Evidence map›Paper›PMID 41429997›Full record

ArticleScience and engineering ethics2025

Does a Smarter ChatGPT Become More Utilitarian?

Jürgen Pfeffer, Sebastian Krügel, Matthias Uhl

Abstract read
In one paragraph

Article in Science and engineering ethics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Digital bioethics: exploring an emerging field.Medicine, health care, and philosophy · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jürgen PfefferTechnical University of Munich, TUM School of Social Sciences and Technology, Munich, Germany.
Sebastian KrügelFaculty of Business, Economics and Social Sciences, University of Hohenheim, Stuttgart, Germany.
Matthias UhlFaculty of Business, Economics and Social Sciences, University of Hohenheim, Stuttgart, Germany. matthias.uhl@uni-hohenheim.de.ORCID 0000-0002-8838-4824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hundreds of millions of users interact with large language models (LLMs) regularly to get advice on all aspects of life. The increase in LLMs' logical capabilities might be accompanied by unintended side effects with ethical implications. Focusing on recent model developments of ChatGPT, we can show clear evidence for a systematic shift in ethical stances that accompanied a leap in the models' logical capabilities. Specifically, as ChatGPT's capacity grows, it tends to give decisively more utilitarian answers to the two most famous dilemmas in ethics. Given the documented impact that LLMs have on users, we call for a research focus on the prevalence and dominance of ethical theories in LLMs as well as their potential shift over time. Moreover, our findings highlight the need for continuous monitoring and transparent public reporting of LLMs' moral reasoning to ensure their informed and responsible use.

Indexed as

Ethical TheoryLanguageLogicMoralsGenerative Artificial IntelligenceHumansChatGPTEthical theoriesLarge language modelsTrolley dilemmaUtilitarianism

Identifiers

PMID41429997
PMCPMC12748100

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.