A de minimis risk is defined as a risk that is so small that it may be legitimately ignored when making a decision. While ignoring small risks is common in our day-to-day decision making, attempts to introduce the notion of a de minimis risk into the framework of decision theory have run up against a series of well-known difficulties. In this paper, I will develop an enriched decision theoretic framework that is capable of overcoming two major obstacles to the modelling (...) of de minimis risk. The key move is to introduce, into decision theory, a non-probabilistic conception of risk known as normic risk. (shrink)

There is no large number of very small bads that is worse than a small number of very large bads – or so, some maintain, it seems plausible to say. In this article, I criticize and reject two recently proposed vindications of the above intuition put forth by Dale Dorsey and Alex Voorhoeve. Dorsey advocates for a threshold marked by the interference with a person's global life projects: any bad that interferes with the satisfaction of a life project is worse (...) than any number of bads that don't interfere with such a life project. Such thresholds, I argue, are broadly implausible. Voorhoeve gives a contractualist account for the irrelevance of minor bads. His account, I argue, does not, among other things, provide the right kind of reason in defence of the above intuition. (shrink)

Medical devices with built-in bias can both result from, and contribute to, harmful systemic racial oppression—a point that Liao and Carbonell (2023) argue convincingly in the target article of thi...

Women are under-represented in surgery, especially in leadership and academic roles, and face a gender pay gap. There has been little work on the role of implicit biases in women’s under-representation in surgery. Nor has the impact of epistemic injustice, whereby stereotyping influences knowledge or credibility judgements, been explored. This article reports findings of a qualitative in-depth interview study with women surgeons that investigates gender biases in surgery, including subtle types of bias. The study was conducted with 46 women surgeons (...) and trainees of the Royal Australasian College of Surgeons. Maximum variance sampling strategies ensured a comprehensive set of perspectives. Data were analysed using iterative thematic analysis to document and classify forms of gender bias experienced by the participants, including implicit bias and epistemic injustice. It found four types of bias affecting women surgeons: workplace factors such as access to parental leave and role models; epistemic injustices—unfair assessments of women surgeons’ credibility by patients and colleagues; stereotyped expectations that they will carry out more of surgery’s carework, such as meeting the emotional needs of patients and objectification. Implicit biases arose in each category. Given that many of the biases identified in this study are small, are harmless on their own and are not necessarily under anyone’s conscious control, important questions arise regarding how they cause harm and how to address them. I draw on theoretical work on cumulative harm to answer these questions. (shrink)

In this article, I describe how gender bias can affect the design, testing, clinical trials, regulatory approval, and clinical use of implantable devices. I argue that bad outcomes experienced by women patients are a cumulative consequence of small biases and inattention at various points of the design, testing, and regulatory process. However, specific instances of inattention and bias can be difficult to identify, and risks are difficult to predict. This means that even if systematic gender bias in implant design is (...) an ethical issue, it is one with no clearly blameworthy player. From a practical perspective, there is no single obvious point at which to intervene. Philosophers working in other areas have explored structurally similar moral problems—sometimes referred to as “moral aggregation problems”—such as the type of environmental harm caused by small actions of many players. I describe key features of these type of problems and strategies to address them. I then draw on these to suggest an approach to gender bias in medical implant design and use. (shrink)