The National Science Foundation (NSF) in the United States, like many other funding agencies all over the globe, has made large investments in interdisciplinary research in the sciences and engineering, arguing that interdisciplinary research is an essential resource for addressing emerging problems, resulting in important social benefits. Using NSF as a case study for problem that might be relevant in other contexts as well, I argue that the NSF itself poses a significant barrier to such research in not sufficiently appreciating (...) the value of the humanities as significant interdisciplinary partners. This essay focuses on the practices of philosophy as a highly valuable but currently under-appreciated partner in achieving the goals of interdisciplinary research. This essay advances a proposal for developing deeper and wider interdisciplinary research in the sciences through coupled ethical-epistemological research. I argue that this more robust model of interdisciplinary practice will lead to better science by providing resources for understanding the types of value decisions that are entrenched in research models and methods, offering resources for identifying the ethical implications of research decisions, and providing a lens for identifying the questions that are ignored, under-examined, and rendered invisible through scientific habit or lack of interest. In this way, we will have better science both in the traditional sense of advancing knowledge by building on and adding to our current knowledge as well as in the broader sense of science for the good of, namely, scientific research that better benefits society. (shrink)

Sustainability science seeks to extend scientific investigation into domains characterized by a distinct problem-solving agenda, physical and social complexity, and complex moral and ethical landscapes. In this endeavor it arguably pushes scientific investigation beyond its usual comfort zones, raising fundamental issues about how best to structure such investigation. Philosophers of science have long scrutinized the structure of science and scientific practices, and the conditions under which they operate effectively. We propose a critical engagement between sustainability scientists and philosophers of science (...) with respect to how to engage in scientific activity in these complex domains. We identify specific issues philosophers of science raise concerning current sustainability science and the contributions philosophers can make to resolving them. In conclusion we reflect on the steps philosophers of science could take to advance sustainability science. (shrink)

Research on interdisciplinary science has for the most part concentrated on the institutional obstacles that discourage or hamper interdisciplinary work, with the expectation that interdisciplinary interaction can be improved through institutional reform strategies such as through reform of peer review systems. However institutional obstacles are not the only ones that confront interdisciplinary work. The design of policy strategies would benefit from more detailed investigation into the particular cognitive constraints, including the methodological and conceptual barriers, which also confront attempts to work (...) across disciplinary boundaries. Lessons from cognitive science and anthropological studies of labs in sociology of science suggest that scientific practices may be very domain specific, where domain specificity is an essential aspect of science that enables researchers to solve complex problems in a cognitively manageable way. The limit or extent of domain specificity in scientific practice, and how it constrains interdisciplinary research, is not yet fully understood, which attests to an important role for philosophers of science in the study of interdisciplinary science. This paper draws upon two cases of interdisciplinary collaboration; those between ecologists and economists, and those between molecular biologists and systems biologists, to illustrate some of the cognitive barriers which have contributed to failures and difficulties of interactions between these fields. Each exemplify some aspect of domain specificity in scientific practice and show how such specificity may constrain interdisciplinary work. (shrink)

In this paper we take a close look at current interdisciplinary modeling practices in the environmental sciences, and suggest that closer attention needs to be paid to the nature of scientific practices when investigating and planning interdisciplinarity. While interdisciplinarity is often portrayed as a medium of novel and transformative methodological work, current modeling strategies in the environmental sciences are conservative, avoiding methodological conflict, while confining interdisciplinary interactions to a relatively small set of pre-existing modeling frameworks and strategies (a process we (...) call crystallization). We argue that such practices can be rationalized as responses in part to cognitive constraints which restrict interdisciplinary work. We identify four salient integrative modeling strategies in environmental sciences, and argue that this crystallization, while contradicting somewhat the novel goals many have for interdisciplinarity, makes sense when considered in the light of common disciplinary practices and cognitive constraints. These results provide cause to rethink in more concrete methodological terms what interdisciplinarity amounts to, and what kinds of interdisciplinarity are obtainable in the environmental sciences and elsewhere. (shrink)

