 

Despite decades of scholarship on greening healthcare, the healthcare industry remains a significant contributor to the climate crisis, which in turn makes it a cause of the health harms that are a product of the climate crisis. Appreciation of the need of the need to mitigate its impact on climate has increased within the healthcare industry over the last year. While this initiative is laudable, it will not be sufficient to prevent the health crises that irreversible climate change will bring. I will argue that the healthcare industry should pursue research on treatments for the health conditions that the climate crisis will generate, as a matter of justice. Because the concepts of justice and social benefit within research ethics are insufficient to ground this duty, I will draw on concepts of justice in public health and environmental ethics to support this claim. This incorporation of a more expansive notion of justice into research will be defended as consistent with recent scholarship on approving applications for funding for COVID-19 research.

Cortilia Lin co-founded Kyalio (VR Surgical Training) and set up operations in Singapore, Taiwan and the Netherlands. With 15 years of Healthcare experience in the US, Europe and APAC, she is invited to bring in the comparative viewpoints on entrepreneurship and corporate intrapreneurship across more than 27 countries, from both MNC and start-up perspectives. 
Cortilia specializes in applying data science for new product design, healthcare portfolio management, innovative sales/marketing strategy, and translating insights into real topline gain. Her work was featured in Harvard Business Review (Traditional Chinese Edition), "Revolutionize Customer Experience with Data Science." On Oct. 25, 2021, she presented on the following topic: 

​Developing high tech/deep tech solutions has become the trend in the research and start-up space. However, high tech solutions generally mean higher total cost of adoption (e.g. human skill transformation and visionary investment) to potential customers, which leads to a narrower addressable market and less scalable outlook to attract funding. Moreover, with a high productization cost, developers are required to capture high value per transaction.  
How may researchers and entrepreneurs together bring the high tech solutions to a broader population and allow more to benefit? This talk presents a collection of pragmatic case studies on making high tech solutions accessible with a market definition ultimately creating a stronger impact to healthcare.

On Sept. 22, 2021, Dr. Krista Tromp from the Department of Medical Ethics, History and Philosophy of Medicine at Erasmus MC, presented on the following: 

Before a research proposal reaches potential participants, many ethical decisions related to the research have been made on which the potential research participants have no influence. Only then do potential participants make a decision about participation. I call those decisions, ‘gates’ in the research enterprise. These decisions concern 1) protective measures in legislation; 2) research design; 3) medical-ethical review; 4) recruitment by the professional; and 5) informed consent by the potential research participant.
In this talk I will give you some insights in the function of the gates. Based on practical examples, I will give you some tools and directions how to handle the decisions you might come across when dealing with these gates in your own research.

On June 15, 2021, Dr. Joshua Schulz, Associate professor of philosophy & ethics consultant from DeSales University, presented on this topic:

This paper begins with the relatively uncontroversial claim that how we define the nature and ends of medicine depends on our current best model of scientific investigation. It is now possible to draw a distinction between analog and digital models of medicine based on how we collect, analyze, and use data. We argue that the development of sophisticated AI will encourage medicine to increasingly focus on disease prediction, risk-management, and behavior optimization. However, principle-based approaches to clinical bioethics are ill-prepared to deal with novel problems posed by this shift. Specifically, an increasing emphasis on the medical management of long-tail risk factors for asymptomatic, primary-prevention targets will raise two sets of worries: one about the medicalization of daily life, and a second about which of several competing models of virtue ethics are best equipped to think about ethical concerns arising from these changes—that is, how medical ethics should deal with what is coming to be known as the problem of ‘corrupt personalization.’

On May 24, 2022, Luis Terán & Ivo Wallimann-Helmer from the Environmental Sciences and Humanities Institute at the University of Fribourg, spoke on the following topic:

Dynamically developing digitization initiatives among public institutions and private companies necessitate a balanced approach to digital ethics. Several frameworks and legal regulations have been adopted to clarify and define the various ethical challenges in digital contexts. These initiatives often accentuate one of three components: data security, data governance, or digital strategy. However, an integrated approach is required to meet the current demand for an ethical and sustainable approach to digitalization and address the growing number of challenges occurring in handling data and related peripheral components. This paper develops the concept of an integrated framework to incorporate all relevant aspects of digital ethics by combining three categories of digital contexts: law and regulations, ethics and justice, and environmental sustainability. The core of this integrated framework, the Fribourg sustainable digital ethics framework (FSDEF), consists of two boundary conditions of sustainable development: social thresholds of justice and ecological planetary boundaries. It also incorporates numerous other frameworks and standards, including value-based engineering and IEEE standards.

On Feb. 22, 2022, Dr. Saba Hinrichs-Krapels, MEng MIET, Technology fellow from Delft University of Technology, presented on this topic:

The purpose of any country’s healthcare system, whether it relies on a public or private provision model, is to ensure the health and well-being of its citizens. The use of technology is now an integral part of healthcare, and forms a substantial portion of its expenditure, and the medical device industry itself continues to grow to cater for its needs. But do we know what happens to health technologies (especially medical devices and equipment) once they are adopted into hospitals, GP practices, and specialist centres? Are they catering to the healthcare needs of patients? This presentation explores these questions and demonstrates some of the challenges in generating the needed evidence to provide answers.

On Nov. 22, 2021, Dr. Shen-yi Liao (from Puget Sound) and Dr. Lisa Carbonell (from University of Cincinnati) presented on this topic: 

It is well-known that racism is encoded into the social practices and institutions of medicine. Less well-known is that racism is encoded into the material artifacts of medicine. We argue that many medical tools and technologies are not merely biased, but oppressive.

An oppressive device exhibits a harmful bias that reflects and perpetuates unjust power relations. Using pulse oximeters and spirometers as case studies, we show how medical devices can materialize oppression along various axes of social difference, including race, gender, class, and ability. Our account uses political philosophy and cognitive science to give a theoretical basis for understanding materialized oppression, explaining how artifacts encode and carry oppressive ideas from the past to the present and future.

Oppressive medical devices present a moral aggregation problem. To remedy this problem, we suggest redundantly layered solutions that are coordinated to disrupt the causal nexus of oppression.

On March 23, 2021, Marlon Domingos, the Data Protection Officer at Erasmus University, presented on the following:

The GDPR facilitates both the protection of personal data as well as the free movement of such data, for instance for innovation and research purposes. However, in current collaborations the sector-specific interpretation of the GDPR open standards cause all kinds of uncertainties and delays. What are my responsibilities as a researcher and what is legally and ethically required of me, in the specific context of my research project? And how do I deal with risky research projects that are legally allowed, but would result in eyebrow raising, if made public.

Martin Sand, from the Ethics and Technology section, Delft University of Technology presented a co-authored paper on the following topic:

Despite worries about the explainability and accuracy of medical AI systems, it is reasonable to assume that they will be increasingly implemented in medical practice. Current ethical debates focus mainly on design requirements and suggest embedding certain values such as transparency, fairness, and explainability in the design of medical AI systems. Aside from concerns about their design, medical AI also raises questions about physician responsibilities once these technologies are implemented and used. How do physicians’ responsibilities change? Which set of competencies do physicians have to learn to responsibly interact with medical AI?