Work

Algorithmic Bias in Facial Recognition

Year: 2025

Type: article

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.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17215787

Author: Fathima, Yasmeen

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: green

OpenAlex ID: W7083580020

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