Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

ABSTRACTDeliberative and decisional groups play crucial roles in most aspects of social life. But it is not obvious how to organize these groups and various socio-cognitive mechanisms can spoil debates and decisions. In this paper we focus on one such important mechanism: the misrepresentation of views, i.e. when agents express views that are aligned with those already expressed, and which differ from their private opinions. We introduce a model to analyze the extent to which this behavioral pattern can warp deliberations (...) and distort the decisions that are finally taken. We identify types of situations in which misrepresentation can have major effects and investigate how to reduce these effects by adopting appropriate deliberative procedures. We discuss the beneficial effects of holding a sufficient number of rounds of expression of views; choosing an appropriate order of speech, typically a random one; rendering the deliberation dissenter-friendly; having agents express fined-grained views. These applicable procedures help improve deliberations because they dampen conformist behavior, give epistemic minorities more opportunities to be heard, and reduce the number of cases in which an inadequate consensus or majority develops. (shrink)

What is the epistemic position that a scientist must be in vis-à-vis a proposition, p, to be in a good enough epistemic position to assert that p to a fellow scientist within the scientific process? My aim is to provide an answer to this question and, more generally, to connect the epistemological debates about the epistemic norms of assertion to the debates about the nature of the scientific process. The question is important because science is a collaborative enterprise based on (...) a division of labor. It has even been suggested that such collaboration is a part of the scientific method. However, scientific collaboration depends upon communication between scientists—that is, intra-scientific testimony. After distinguishing some different kinds of intra-scientific testimony, I provide a specific proposal for an epistemic norm of assertion that generally governs such testimony. I argue that the proposal aligns with the requirements of three scientific virtues—replicability, revisability, and accountability. The discussion of replicability considers a prominent debate in the social and cognitive sciences. In conclusion, I consider some of the wider questions raised by characterizing scientific collaboration, division of labor, and more generally, scientific method via intra-scientific testimony. (shrink)

Although there has been a lot of investigation into the influence of the network structure of scientific communities on the one hand and into testimonial norms on the other, a discussion of TNs that take the network structure into account has been lacking. In this paper, I introduce two TNs which are sensitive to the local network structure. According to these norms, scientists should give less weight to the results of well-connected colleagues, as compared to less connected ones. I employ (...) an Agent Based Model to test the reliability of the two novel TNs against different versions of conventional, structure-insensitive TNs in networks of varying size and structure. The results of the simulations show that the novel TNs are more reliable. This suggests that it would be beneficial for scientific communities if their members followed such norms. For individual scientists, I show that there are both reasons for and reasons against adopting them. (shrink)

How we can reliably draw inferences from data, evidence and/or experience has been and continues to be a pressing question in everyday life, the sciences, politics and a number of branches in philosophy (traditional epistemology, social epistemology, formal epistemology, logic and philosophy of the sciences). In a world in which we can now longer fully rely on our experiences, interlocutors, measurement instruments, data collection and storage systems and even news outlets to draw reliable inferences, the issue becomes even more pressing. (...) While we were working on this question using a formal epistemology approach Landes and Osimani (2020); De Pretis et al. (2019); Osimani and Landes (2020); Osimani (2020), we realised that the width of current active interests in the notion of reliability was much broader than we initially thought. Given the breadth of approaches and angles present in philosophy (even in this journal Schubert 2012; Avigad 2021; Claveau and Grenier 2019; Kummerfeld and Danks 2014; Landes 2021; Trpin et al. 2021; Schippers 2014; Schindler 2011; Kelly et al. 2016; Mayo-Wilson 2014; Olsson and Schubert 2007; Pittard 2017), we thought that it would be beneficial to provide a forum for an open exchange of ideas, in which philosophers working in different paradigms could come together. Our call for expression of interest received a great variety of promised manuscripts, the variety is reflected in the published papers. They range from fields far away from our own interests such as quantum probabilities de Ronde et al. (2021), evolvable software systems Primiero et al. (2021), to topics closer to our own research in the philosophy of medicine Lalumera et al. (2020), psychology Dutilh et al. (2021), traditional epistemology Dunn (2021); Tolly (2021) to finally close shared interests in formal epistemology Romero and Sprenger (2021) even within our own department Merdes et al. (2021). Our job is now to reliably inform you about all the contributions in the papers in this special issue. Unfortunately, that task is beyond our capabilities. What we can and instead do is to summarise the contributed papers to inform your reliable inference to read them all in great detail. (shrink)

Science is a social epistemic enterprise. The complexity of research requires the division of cognitive labor. As a consequence, scientists have to present results and incorporate the results of others into their body of knowledge. This creates the possibility of strategic behavior, leading to phenomena such as publication bias. To analyze the dynamics of strategic behavior in epistemic communities, agent-based modeling suggests itself as a method. The phenomena generated by the developed agent-based simulation model reveal a diverse set of possible (...) dynamics in strategically heterogeneous groups and support the claim that there is a trade-off between a behavioral rule’s efficacy to generate accurate beliefs under optimal conditions and its robustness to variation in the composition of the epistemic environment. (shrink)

Given the importance of scientific research in shaping our perception of the world, and our senses of what policies will and won’t succeed in altering that world, it is of great practical, political, and moral importance that we carry out scientific research with integrity. The phenomenon of scientific fraud stands in the way of that, as scientists may knowingly enter claims they take to be false into the scientific literature, often knowingly doing so in defiance of norms they profess allegiance (...) to. In this chapter we take a look at some of the causes of scientific fraud, and how it might be manifested in large-scale research teams and situations of anonymous authorship. We find that such cases make trouble for what might seem like intuitive answers to the question “who should be held responsible for this fraud?”, and we argue that in such cases it would be better to hold the entire community responsible for seeing to it that there is less fraud. (shrink)