In this paper I develop a concept of behavioural ecological individuality. Using findings from a case study which employed qualitative methods, I argue that individuality in behavioural ecology should be defined as phenotypic and ecological uniqueness, a concept that is operationalised in terms of individual differences such as animal personality and individual specialisation. This account make sense of how the term “individuality” is used in relation to intrapopulation variation in behavioural ecology. The concept of behavioural ecological individuality can sometimes be (...) used to identify individuals. It also shapes research agendas and methodological choices in behavioural ecology, leading researchers to account for individuals as sources of variation. Overall, this paper draws attention to a field that has been largely overlooked in philosophical discussions of biological individuality and highlights the importance of individual differences and uniqueness for individuality in behavioural ecology. (shrink)

Reasoning in medicine requires the critical use of a clinical methodology whose validity must be evaluated as well as its limits. In the last decade, an increasing amount of evidence has shown severe limitations and flaws in the conduct of prognostic studies. The main reason behind this fact is that prognostic judgments are at high risk of error. In this paper we investigate the pragmatic and illocutionary aspects of different forms of linguistic acts and judgments involved in clinical practice. More (...) specifically, we analyze the role of uncertainty with regard to ‘particular’ clinical judgments and its relation with ‘general’ evidence. Focusing on how prognostic judgments are formulated and justified, our main purpose is to highlight the explication, the structure and the limits of prognosis from a linguistic and epistemological perspective. (shrink)

Advanced AI systems are rapidly making their way into medical research and practice, and, arguably, it is only a matter of time before they will surpass human practitioners in terms of accuracy, reliability, and knowledge. If this is true, practitioners will have a prima facie epistemic and professional obligation to align their medical verdicts with those of advanced AI systems. However, in light of their complexity, these AI systems will often function as black boxes: the details of their contents, calculations, (...) and procedures cannot be meaningfully understood by human practitioners. When AI systems reach this level of complexity, we can also speak of black-box medicine. In this paper, we want to argue that black-box medicine conflicts with core ideals of patient-centered medicine. In particular, we claim, black-box medicine is not conducive for supporting informed decision-making based on shared information, shared deliberation, and shared mind between practitioner and patient. (shrink)