The integration of normative analysis with empirical data often remains unclear despite the availability of many empirical bioethics methodologies. This paper sought bioethics scholars’ experiences and reflections of doing empirical bioethics research to feed these practical insights into the debate on methods. We interviewed twenty-six participants who revealed their process of integrating the normative and the empirical. From the analysis of the data, we first used the themes to identify the methodological content. That is, we show participants’ use of familiar (...) methods explained as “back-and-forth” methods (reflective equilibrium), followed by dialogical methods where collaboration was seen as a better way of doing integration. Thereafter, we highlight methods that were deemed as inherent integration approaches, where the normative and the empirical were intertwined from the start of the research project. Second, we used the themes to express not only how we interpreted what was said but also how things were said. In this, we describe an air of uncertainty and overall vagueness that surrounded the above methods. We conclude that the indeterminacy of integration methods is a double-edged sword. It allows for flexibility but also risks obscuring a lack of understanding of the theoretical-methodological underpinnings of empirical bioethics research methods. (shrink)

Crashes involving self-driving cars at least superficially resemble trolley dilemmas. This article discusses what lessons machine ethicists working on the ethics of self-driving cars can learn from trolleyology. The article proceeds by providing an account of the trolley problem as a paradox and by distinguishing two types of solutions to the trolley problem. According to an optimistic solution, our case intuitions about trolley dilemmas are responding to morally relevant differences. The pessimistic solution denies that this is the case. An optimistic (...) solution would yield first-order moral insights for the ethics of self-driving cars, but such a solution is difficult to come by. More plausible is the pessimistic solution, and it teaches us a methodological lesson. The lesson is that machine ethicists should discount case intuitions and instead rely on intuitions and judgments at a higher level of generality. (shrink)