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AI-Powered Threats and Solutions: A Theoretical Analysis of Risks, Governance, and Ethical Safeguards

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  • Arkyadeep Sarkar,
  • Shankha Shubhra Goswami,
  • Sushil Kumar Sahoo
Arkyadeep Sarkar
Department of Mechanical Engineering, Abacus Institute of Engineering and Management, India
Shankha Shubhra Goswami
Department of Mechanical Engineering, Abacus Institute of Engineering and Management, India
Sushil Kumar Sahoo
Department of Mechanical Engineering, Indira Gandhi Institute of Technology, India

Published 2026-01-25

Keywords

  • Artificial Intelligence (AI),
  • AI governance,
  • Cybersecurity threats,
  • Ethical and responsible AI,
  • Explainable AI,
  • Adversarial machine learning
    • ...More
    Less

Copyright (c) 2026 Arkyadeep Sarkar, Shankha Shubhra Goswami, Sushil Kumar Sahoo (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Sarkar, A., Goswami, S. S., & Sahoo, S. K. . (2026). AI-Powered Threats and Solutions: A Theoretical Analysis of Risks, Governance, and Ethical Safeguards. Applied Research Advances, 2(1), 1-23. https://doi.org/10.65069/ara2120267
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Abstract

Artificial Intelligence (AI) represents one of the most transformative technological paradigms of the 21st century, revolutionizing fields such as healthcare, finance, defense, and communication. However, the same capabilities that enable innovation also introduce substantial risks when exploited maliciously or left unregulated. This study presents a theoretical analysis of the emerging threats posed by AI—including deepfakes, autonomous cyberattacks, data manipulation, misinformation propagation, and algorithmic bias—and explores the countermeasures designed to address these risks. Drawing upon contemporary research, the paper emphasizes the dual-use nature of AI, the ethical and governance challenges it poses, and the pressing need for global cooperation. The findings reveal that sustainable and responsible AI development depends on integrating explainable AI, adversarial defense systems, robust governance frameworks, and international regulatory coordination. The paper concludes by proposing a multidimensional framework that aligns AI innovation with human safety, transparency, and accountability.

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