ArgLab • Reading Group

Frank Zenker

An argument scheme and critical questions for abductive argument

Introduced by Charles Sanders Peirce (1839–1914), ‘abduction’ refers to the creative generation of explanatory hypotheses. The term denotes an inference that is frequently employed, in some form or other, both in everyday and in scientific reasoning. With important exceptions and qualification, many scholars view abduction as the strongest candidate for a third top level inference-type besides deduction and induction (aka ‘reasoning of the third kind’) or assign to it a crucial role in scientific and common-sense reasoning. Whether abduction is treated as an argument or as an inference, the mainstream view presupposes a tight connection between abduction and inference to the best explanation (IBE).

This talk critically evaluates this link to support a narrower view on abduction, as laid out in Yu & Zenker (2018). We claim that merely the hypothesis-generative aspect, but not the evaluative aspect, is properly abductive in the sense introduced by C. S. Peirce. Equating abduction with IBE (or understanding them as inseparable parts) unnecessarily complicates argument evaluation by leveling the status of abduction as a third reasoning mode (besides deduction and induction). Besides proposing a scheme for abductive argument along with critical questions, we suggest retaining abduction alongside IBE as related but distinct categories.

Yu, S., Zenker, F. (2018). Peirce Knew Why Abduction Isn’t IBE – A Scheme and Critical Questions for Abductive Argument. Argumentation, 32, 569–587.

Frank Zenker (Bogazici University, Istanbul)

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The Argumentation Lab (ArgLab) organizes a reading group on Explainable Artificial Intelligence (XAI) and Inference to the Best Explanation (IBE). This reading group is part of the activities organized by the research group ANTIDOTE. The purpose of this reading group is to explore topics related, but not limited to, explanation in science and in language, methods of inquiry, and its application to artificial intelligence (explainability, interpretability, debugging, etc.). We will start reading classics in the literature on inference to the best explanation and move from there to more contemporary topics in AI and philosophy of science/language.

Each session will be led by a rapporteur, who will introduce the reading and spark discussion. Please write to if you are interested in taking part.