Bridging the Ethical Gap: Privacy-Preserving Artificial Intelligence in the Age of Pervasive Data

Vijayalaxmi Methuku, Srikanth Kamatala*, Praveen Kumar Myakala

Abstract

Artificial intelligence is increasingly embedded in modern systems, driving innovations in areas such as personalized healthcare, autonomous technologies, and digital services. Alongside these advancements, concerns about privacy, ethical accountability, and responsible data stewardship have grown significantly. This article investigates how ethical principles can be integrated into AI design and deployment, with a focus on privacy-preserving techniques. Approaches such as federated learning, differential privacy, and homomorphic encryption are examined for their ability to support secure AI while enabling decentralized data processing. Through the analysis of real-world case studies and ethical lapses, the study identifies critical gaps in current practices and highlights the risks of opaque algorithmic decision-making. To address these challenges, a comprehensive, multi-dimensional framework is proposed to promote transparency, accountability, and human-centered values in the development of ethically aligned and privacy-respecting AI systems.

Keywords

Ethical Artificial Intelligence; AI Ethics; Responsible AI; AI Governance; Privacy-Preserving AI; Data Protection; Secure Machine Learning; Federated Learning; Differential Privacy; Homomorphic Encryption; Algorithmic Accountability; Transparency in AI; Explainable AI (XAI); AI Bias and Fairness; Human-Centered AI.

Cite This Article

Methuku, V., Kamatala, S., Myakala, P. K. (2021). Bridging the Ethical Gap: Privacy-Preserving Artificial Intelligence in the Age of Pervasive Data. International Journal of Scientific Advances (IJSCIA), Volume 2| Issue 6: Nov-Dec 2021, Pages 1042-1047, URL: https://www.ijscia.com/wp-content/uploads/2025/04/Volume2-Issue6-Nov-Dec-No.210-1042-1047.pdf

Volume 2 | Issue 6: Nov-Dec 2021