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What We Do
What We Do
The MInD research group puts together theoretical and formal models of inference and decision-making with empirical approaches to the study of human reasoning and cognition. The aim is twofold: to better understand, and possibly improve, how people reason and make choices in different contexts, both in ordinary life and in science; and to clarify and strengthen the methodology and foundations of cognitive, behavioral, and social sciences.
Our approach is grounded both in contemporary philosophy of science and in current work in cognitive science, and aims at bridging these two research traditions. Recent research in cognitive and behavioral sciences is increasingly illuminating the basic mechanisms of human reasoning and cognition, as well as their limitations and systematic deviations from the normative theories of rational inference and decision-making as studied by logicians and philosophers. This raises interesting questions about human rationality and scientific reasoning in general, as well as about the foundations and methods of specific scientific disciplines.
Topics we work, or plan to work, on include:
Formal epistemology and philosophy of science:
Bayesian confirmation theory, truthlikeness theory, cognitive decision theory.
Philosophy of cognitive, behavioral, and social sciences, including neuroscience, (behavioral) economics, medicine, forensic science, statistics, machine learning, history, textual criticism, etc.
Philosophical issues in the foundations, epistemology, and the methodology of science: e.g., reverse inference, abduction, analogy, simplicity, replicability, explainability, etc.
Models of reasoning, inference and decision-making:
Heuristics and biases, ecological rationality, nudge theory.
Experts, science, and society: boosting scientific literacy, managing false and misleading information, assessing expert advice
Legal epistemology and cognitive biases in legal reasoning
ONGOING PROJECTS
Reasoning with hypotheses: Integrating logical, probabilistic, and experimental perspectives (PRIN project, funded by MUR 2024-2025)
Boosting intellectual humility to improve science communication in healthcare (funded by the John Templeton Foundation, 2023-2026)
NUTS (Nudge Unit Toscana per la Salute), joint IMT - ARS Toscana initiative
PAST PROJECTS
SpinGeVacS: Spinta gentile, vaccinazione anti-COVID-19 e salute pubblica (funded by Regione Toscana, 2021-2024)
Understanding public data: experts, decisions, epistemic values (PRO3 project, funded by MUR 2021-2023)
From Models to Decisions (PRIN project, funded by MUR 2024-2025)
Who We Are
Who We Are
ALICE ANDREA CHINAIA
PhD Student
MATTEO PIRISI
PhD Student
PIERO AVITABILE
PhD Student
TOBIA FOGARIN
PhD Student
RUGGERO RONI
PhD Student
MARGHERITA BIANCHETTI
PhD Student
Guest members
DARIO MENICAGLI
PhD
GIOVANNA MANCINI
PhD student
Past members
What We Publish
What We Publish
Closer to the target: a meta-theory of scientific progress
Gustavo Cevolani & Matteo De BenedettoPhilosophy of Science, forthcomingThe contemporary debate over scientific progress is fragmented into four competing, independent approaches, making systematic comparison difficult. To resolve this, we propose a formal meta-theory of progress, within which the different approaches can be represented and compared. Generalizing the formal core of truthlikeness theory, we develop a neutral meta-theory of “target-likeness”. We demonstrate how to represent the competing approaches as alternative measures of target-likeness. We conclude by discussing the implications and applications of our theory both inside and outside the current debate on scientific progress.
Truthlikeness and the inclusion fallacy
Gustavo Cevolani, Davide Coraci & Matteo De BenedettoThinking and Reasoning, 2025. DOI: 10.1080/13546783.2025.2575760In this paper, we offer a novel normative analysis of the inclusion fallacy. This refers to the robust tendency of experimental participants to reason about categories in a way that violates the laws of probability. In contrast to the received view, we argue that participants’ preferences in this kind of task might be rationally defended. To this purpose, we employ the philosophical notion of truthlikeness as a normative benchmark for category-based induction. Our analysis complements the main empirical findings and theoretical predictions of the psychological literature and it explains the difficulties that probabilistic models have in treating cases like the inclusion fallacy.
Conceptual Progress in Science: Cognitive Enhancement and Pragmatic Optimization
De Benedetto, M. Ergo: an Open Access Journal of Philosophy, forthcoming.This paper focuses on the nature of conceptual progress in science. Analyzing five historical episodes of conceptual progress in science, I will show that none of the existing philosophical theories of conceptual progress can make sense of all these cases. I will argue that this is because these theories try to capture conceptual progress as a single type of improvement. Instead, building upon recent cognitive science, I will propose a novel cognitive-pragmatic theory of conceptual progress that understands this phenomenon as involving two evaluative dimensions: cognitive enhancement and pragmatic optimization. While the former dimension assesses concepts in terms of their general cognitive utility, the latter assesses their optimization to the specific goals of the relevant scientific community. We will see that, thanks to these two dimensions, this theory is able to adequately characterize the diversity of conceptual progress exhibited by these historical episodes.
Our Collaborations
Our Collaborations
Center for Logic, Language, and Cognition (LLC) - University of Turin
The Center for Philosophy of Science - The Hong Kong University of Science and Technology
Center for Philosophy, Science, and Policy (CPSP) - Marche Polytechnic University
Game Science Research Center (Game.Sci Re.Center)
Vincenzo Crupi - University of Turin
Andrea Iacona - University of Turin
Carlo Martini - Università Vita Salute San Raffaele (Milan)
Stefania Pighin - University of Trento
Mario Piazza - Scuola Normale Superiore Pisa
Andrea Sereni - IUSS Pavia
Yafeng Shan - The Hong Kong University of Science and Technology
Jan Sprenger - University of Turin
Katya Tentori - University of Trento
Giovanni Valente - Politecnico di Milano
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