FAIR data principles and AI ethics: Exploring convergence and gaps

Anastasios G Papadiamantis; Iseult Lynch; Georgia Melagraki; Antreas Afantitis

doi:10.1177/2949799x251403108

FAIR data principles and AI ethics: Exploring convergence and gaps

Anastasios G Papadiamantis^*
, Iseult Lynch
, Georgia Melagraki
, Antreas Afantitis

^*Corresponding author for this work

Earth and Environmental Sciences

Research output: Contribution to journal › Comment/debate › peer-review

Abstract

Mapping AI-ethics frameworks to the FAIR principles and their extensions shows good conceptual alignment. While not directly referenced in AI-ethics frameworks, FAIR can enhance ethical AI use through traceability, accountability, auditability and transparent data governance.

Original language	English
Article number	2949799X251403108
Number of pages	6
Journal	FAIR Connect
Volume	3
DOIs	https://doi.org/10.1177/2949799x251403108
Publication status	Published - 16 Dec 2025

Keywords

ethics (http://purl.obolibrary.org/obo/NCIT_C39796)
machine learning (http://purl.obolibrary.org/obo/NCIT_C176231)
artificial intelligence (http://purl.obolibrary.org/obo/NCIT_C16309)
FAIR principles (http://purl.obolibrary.org/obo/T4FS_0000447)

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PapadiamantisAG2025FAIRFinal published version, 796 KBLicence: Creative Commons: Attribution (CC BY)

https://journals.sagepub.com/doi/10.1177/2949799X251403108Licence: Creative Commons: Attribution (CC BY)

Cite this

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title = "FAIR data principles and AI ethics: Exploring convergence and gaps",

abstract = "Mapping AI-ethics frameworks to the FAIR principles and their extensions shows good conceptual alignment. While not directly referenced in AI-ethics frameworks, FAIR can enhance ethical AI use through traceability, accountability, auditability and transparent data governance.",

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year = "2025",

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doi = "10.1177/2949799x251403108",

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T2 - Exploring convergence and gaps

AU - Papadiamantis, Anastasios G

AU - Lynch, Iseult

AU - Melagraki, Georgia

AU - Afantitis, Antreas

PY - 2025/12/16

Y1 - 2025/12/16

N2 - Mapping AI-ethics frameworks to the FAIR principles and their extensions shows good conceptual alignment. While not directly referenced in AI-ethics frameworks, FAIR can enhance ethical AI use through traceability, accountability, auditability and transparent data governance.

AB - Mapping AI-ethics frameworks to the FAIR principles and their extensions shows good conceptual alignment. While not directly referenced in AI-ethics frameworks, FAIR can enhance ethical AI use through traceability, accountability, auditability and transparent data governance.

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KW - machine learning (http://purl.obolibrary.org/obo/NCIT_C176231)

KW - artificial intelligence (http://purl.obolibrary.org/obo/NCIT_C16309)

KW - FAIR principles (http://purl.obolibrary.org/obo/T4FS_0000447)

U2 - 10.1177/2949799x251403108

DO - 10.1177/2949799x251403108

M3 - Comment/debate

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VL - 3

JO - FAIR Connect

JF - FAIR Connect

M1 - 2949799X251403108

ER -

FAIR data principles and AI ethics: Exploring convergence and gaps

Abstract

Keywords

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