A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge (...) bioengineering scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

Scientific research is a highly complex and creative domain of human activity. In addition to its intrinsic value, understanding scientific thinking provides insight into the creative potential of human psychological capacities, as they are imbedded in rich social, material, and cultural environments. I discuss findings from my own investigations using two forms of qualitative research suited to studying scientific thinking as situated in context: cognitive-historical and cognitive-ethnographic.

A topic of special importance when it comes to responsibility and implicit bias is responsibility for knowledge. Are there strategies for becoming more responsible and respectful knowers? How might we work together, not just as individuals but members of collectives, to reduce the negative effects of bias on what we see and believe, as well as the wrongs associated with epistemic injustice? To explore these questions, Chapter 9 introduces the concept of epistemic responsibility, a set of practices developed through the (...) cultivation of basic epistemic virtues, such as open-mindedness, epistemic humility, and diligence that help knowers seek information about themselves, others, and the world. (shrink)

Moral distress is a well-documented phenomenon in the nursing profession, and increasingly thought to be implicated in a nation-wide nursing shortage in the US. First identified by the philosopher Andrew Jameton in 1984, moral distress has also proven resistant to various attempts to prevent its occurrence or at least mitigate its effects. While this would seem to be bad news for nurses and their patients, it is potentially good news for philosophical counselors, for whom there is both socially important and (...) philosophically interesting work to be done. In an effort to encourage such work, this paper explicates the philosophical (as opposed to more purely psychological or institutional) contours of the problem. A subsequent paper, titled 'A Philosophical Counseling Approach to Moral Distress,' will highlight ways in which such a response would differ from the strategies so far deployed within the nursing profession. (shrink)

Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...) is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)

Following Nancy Cartwright and others, I suggest that most (if not all) theories incorporate, or depend on, one or more idealizing assumptions. I then argue that such theories ought to be regimented as counterfactuals, the antecedents of which are simplifying assumptions. If this account of the logic form of theories is granted, then a serious problem arises for Bayesians concerning the prior probabilities of theories that have counterfactual form. If no such probabilities can be assigned, the the posterior probabilities (...) will be undefined, as the latter are defined in terms of the former. I argue here that the most plausible attempts to address the problem of probabilities of conditionals fail to help Bayesians, and, hence, that Bayesians are faced with a new problem. In so far as these proposed solutions fail, I argue that Bayesians must give up Bayesianism or accept the counterintuitive view that no theories that incorporate any idealizations have ever really been confirmed to any extent whatsoever. Moreover, as it appears that the latter horn of this dilemma is highly implausible, we are left with the conclusion that Bayesianism should be rejected, at least as it stands. (shrink)

In "The Virtues of Sharing" I defend two central theses: that sharing is our most overarching ethical ideal, and that virtue ethics is able to serve as a comprehensive and free-standing approach to moral theory. My arguments for these theses are intertwined, because they are also designed to show how a virtue-ethical theory that treats the "Will to Share" as the basis of moral agency helps to resolve the contemporary Justice/Care Debate.