Addressing Bias and Fairness Issues in Artificial Intelligence

Pragya Gupta

artificial intelligence, bias, fairness, algorithmic bias, machine learning, societal inequalities, diversity, ethical frameworks.

This paper explores the multifaceted aspects of bias in AI, encompassing its types, sources, implications, and mitigation strategies. Drawing on real-world examples, it delves into reporting bias, selection bias, group attribution bias, and implicit bias, highlighting their impact on societal inequalities and marginalized groups. The reinforcement of historical biases in AI training data perpetuates discrimination and hampers progress towards equality. The paper discusses quantitative measures like disparate impact and demographic parity, while emphasizing the vital role of qualitative assessments and human evaluators in identifying bias. Furthermore, it explores strategies for addressing bias, such as diverse training data, in-processing and post-processing models, and algorithmic debiasing techniques. The article also underscores interdisciplinary collaboration, ethical considerations, and regulatory standards as essential components of building fair and accountable AI systems. Lastly, it outlines future directions for research, including adaptive algorithms, intersectional fairness, inclusive development, and robust ethical frameworks, aiming to guide AI towards equitable and responsible advancement.

Published Paper   E-Certificate

"Addressing Bias and Fairness Issues in Artificial Intelligence", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 9, page no.44 - 48, September-2023, Available :https://ijsdr.org/papers/IJSDR2309008.pdf

Volume 8 Issue 9, September-2023

Pages : 44 - 48

Paper Reg. ID: IJSDR_208402

Published Paper Id: IJSDR2309008

Downloads: 000347197

Research Area: Computer Engineering 

Country: New Delhi, Delhi, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2309008

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2309008

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition