ArticleFrontiers in artificial intelligence2024
Analyzing the European institutional response to ethical and regulatory challenges of artificial intelligence in addressing discriminatory bias.
Article in Frontiers in artificial intelligence, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Artificial intelligence based on forensic medical databases: construction, application, and prospects.Forensic science, medicine, and pathology · 2026Review
- Integrating big data and artificial intelligence to predict progression in multiple sclerosis: challenges and the path forward.Journal of neuroengineering and rehabilitation · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The European Union and some of its institutions have taken significant steps to address the challenges posed by the development and use of Artificial Intelligence (AI) in various contexts. The ubiquity of AI applications in everyday life, affecting both citizens and professionals, has made AI a common topic of discussion. However, as is evident from the documents analyzed here, concerns have been raised about the possible negative social consequences of AI, in particular discriminatory bias, making it a particularly relevant issue if people-centred, rights-based AI is to be implemented. This article aims to examine the challenges of defining, identifying and mitigating discriminatory bias in AI systems from two perspectives: (1) to conduct an ethical and normative review of European Commission documents from the last 8 years (from GDPR to AI Act regulation); and (2) to expose recommendations for key stakeholders, including designers, end-users and public authorities, to minimize/mitigate this risk. The document review was carried out on 21 EU regulatory and ethical guidelines in the field of AI, from which 152 measures were extracted, differentiated between design, governance and organizational measures. It has also been observed that there is no clear conceptual framework on the issue at the European level, showing a clear problem in providing definitions of algorithmic bias and discrimination, but not in assessing their potential negative impact on individuals. Secondly, these gaps may affect the concreteness and detail of the possible mitigation/minimization measures proposed and, subsequently, their application in different contexts. Finally, the last section of this paper presents a brief discussion and conclusions on possible issues related to the implementation of the measures extracted and certain limitations of the study.
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What OpenQuestion holds
Registered trials
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.