Evidence map›Paper›PMID 42671735›Full record

ArticleAnnals of biomedical engineering2026

The Ethics of Prompting Large Language Models in Academic Publishing.

Timothy Daly, Jaime A Teixeira da Silva

Erratum issuedAbstract readLetter
PubMed Publisher
In one paragraph

Article in Annals of biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Timothy DalyBioethics Program, FLACSO Argentina, Buenos Aires, Argentina. tdaly@flacso.org.ar.ORCID http://orcid.org/0000-0003-1650-242X
Jaime A Teixeira da Silva, Ikenobe 3011-2, Miki, Kagawa-ken, 761-0799, Japan. jaimetex@yahoo.com.ORCID http://orcid.org/0000-0003-3299-2772

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here, we build on a letter published in 2023 in this journal ( https://doi.org/10.1007/s10439-023-03272-4 ) on prompt engineering for academic writing. Drawing on ethics literature, both new and old, we reflect on the prompting of large language models (LLMs) from three different moral perspectives: consequentialism (the ethics of outcomes), deontology (the ethics of duties), and virtue ethics (the ethics of character). While we recognize that human authors who prompt LLMs to derive text can simplify knowledge creation, the question becomes: are prompters equivalent to authors, and should they be rewarded as such? We push back against over-reliance on prompt engineering by arguing in favor of the craft of human draft as a task worth preserving in academia to encourage authors to retain control over published content that bears their name.

Indexed as

ChatbotsEthicsGenerative artificial intelligenceLarge language models

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.