Dunja Šešelja
I'm a Professor for Social Epistemology and Reasoning in Science at the Institute for Philosophy II, Ruhr University Bochum (RUB). Together with Christian Straßer I lead the Research Group on Reasoning, Rationality and Science at RUB. I serve as an Editor-in-Chief of the European Journal for Philosophy of Science. My areas of expertise are social epistemology and philosophy of science, in particular formal modeling of scientific inquiry, social epistemology of scientific disagreements and controversies, and integrated history and philosophy of science.
Info about our research network on Simulations of Scientific Inquiry, funded by the DFG, can be found on this link: https://www.ruhr-uni-bochum.de/ssi-phil/
Previously, I held visiting professorships at the University of Vienna and Ghent University, and postdoc positions at Ghent University, Ruhr-University Bochum, and at MCMP, LMU Munich (with which I am still affiliated as an external member), and served as a Steering Committee member of the European Philosophy of Science Association (EPSA). Before taking the position at Ruhr University Bochum, I worked as an assistant professor at TU Eindhoven (with which I am still affiliated as an external member) on a tenure track.
(Photo by ©RUB, Marquard)
Info about our research network on Simulations of Scientific Inquiry, funded by the DFG, can be found on this link: https://www.ruhr-uni-bochum.de/ssi-phil/
Previously, I held visiting professorships at the University of Vienna and Ghent University, and postdoc positions at Ghent University, Ruhr-University Bochum, and at MCMP, LMU Munich (with which I am still affiliated as an external member), and served as a Steering Committee member of the European Philosophy of Science Association (EPSA). Before taking the position at Ruhr University Bochum, I worked as an assistant professor at TU Eindhoven (with which I am still affiliated as an external member) on a tenure track.
(Photo by ©RUB, Marquard)
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Papers by Dunja Šešelja
represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide epistemically opaque how-possibly explanations (Šešelja et al., 2022). While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry.
have been left out of these discussions. Examples of collectively preventable epistemic harms include a premature abandonment of a promising research program within a given scientific domain, or the prevalence of pernicious biases in a certain field of study. In this paper we propose an account of collective epistemic responsibility,
which fills this gap. Building on Hindriks’ (2018) account of collective moral responsibility, we introduce the Epistemic Duty to Join Forces. Our theory provides an account of the responsibilities of scientists to prevent epistemic harms during inquiry. It also suggests
fruitful appli- cations to other discussions, such as those concerning epistemic injustice and epistemically pernicious groups.
the mid-twentieth century was a large-scale study by a prominent gastroenterologist Palmer, which suggested no bacteria could be found in the human stomach. To this end, we employ the method of digital textual analysis and study the literature on the etiology of PUD published in the decade prior to Palmer’s article. Our findings suggest that the bacterial hypothesis had already been abandoned before the publication of Palmer’s paper, which challenges the widely held view that his study played a crucial role in the development of this episode. In view of this result, we argue that the PUD case does not illustrate harmful effects of a high degree of information flow, as it has frequently been claimed in the literature on network epistemology. Moreover, we argue that alternative examples of harmful effects of a high degree of information flow may be hard to find in the history of science.
(ABMs) suggest that a crucial factor conducive to efficient inquiry is what Zollman, 2010 has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories
lasting sufficiently long for the community to identify the best theory and
to converge on it. But what exactly generates transient diversity? And
is transient diversity a decisive factor when it comes to the efficiency of
inquiry? In this paper we examine the impact of different conditions on
the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature (such as different social networks and cautious decision-making), as well as some factors that have so far been neglected (such as evaluations underlying theory-choice performed by scientists). This study is obtained via an argumentation-based ABM (Borg et al., 2017, 2018). Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-60042-0 56.
represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide epistemically opaque how-possibly explanations (Šešelja et al., 2022). While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry.
have been left out of these discussions. Examples of collectively preventable epistemic harms include a premature abandonment of a promising research program within a given scientific domain, or the prevalence of pernicious biases in a certain field of study. In this paper we propose an account of collective epistemic responsibility,
which fills this gap. Building on Hindriks’ (2018) account of collective moral responsibility, we introduce the Epistemic Duty to Join Forces. Our theory provides an account of the responsibilities of scientists to prevent epistemic harms during inquiry. It also suggests
fruitful appli- cations to other discussions, such as those concerning epistemic injustice and epistemically pernicious groups.
