Ushaa Eswaran
Vivek Eswaran
Keerthna Murali
Vishal Eswaran
- Principal and Professor Department of ECE, Indira Institute of Technology and Sciences, Markapur Andhra Pradesh India
- Senior Software Engineer Tech Lead at Medallia, Austin Texas United States
- Cybersecurity Site Reliability Engineer II (SRE) at Dell EMC | CKAD | AWS CSAA United States
- 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, artificial intelligence (AI) ethics, mitigation techniques, model transparency, regulation
[This article belongs to International Journal of Information Security Engineering(ijise)]
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| Volume | 01 |
| Issue | 02 |
| Received | November 23, 2023 |
| Accepted | November 29, 2023 |
| Published | December 30, 2023 |