Algorithmic Bias in Facial Recognition

This paper presents a self-directed research study investigating algorithmic bias in facial recognition systems. It examines how skin tone may influence recognition accuracy by testing a custom-labeled dataset of 100 publicly sourced facial images using freely available facial recognition tools. The paper follows a standard research format, including literature review, methodology, results, and discussion, and reflects an exploration of fairness, representation, and ethics in artificial intelligence.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-27
DOI
https://doi.org/10.5281/zenodo.17215787
Primary Topic
Plant Pathogens and Fungal Diseases
Type
article
Field-Weighted Citation Impact
0.00
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article

Algorithmic Bias in Facial Recognition

Zenodo (CERN European Organization for Nuclear Research)
Plant Pathogens and Fungal Diseases
article

Algorithmic Bias in Facial Recognition

article en

Abstract

This paper presents a self-directed research study investigating algorithmic bias in facial recognition systems. It examines how skin tone may influence recognition accuracy by testing a custom-labeled dataset of 100 publicly sourced facial images using freely available facial recognition tools. The paper follows a standard research format, including literature review, methodology, results, and discussion, and reflects an exploration of fairness, representation, and ethics in artificial intelligence.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 45%
Plant Pathogens and Fungal Diseases
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Algorithmic Bias in Facial Recognition · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS