FAIR data principles and AI ethics:Exploring convergence and gaps

Anastasios G. Papadiamantis; Iseult; id_orcid 0000-0003-4250-4584 Lynch; Georgia Melagraki; Antreas Afantitis

doi:10.1177/2949799x251403108

December 16, 2025Open Access

FAIR data principles and AI ethics:Exploring convergence and gaps

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Key Points

Investigate the alignment between FAIR data principles and AI ethics frameworks.
Mapped AI ethics frameworks to FAIR principles.
Analyzed enhancements in ethical AI use through FAIR principles.
Identified conceptual alignment between frameworks and principles.
FAIR principles align well with AI ethics frameworks conceptually.
Implementation of FAIR enhances traceability and accountability in AI.
Emphasized the need for transparent data governance in AI practices.

Implication

Exploration of FAIR principles enhances ethical AI use, indicating alignment with AI-ethics frameworks.

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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Cite This Study

Papadiamantis et al. (2025) studied this question.

synapsesocial.com/papers/698433d8f1d9ada3c1fb153f https://doi.org/10.1177/2949799x251403108

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FAIR data principles and AI ethics:Exploring convergence and gaps

Key Points

Implication

Abstract

Discussion

Cite This Study

FAIR data principles and AI ethics:Exploring convergence and gaps

Key Points

Implication

Abstract

Discussion

Cite This Study

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