Environmental problems often outstrip the abilities of any single scientist to understand, much less address them. As a result, collaborations within, across, and beyond the environmental sciences are an increasingly important part of the environmental science landscape. Here, we explore an insufficiently recognized and particularly challenging barrier to collaborative environmental science: value pluralism, the presence of non-trivial differences in the values that collaborators bring to bear on project decisions. We argue that resolving the obstacles posed by value pluralism to collaborative (...) environmental science requires detecting and coordinating the underlying problematic value differences. We identify five ways that a team might coordinate their problematic value differences and argue that, whichever mode is adopted, it ought to be governed by participatory virtues, pragmatic resolve, and moral concern. Relying on our experiences with the Toolbox Dialogue Initiative, as well as with other dialogical approaches that support team inquiry, we defend the claim that philosophical dialogue among collaborators can go a long way towards helping teams of environmental scientists and fellow travelers detect their problematic value differences. Where dialogical approaches fare less well is in helping teams coordinate these differences. We close by describing several principles for augmenting philosophical dialogue with other methods, and we list several of these methods in an appendix with brief descriptions and links for further learning. Overall, the article makes three main contributions to the research collaboration and values in science literatures: It deepens our understanding of problematic value pluralism in team science; It provides actionable guidance and methods for improving values-oriented philosophical dialogue interventions; and It demonstrates one way of doing engaged philosophy. (shrink)

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...

We argue that non-epistemic values, including moral ones, play an important role in the construction and choice of models in science and engineering. Our main claim is that non-epistemic values are not only “secondary values” that become important just in case epistemic values leave some issues open. Our point is, on the contrary, that non-epistemic values are as important as epistemic ones when engineers seek to develop the best model of a process or problem. The upshot is that models are (...) neither value-free, nor depend exclusively on epistemic values or use non-epistemic values as tie-breakers. (shrink)

Complex environmental problems require well-researched policies that integrate knowledge from both the natural and social sciences. Epistemic differences can impede interdisciplinary collaboration, as shown by debates between conservation biologists and anthropologists who are working to preserve biological diversity and support economic development in central Africa. Disciplinary differences with regard to 1) facts, 2) rigor, 3) causal explanation, and 4) research goals reinforce each other, such that early decisions about how to define concepts or which methods to adopt may tilt research (...) design and data interpretation toward one discipline’s epistemological framework. If one of the contributing fields imposes a solution to an epistemic problem, this sets the stage for what I call disciplinary capture. Avoiding disciplinary capture requires clear communication between collaborators, but beyond this it also requires that collaborators craft research questions and innovate research designs which are different from the inherited epistemological frameworks of contributing disciplines. (shrink)

When developing computational models to analyze the tradeoffs between climate risk management strategies (i.e., mitigation, adaptation, or geoengineering), scientists make explicit and implicit decisions that are influenced by their beliefs, values and preferences. Model descriptions typically include only the explicit decisions and are silent on value judgments that may explain these decisions. Eliciting scientists’ mental models, a systematic approach to determining how they think about climate risk management, can help to gain a clearer understanding of their modeling decisions. In order (...) to identify and represent the role of values, beliefs and preferences on decisions, we used an augmented mental models research approach, namely values-informed mental models (ViMM). We conducted and qualitatively analyzed interviews with eleven climate risk management scientists. Our results suggest that these scientists use a similar decision framework to each other to think about modeling climate risk management tradeoffs, including eight specific decisions ranging from defining the model objectives to evaluating the model’s results. The influence of values on these decisions varied between our scientists and between the specific decisions. For instance, scientists invoked ethical values (e.g., concerns about human welfare) when defining objectives, but epistemic values (e.g., concerns about model consistency) were more influential when evaluating model results. ViMM can (i) enable insights that can inform the design of new computational models and (ii) make value judgments explicit and more inclusive of relevant values. This transparency can help model users to better discern the relevance of model results to their own decision framing and concerns. (shrink)