the mid-twentieth century was a large-scale study by a prominent gastroenterologist Palmer, which suggested no bacteria could be found in the human stomach. To this end, we employ the method of digital textual analysis and study the literature on the etiology of PUD published in the decade prior to Palmer’s article. Our findings suggest that the bacterial hypothesis had already been abandoned before the publication of Palmer’s paper, which challenges the widely held view that his study played a crucial role in the development of this episode. In view of this result, we argue that the PUD case does not illustrate harmful effects of a high degree of information flow, as it has frequently been claimed in the literature on network epistemology. Moreover, we argue that alternative examples of harmful effects of a high degree of information flow may be hard to find in the history of science.
(ABMs) suggest that a crucial factor conducive to efficient inquiry is what Zollman, 2010 has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories
lasting sufficiently long for the community to identify the best theory and
to converge on it. But what exactly generates transient diversity? And
is transient diversity a decisive factor when it comes to the efficiency of
inquiry? In this paper we examine the impact of different conditions on
the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature (such as different social networks and cautious decision-making), as well as some factors that have so far been neglected (such as evaluations underlying theory-choice performed by scientists). This study is obtained via an argumentation-based ABM (Borg et al., 2017, 2018). Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-60042-0 56.
Part 1: General introduction to ABMs as a tool employed in social sciences and philosophy; Introduction to ABMs of scientific interaction.
Part 2: Argumentation-based ABM of scientific inquiry (ArgABM)
Part 3: Zooming in on ArgABM (https://github.com/g4v4g4i/ArgABM)
The code of our model can be found at https://github.com/daimpi/SocNetABM
Abstract:
In this talk we present an agent-based model (ABM) of scientific inquiry as a tool for investigating how different social networks impact the efficiency of scientists in acquiring knowledge. In contrast to other existing ABMs of science, our model aims to represent the argumentative dynamics that underlies scientific practice. To this end we employ abstract argumentation theory as the core design feature of the model. This helps to avoid a number of problematic idealizations which are present in other ABMs of science and which impede their relevance for the actual scientific practice.
UCL Department of Science and Technology Studies
Abstract:
A number of recent attempts at understanding the normative aspects of the division of cognitive labor via agent-based models (ABMs) have suggested that increased information flow among scientists is not necessarily beneficial for the efficiency of the scientific community in acquiring knowledge. Most prominently, Kevin Zollman has developed models which show that efficient knowledge acquisition by a scientific community requires either that the information flow among scientists be restricted or that scientists have extreme beliefs regarding their
pursued hypotheses. This conclusion poses a direct challenge to some of the central ideas in the literature on scientific diversity,
according to which interaction among scientists should be encouraged since it is conducive to scientific objectivity even if scientists do not hold extreme or biased views towards their respective inquiries.
In this paper I argue that i) Zollman's model rests on some
unwarranted assumptions about how scientists evaluate their hypotheses and how they respond to new evidence; and that ii) there are good reasons to suppose that changing these assumptions would significantly affect the results of the models relevant for the epistemic significance of interaction among scientists. I will illustrate my points by the same case study that Zollman uses to motivate his approach: the research on causes of peptic ulcer disease.
Finally, I show that similar problems can be identified in other ABMs that have been used to suggest that unrestricted information flow among scientists may be epistemically detrimental. While my arguments primarily aim to undercut the conclusions drawn from these ABMs, I also point to directions in which ABMs can be adjusted so that these problems are resolved.
Abstract:
A point often made in the literature on scientific pluralism is that interaction among scientists is a necessary condition for scientific objectivity. This stance has been challenged by Kevin Zollman. In view of a game-theoretic model Zollman has argued that an efficient acquisition of scientific knowledge requires either a restriction of the information flow among scientists or the scientists having extreme beliefs regarding their pursued hypotheses. In this paper I challenge some basic ideas underlying Zollman’s model by showing that it is based on unwarranted assumptions about how scientists evaluate their hypotheses and how they respond to new evidence.
Reading Committee: Prof. Dr. Tim De Mey, Erasmus University Rotterdam, Ghent University; Prof. Dr. Theo Kuipers University of Groningen; Prof. Dr. Thomas Nickles, University of Nevada at Reno; Prof. Dr. Dagmar Provijn, Ghent University; Prof. Dr. Maarten Van Dyck, Ghent University.
The manuscript available upon request.