AI in Autonomous Systems: Safety, Reliability, and Governance
Keywords:
Artificial Intelligence, Autonomous Systems, Safety, Reliability, Governance, Ethics, AI RegulationsAbstract
Artificial Intelligence (AI) has significantly transformed autonomous systems, enhancing their capabilities across various industries such as transportation, healthcare, manufacturing, and defense. As AI-driven autonomous systems become more prevalent, ensuring their safety, reliability, and adherence to governance frameworks is of paramount importance. Safety concerns arise from unpredictable AI behaviors, sensor malfunctions, and adversarial attacks, making robust safety protocols essential. Reliability is a major challenge due to system failures, biases in decision-making and environmental uncertainties that impact AI performance. Furthermore, governance plays a crucial role in regulating AI ethics, accountability, and transparency. This research paper provides a detailed examination of AI in autonomous systems by analyzing safety measures, reliability enhancements, and governance strategies. Additionally, an experimental analysis is conducted to assess AI-driven autonomous vehicle performance in controlled and real-world conditions. The results highlight the necessity of stringent testing, algorithmic improvements, and policy implementations to achieve trustworthy autonomous AI systems.
References
[1] G. K. Karamchand, "Artificial Intelligence: Insights into a Transformative Technology," Journal of Computing and Information Technology, vol. 3, no. 1, 2023.
[2] S. Chitimoju, "AI-Driven Threat Detection: Enhancing Cybersecurity through Machine Learning Algorithms," Journal of Computing and Information Technology, vol. 3, no. 1, 2023.
[3] G. K. Karamchand, "Automating Cybersecurity with Machine Learning and Predictive Analytics,"
Journal of Computational Innovation, vol. 3, no. 1, 2023.
[4] H. Azmat, "Artificial Intelligence in Transfer Pricing: A New Frontier for Tax Authorities?," Aitoz Multidisciplinary Review, vol. 2, no. 1, pp. 75-80, 2023.
[5] S. Chitimoju, "Ethical Challenges of AI in Cybersecurity: Bias, Privacy, and Autonomous Decision- Making," Journal of Computational Innovation, vol. 3, no. 1, 2023.
[6] G. K. Karamchand, "Exploring the Future of Quantum Computing in Cybersecurity," Journal of Big Data and Smart Systems, vol. 4, no. 1, 2023.
[7] S. Ravikumar, S. Tasneem, N. Sakib, and K. A. Islam, "Securing AI of Healthcare: A Selective Review on Identifying and Preventing Adversarial Attacks," in 2024 IEEE Opportunity Research Scholars Symposium (ORSS), 2024: IEEE, pp. 75-78.
[8] S. Chitimoju, "The Risks of AI-Generated Cyber Threats: How LMs Can Be Weaponized for Attacks," International Journal of Digital Innovation, vol. 4, no. 1, 2023.
[9] G. K. Karamchand, "From Local to Global: Advancements in Networking Infrastructure," Journal of Computing and Information Technology, vol. 4, no. 1, 2024.
[10] S. Chitimoju, "Using Large Language Models for Phishing Detection and Social Engineering Defense," Journal of Big Data and Smart Systems, vol. 4, no. 1, 2023.
[11] G. K. Karamchand, "Mesh Networking for Enhanced Connectivity in Rural and Urban Areas,"
Journal of Computational Innovation, vol. 4, no. 1, 2024.
[12] M. Rizvi, "Enhancing cybersecurity: The power of artificial intelligence in threat detection and prevention," International Journal of Advanced Engineering Research and Science, vol. 10, no. 5,
pp. 055-060, 2023.
[13] H. Azmat and Z. Huma, "Comprehensive Guide to Cybersecurity: Best Practices for Safeguarding Information in the Digital Age," Aitoz Multidisciplinary Review, vol. 2, no. 1, pp. 9-15, 2023.
[14] S. Chitimoju, "A Survey on the Security Vulnerabilities of Large Language Models and Their Countermeasures," Journal of Computational Innovation, vol. 4, no. 1, 2024.
[15] S. Chitimoju, "Mitigating the Risks of Prompt Injection Attacks in AI-Powered Cybersecurity Systems," Journal of Computing and Information Technology, vol. 4, no. 1, 2024.
[16] V. Shestakova, "Best practices to mitigate bias and discrimination in artificial intelligence,"
Performance Improvement, vol. 60, no. 6, pp. 6-11, 2021.
[17] S. Chitimoju, "The Evolution of Large Language Models: Trends, Challenges, and Future Directions," Journal of Big Data and Smart Systems, vol. 5, no. 1, 2024.
[18] G. K. Karamchand, "Networking 4.0: The Role of AI and Automation in Next-Gen Connectivity,"
Journal of Big Data and Smart Systems, vol. 5, no. 1, 2024.
[19] S. Chitimoju, "The Impact of AI in Zero-Trust Security Architectures: Challenges and Innovations," International Journal of Digital Innovation, vol. 5, no. 1, 2024.
[20] G. Karamchand, "The Impact of Cloud Computing on E-Commerce Scalability and Personalization," Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 13-18, 2024.
[21] S. Chitimoju, "Enhancing Cyber Threat Intelligence with NLP and Large Language Models,"
Journal of Big Data and Smart Systems, vol. 6, no. 1, 2025.
[22] S. Chitimoju, "Federated Learning in Cybersecurity: Privacy-Preserving AI for Threat Detection,"
International Journal of Digital Innovation, vol. 6, no. 1, 2025.
[23] G. K. Karamchand, "Scaling New Heights: The Role of Cloud Computing in Business Transformation," International Journal of Digital Innovation, vol. 5, no. 1, 2024.
[24] D. Van Hie, "The Impact of AI-driven Automation on Workforce Dynamics and Skill Requirements Across Industries," Journal of Sustainable Urban Futures, vol. 14, no. 1, pp. 1-13, 2024.
[25] V. Thakare, G. Khire, and M. Kumbhar, "Artificial intelligence (AI) and internet of things (IoT) in healthcare: Opportunities and challenges," ECS Transactions, vol. 107, no. 1, p. 7941, 2022.
[26] G. Karamchand, "The Road to Quantum Supremacy: Challenges and Opportunities in Computing," Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 19-26, 2024.
[27] G. Karamchand, "The Role of Artificial Intelligence in Enhancing Autonomous Networking Systems," Aitoz Multidisciplinary Review, vol. 3, no. 1, pp. 27-32, 2024.
