We argue that there is a large class of questions—specifically questions about how to epistemically evaluate environments that currently available epistemic theories are not well-suited for answering, precisely because these questions are not about the epistemic state of particular agents or groups. For example, if we critique Facebook for being conducive to the spread of misinformation, then we are not thereby critiquing Facebook for being irrational, or lacking knowledge, or failing to testify truthfully. Instead, we are saying something about the (...) social media environment. In this paper, we first propose that a new branch of epistemology–Environmental Epistemology–is needed to address these questions. We argue that environments can be proper objects of epistemic evaluation, and that there are genuine epistemic norms that govern environments. We then provide a positive account of these norms and conclude by considering how recognition of these norms may require us to rethink longstanding epistemic debates. (shrink)

Evolutionary anthropologists and archaeologists have been considerably successful in modelling the cumulative evolution of culture, of technological skills and knowledge in particular. Recently, one of these models has been introduced in the philosophy of science by De Cruz and De Smedt (Philos Stud 157:411–429, 2012), in an attempt to demonstrate that scientists may collectively come to hold more truth-approximating beliefs, despite the cognitive biases which they individually are known to be subject to. Here we identify a major shortcoming in that (...) attempt: De Cruz & De Smedt’s mathematical model makes one particularly strong tractability assumption that causes the model to largely miss its target (namely, truth accumulation in science), and that moreover conflicts with empirical observations. The second, more constructive part of the paper presents an alternative, agent-based model, which allows one to much better examine the conditions for scientific progress and decline. (shrink)

ABSTRACT The emerging consensus in the secondary literature on Duhem is that his notion of ‘good sense’ is a virtue of individual scientists that guides them choosie between empirically equal rival theories : 149–159; Ivanova 2010. “Pierre Duhem’s Good Sense as a Guide to Theory Choice.” Studies in History and Philosophy of Science Part A 41 : 58–64; Fairweather 2011. “The Epistemic Value of Good Sense.” Studies in History and Philosophy of Science Part A 43 : 139–146; Bhakthavatsalam. “Duhemian Good (...) Sense and Agent Reliabilism.” Studies in History and Philosophy of Science Part A 64: 22–29). In this paper, I argue that good sense is irrelevant for theory choice within Duhem’s conception of scientific methodology. Theory choice, for Duhem, is either a pseudo-problem or addressed purely by empirical and formal desiderata depending on how it is understood. I go on to provide a positive interpretation of good sense as a feature of scientific communities that undergo particular forms of education that allow scientists to abandon theory pursuit. I conclude by suggesting that this interpretation entails that virtue epistemological readings of Duhem are insufficient for understanding good sense; we must employ a social epistemological perspective. (shrink)

International Journal of Philosophical Studies, Volume 20, Issue 2, Page 271-287, May 2012.

Judgment aggregation problems are language dependent in that they may be framed in different yet equivalent ways. We formalize this dependence via the notion of translation invariance, adopted from the philosophy of science, and we argue for the normative desirability of translation invariance. We characterize the class of translation invariant aggregation functions in the canonical judgment aggregation model, which requires collective judgments to be complete. Since there are reasonable translation invariant aggregation functions, our result can be viewed as a possibility (...) theorem. At the same time, we show that translation invariance does have certain normatively undesirable consequences (e.g. failure of anonymity). We present a way of circumventing them by moving to a more general model of judgment aggregation, one that allows for incomplete collective judgments. (shrink)