I received my PhD in philosophy from Humboldt University in Berlin. My work is concerned with foundational issues of scientific explanations, and it has been published in the world leading philosophy journals such as Philosophy of Science and Synthese, as well as in some of the top-tier biology and neuroscience journals such as the Philosophical Transactions of the Royal Society B: Biological Sciences, and Frontiers in Systems Neuroscience, Frontiers in Psychiatry. My work is thoroughly informed by science and interdisciplinary, and I even use empirical methods such as bibliometrics and text mining to understand the explanatory landscape and dynamics of neuroscience.
Fields of interest
- scientific explanations
- pragmatics of AI
- science and technology studies
In the last six years I developed the systematic and comprehensive account of the so-called topological or network explanations. My account provides necessary and sufficient conditions under which network models provide genuine explanations. The first condition ensures proper scientific explananda and explanantia. The second condition secures explanatoriness, i.e., it captures counterfactual dependency relations. Finally, the third condition provides contextual criteria for using the counterfactual, which emerge from different question asking perspectives.
This last condition is the core of my account of the pragmatics of explanation. It is based on the idea that certain perspectival inferential patterns determine both the explanation seeking questions and the space of possible answers to them. On this view, explanations are answers to why-questions. Why-questions can be conclusions in (erotetic) arguments that show how a question arises from certain contexts. Why-questions derived in this way, restrict the range of possible direct answers to them. The idea is that perspectival information determines explanatory relevance of an answer to a why-question just in case the perspectival information (erotetically) implies the question.
A general account of pragmatics of explanation is particularly needed, especially when it comes to AI systems, which are often used in data-driven decision-making without an explanation of how the AI makes those decisions. This explanatory opacity of AI is only partly a result of its profound complexity. The other part of the opacity problem stems from using explanatory norms that are too permissive, too restrictive, or incommensurable. I develop a heuristic for explainable AI which can deal with both the complexity of AI and plurality of explanatory norms.
The account of pragmatics of explanation connects various contexts from which explainability questions arise to relevant explanatory norms.
Grants and awards
2023 - Leiden University Fund, a grant for participation at the 5th Annual Workshop Scientific Understanding and Representation (SURe) in Toronto, Canada. Total amount: € 1000.
2020-2022 - Radboud Excellence Initiative Fellowship (Radboud Excellence Initiative). Total amount: € 205.300.
2016-2018 - Marie Skłodowska-Curie Fellowship (EU’s H2020-MSCA-IF-2015 Programme). Total amount: € 185.076.
2007-2011 - Villigst-Doctoral Scholarship. Total amount: € 41.400.
•PhD in philosophy from Humboldt University in Berlin (Germany).
• 24 publications, in some of the world leading philosophy journals such as Philosophy of Science, Synthese, as well as in top tier science journals such as Philosophical Transactions of the Royal Society B: Biological Sciences, Frontiers in Systems Neuroscience, Frontiers in Psychiatry.
• Very strong teaching and tutoring profile, with excellent student evaluations and colleagues’ commendations, and already obtained Dutch University Teaching Qualification (BKO).
• Co-founder and coordinator of the “Dutch Distinguished Lecture Series in Philosophy and Neuroscience (DDLS)” as well as of the annual workshop series “Scientific Understanding and Representation (SURe)”.
• Very strong track record of successful funding applications (total: € 454.573), including the Marie Skłodowska-Curie grant of the EU’s Horizon 2020 Programme.
• Internationally established, as evidenced by numerous invitations to serve as an evaluator for major international funding programmes (e.g., the NSF of the USA, Dutch NWO VENI program, START Program of the FWF Austrian Science Fund); to be a referee in leading philosophy and science journals (e.g., Philosophy of Science, Analysis, Synthese, Neuroimage); and to serve on the program committees of international conferences and workshops.
1. Kostic, D. (2022). “Topological Explanations, an Opinionated Appraisal.” In Lawler, I., Shech, E. and Khalifa, K. (eds): Scientific Understanding and Representation: Mathematical Modeling in the Life and Physical Sciences, Routledge, pp. 96-115. DOI: 10.4324/9781003202905-9.
2. Kostic, D. and Khalifa, K. (2022). "Decoupling Topological Explanations from Mechanisms.” Philosophy of Science (2022), 22, 1–24 doi:10.1017/psa.2022.29.
3. Kostic, D. and Khalifa, K. (2021) “The Directionality of Topological Explanations.” Synthese, 199, 14143–14165 (2021). https://doi.org/10.1007/s11229-021-03414-y.
4. Kostic, D. (2020). “General Theory of Topological Explanations and Explanatory Asymmetry”. Philosophical Transactions of the Royal Society B: Biological Sciences, 375: 20190321.
5. Kostic, D. (2018). “The Topological Realization”. Synthese, 195(1), 79-98.
- Kostic D. & Khalifa K. (2023), Decoupling topological explanations from mechanisms, Philosophy of Science 90(2): 245-268.
- Khalifa K., Islam, F., Gamboa J.P., Wilkenfeld D. & Kostić D. (2022), Integrating philosophy of understanding with the cognitive sciences, Frontiers in Systems Neuroscience 16: .
- Kostić D. (2022), Topological explanations: an opinionated appraisal. In: Lawler I., Shech E. & Khalifa K. (Eds.), Scientific understanding and representation: mathematical modeling in the life and physical sciences: Routledge. 96-115.
- Boer N.S. de, Kostic D., Ross M., Bruin L. de & Glas G. (2022), Using network models in person-centered care in psychiatry: how perspectivism could help to draw boundaries, Frontiers in Psychiatry 13.
- Kostić D. & Khalifa K. (2021), The directionality of topological explanations, Synthese 199: 14143–14165.
- Kostic D., Hilgetag C. & Tittgemeyer M. (2020), Unifying the essential concepts of biological networks: biological insights and philosophical foundations, Philosophical transactions of the Royal Society of London. Series B, Biological sciences 375(1796): .
- Kostić D. (2020), General theory of topological explanations and explanatory asymmetry, Philosophical Transactions of the Royal Society B: Biological Sciences 375(1796): 20190321.
- Kostić D. (2019), Minimal structure explanations, scientific understanding and explanatory depth, 27(1): 48-67.
- Kostic D. (2019), Unifying the debates: mathematical and non-causal explanations, Perspectives on Science 27(1): 1-6.
- Kostić D. (2018), Guest editor: Mechanistic and topological explanations. Synthese 195(1).
- Kostić D. (2018), The topological realization, Synthese 195(1): 79-98.
- Kostic D. (2018), The ultimate articulation of the account of explanatory understanding Review of: Khalifa K. (2017) Understanding, explanation, and scientific knowledge, Metascience 28: 61-64.
- Kostić D. (2017), Explanatory perspectivalism: limiting the scope of the hard problem of consciousness, Topoi 36(1): 119-125.
- Kostić D. (2016), Mechanistic and topological explanations: an introduction, Synthese 195(1): 1-10.
- Kostić D. (2012), The explanatory gap problem: how neuroscience might contribute to its solution. Berlin: Universitätsbibliothek der Humboldt-Universität zu Berlin.
- Kostić D. (2012), Osnove transparentnosti objašnjenja: semanticka realizacija, Treci program 156(4): 1-12.
- Kostić D. (2011), The explanatory gap account and intelligibility of explanation, Theoria Beograd 54(3): 27-42.
- Kostić D. (2011), The two-dimensional argument against physicalism and the conceptual analysis, Belgrade Philosophical Annual 24: 5-17.
- Kostic D. (2011), The vagueness constraint and the quality space for pain, Philosophical Psychology 25(6): 929-939.
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