Neele Engelmann

Neele Engelmann

Cognitive Scientist

Max Planck Institute for Human Development (Berlin), Center for Humans and Machines

Biography

I’m a postdoctoral researcher at Max Planck Institute for Human Development, Center for Humans and Machines in Berlin, Germany. I obtained my Ph.D. in Psychology from Georg-August-University Göttingen in 2022, with a project focusing on the role of causal representations in moral judgment. Before my current position, I was a postdoc at the Center for Law, Behaviour, and Cognition at Ruhr-University Bochum, Germany. My research interests lie at the intersection of psychology, philosophy, and law.

CV

Interests

  • Moral Psychology
  • Human-AI interaction
  • Causal Reasoning
  • Experimental Philosophy
  • Experimental Jurisprudence
  • Computational Modelling
  • Open Science

Education

  • Dr. rer. nat. Psychology, 2022

    Georg-August-University Göttingen, Germany

  • M.Sc. Psychology, 2017

    Georg-August-University Göttingen, Germany

  • B.Sc. Psychology, 2014

    Georg-August-University Göttingen, Germany

Publications

click title for abstracts

(2024). Apply the laws, if they are good: Moral evaluations linearly predict whether judges should apply the law. [submitted].

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(2024). Exploring the psychology of GPT-4's moral and legal reasoning. Artificial Intelligence (333), 104145.

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(2024). Does moral valence influence the construal of alternative possibilities?. Possibility Studies & Society.

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(2024). Understanding rule enforcement using drift diffusion models. Proceedings of the Annual Meeting of the Cognitive Science Society (46).

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(2023). Who Caused It? Different Effects of Statistical and Prescriptive Abnormality on Causal Selection in Chains. In K. Tobia (Ed): The Cambridge Handbook of Experimental Jurisprudence. Cambridge University Press [in press].

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(2023). The perceived dilution of causal strength. Cognitive Psychology, 140, 101540.

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(2023). Murderer at the door! To lie or to mislead?. In A. Wiegmann (Ed): Lying, fake news, and bullshit. Bloomsbury [in press].

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(2022). Is lying morally different from misleading? An empirical investigation. In L. Horn (Ed): From lying to perjury: Linguistic and legal perspectives on lies and other falsehoods. De Gruyter.

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(2022). How to weigh lives. A computational model of moral judgment in multiple-outcome structures. Cognition, 218, 104910.

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(2022). How causal structure, causal strength, and foreseeability affect moral judgments. Cognition, 226, 105167.

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(2021). Can a question be a lie? An empirical investigation. Ergo, an Open Access Journal of Philosophy, 8:7.

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(2021). A causal proximity effect in moral judgment. Proceedings of the Annual Meeting of the Cognitive Science Society (43).

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(2020). Entwicklungen und Probleme der Moralpsychologie zu Beginn des 21. Jahrhunderts. In N. Paulo & J. C. Bublitz (Hgs.): Empirische Ethik - Grundlagentexte aus Psychologie und Philosophie (pp. 139-175). Suhrkamp Verlag, Berlin.

(2020). Asking questions to provide a causal explanation – Do people search for the information required by cognitive psychological theories?. In E. A. Bar-Asher Siegal & Boneh N. (Eds): Perspectives on Causation (pp. 121-147). Springer, Cham.

(2019). Moral reasoning with multiple effects: Justification and moral responsibility for side effects. Proceedings of the Annual Meeting of the Cognitive Science Society 41 (pp. 1703-1709).

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(2014). Foraging for alternatives: ecological rationality in keeping options viable. Proceedings of the Annual Meeting of the Cognitive Science Society 36.

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Teaching & Supervision

I have been co-teaching introductory statistics since winter 2017, leading practical exercise and discussion sessions for first-year psychology students. The seminar “Quantitative Methods I” covers basics of research design and hypothesis testing, data visualisation, probability theory, descriptive and inferential data analysis, and power analyses. Practical exercises are held using MS Excel. “Quantitative Methods II” focuses on the General Linear Model and its various applications (multiple linear regression and its assumptions, ANOVA, contrast analyses, logistic regression, multilevel models). The practical exercises are conducted in R and RStudio.

  • Winter 2021/22: Quantitative Methods I
  • Summer 2021: Quantitative Methods II
  • Winter 2020/21: Quantitative Methods I
  • Summer 2020: Quantitative Methods II
  • Winter 2019/20: Quantitative Methods I
  • Summer 2019: Quantitative Methods II
  • Winter 2018/19: Quantitative Methods I
  • Summer 2018: Quantitative Methods II
  • Winter 2017/18: Quantitative Methods I

In addition, I have supervised and co-supervised a number of empirical Bachelor and Master projects in the fields of causal and moral reasoning and experimental philosophy.