Evidence map›Paper›PMID 40421379›Full record

ReviewAI and ethics2025

The rise of checkbox AI ethics: a review.

Sara Kijewski, Elettra Ronchi, Effy Vayena

Abstract readReview
In one paragraph

Review in AI and 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. 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.

Sara KijewskiDepartment of Health Sciences and Technology, Chair of Bioethics, ETH Zurich, Zurich, Switzerland.ORCID 0000-0001-7781-7869
Elettra RonchiData and Digital Health Division of Country Health Policies and Systems World Health Organization Regional Office for Europe, Copenhagen, Denmark.ORCID 0009-0008-9818-0850
Effy VayenaDepartment of Health Sciences and Technology, Chair of Bioethics, ETH Zurich, Zurich, Switzerland.ORCID 0000-0003-1303-5467

Funding

World Health Organization 001
6 · The paper itself

Abstract

The rapid advancement of artificial intelligence (AI) sparked the development of principles and guidelines for ethical AI by a broad set of actors. Given the high-level nature of these principles, stakeholders seek practical guidance for their implementation in the development, deployment and use of AI, fueling the growth of practical approaches for ethical AI. This paper reviews, synthesizes and assesses current practical approaches for AI in health, examining their scope and potential to aid organizations in adopting ethical standards. We performed a scoping review of existing reviews in accordance with the PRISMA extension for scoping reviews (PRISMA-ScR), systematically searching databases and the web between February and May 2023. A total of 4284 documents were identified, of which 17 were included in the final analysis. Content analysis was performed on the final sample. We identified a highly heterogeneous ecosystem of approaches and a diverse use of terminology, a higher prevalence of approaches for certain stages of the AI lifecycle, reflecting the dominance of specific stakeholder groups in their development, and several barriers to the adoption of approaches. These findings underscore the necessity of a nuanced understanding of the implementation context for these approaches and that no one-size-fits-all approach exists for ethical AI. While common terminology is needed, this should not come at the cost of pluralism in available approaches. As governments signal interest in and develop practical approaches, significant effort remains to guarantee their validity, reliability, and efficacy as tools for governance across the AI lifecycle. Supplementary Information: The online version contains supplementary material available at 10.1007/s43681-024-00563-x.

Indexed as

AI ethicsArtificial intelligenceGovernanceHealthPractical approachesTools

Identifiers

PMID40421379
PMCPMC12103313

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.