AG Heinzelmann, 17.10.2025 Empirically Investigating the Concept of Lying?

In this talk, we will present three experiments on the concept of lying. The first two experiments address the question of whether a person can lie without saying anything false, while the third one tests whether people’s lie attributions are reliable or biased. In the first experiment, 5- and 8-year-old children as well as adults were presented with utterances intended to deceive but that were accidentally true, and were asked whether the speaker had lied. The second experiment is a cross-cultural study in which participants from ten countries were presented with deceptive implicatures (literally true statements implying something false) and asked whether the speaker had lied and whether they had said something true or false. The third experiment tested whether partisanship influenced lie attributions by asking Democrats and Republicans to judge whether a politician from their own or the opposing party had lied.

Alex Wiegmann is a Postdoctoral Researcher at the Georg‑Elias‑Müller Institute for Psychology, University of Göttingen and a Researcher at the University of Granada. He is part of a junior research group called EXTRA “Experimental Philosophy and the Method of Cases” until the end of this year. His research currently focuses on experimental philosophy, but he wrote his PhD on moral psychology and developed a causal model of transfer effects between moral dilemmas.

ResearchGate

Louisa  M. Reins is a cognitive psychology researcher at the University of Göttingen, specializing in the intersections of moral psychology and experimental philosophy. Her work focuses on the folk concept of lying, exploring how people judge deceptive implicatures, presuppositions, and actions across modalities and cultures, where she has collaborated together with Alex Wiegmann on various projects. Their scholarly output also includes investigations into partisan bias in judgments of misinformation, the experimental philosophy of lying, and the moral and legal reasoning capabilities of large language models.

ResearchGate