Presenters
Pei-hua Huang
Samantha Copeland
Kind of session / presentation

Convergence Ethics

Bioethics traditionally focuses on normative questions related to medical practice. The inquiry involves the moral permissibility of using new technologies for medical purpose and also existing medical technologies for non-medical purpose. While these inquiries probe into the ethical issues raised by the medical technologies, they take a rather reactive attitude towards the application of technologies. These inquiries limit themselves to the applications of the technologies; they do not venture into the design of these technologies nor provide critiques over how these technologies ought to be designed – such tasks are for ethics of technology. However, more and more studies have shown that ill-designed medical technologies can worsen health inequality or even bring in oppression, there’s an increasing need to take a more proactive measures to address ethical risks as early as possible. 

In this paper, we argue that as the medical sector becomes ever more technology-intensive, it is vital to proactively address ethical risks during the development phase of the technology by converging bioethics and the ethics of technology. Capitalised on insight from responsible innovation, we develop a convergence ethics approach to medical technology. We use digital twin for healthcare and deep brain stimulation as our key cases to demonstrate how to apply this approach to address ethical concerns during the development stage.

In particular, we will focus on two implications of this ‘convergence’ in this session. Taking into consideration both ethics of technology and bioethics, we suggest that the grounding distinction between research and practice found in bioethics must be tempered with the interactive and value-driven approaches to design and innovation from ethics of technology approaches. This results in a reshaping of how we think about participants in medical research. Drawing from examples in experimental neurotechology and the use of data in machine learning approaches to medical research and intervention, we highlight how the relationship between researcher and research subject ought to be reconsidered in order to address contemporary ethical issues raised by technologies in health research and care contexts.