ARTIFICIAL INTELLIGENCE AND BIAS: CHALLENGES, IMPLICATIONS, AND REMEDIES

Paper

ARTIFICIAL INTELLIGENCE AND BIAS: CHALLENGES, IMPLICATIONS, AND REMEDIES

Published 2023 · Alfonso Min

UNKNOWN SJR score

8

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1

Influential Citations

Semantic Scholar

Abstract

This paper investigates the multifaceted issue of algorithmic bias in artificial intelligence (AI) systems and explores its ethical and human rights implications. The study encompasses a comprehensive analysis of AI bias, its causes, and potential remedies, with a particular focus on its impact on individuals and marginalized communities. The primary objectives of this research are to examine the concept of algorithmic bias, assess its ethical and human rights implications, identify its causes and mechanisms, evaluate its societal impact, explore mitigation strategies, and examine regulatory and community-driven approaches to address this critical issue. The research employs a multidisciplinary approach, drawing from literature reviews, case studies, and ethical analyses. It synthesizes insights from academic papers, governmental reports, and industry guidelines to construct a comprehensive overview of algorithmic bias and its ramifications. This research paper underscores the urgency of addressing algorithmic bias, as it raises profound ethical and human rights concerns. It advocates for comprehensive approaches, spanning technical, ethical, regulatory, and community-driven dimensions, to ensure that AI technologies respect the rights and dignity of individuals and communities in our increasingly AI-driven world.

Literature Review

Study Snapshot

Algorithmic bias in AI systems has significant ethical and human rights implications, requiring comprehensive approaches across technical, ethical, regulatory, and community-driven dimensions to ensure respect for individuals and communities.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

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ARTIFICIAL INTELLIGENCE AND BIAS: CHALLENGES, IMPLICATIONS, AND REMEDIES

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Citations

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