Unveiling Fairness: A Quest for Ethical AI and Bias Mitigation

Year : 2023 | Volume : 01 | Issue : 02 | Page : 32-35
By

    Ushaa Eswaran

  1. Vivek Eswaran

  2. Keerthna Murali

  3. Vishal Eswaran

  1. Principal and Professor, Department of ECE, Indira Institute of Technology and Sciences, Markapur, Andhra Pradesh, India
  2. Senior Software Engineer, Tech Lead at Medallia, Austin, Texas, United States
  3. Cybersecurity, Site Reliability Engineer II (SRE) at Dell EMC | CKAD |, AWS CSAA, United States
  4. Senior Data Engineer, CVS Health Centre, Dallas, Texas, United States

Abstract

Artificial Intelligence (AI) systems have become ubiquitous across areas like finance, healthcare, employment, and criminal justice. However, they suffer from issues of unfair bias, lack of transparency, and broad ethical implications impacting vulnerable societal groups disproportionately. This paper reviews key challenges around AI ethics and bias while proposing data-driven guidelines mitigating such algorithmic harms through rigorous statistical testing, predictive modeling ensembles adjusting distortion vectors and AI audits by domain experts analyzing source codes, training data curation and model card documentations ensuring responsible development. A tiered regulatory framework is envisioned spanning self-regulation, external audits, professional Codes of Ethics and government oversight balancing innovation impacts with public safeguards.

Keywords: Algorithmic bias, AI ethics, mitigation techniques, model transparency, regulation

[This article belongs to International Journal of Information Security Engineering(ijise)]

How to cite this article: Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran Unveiling Fairness: A Quest for Ethical AI and Bias Mitigation ijise 2023; 01:32-35
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Regular Issue Subscription Review Article
Volume 01
Issue 02
Received November 23, 2023
Accepted November 29, 2023
Published December 6, 2023

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