ARCHIVES

1. S. Russell, "Human Compatible: Artificial Intelligence and the Problem of Control," Viking Press, 2019.
2. S. D. Baum, "A survey of artificial general intelligence projects for ethics, risk, and policy," Global Catastrophic Risk Institute Working
Paper, 2017.
3. E. Awad et al., "The moral machine experiment," Nature, vol. 563, no. 7729, pp. 59-64, 2018.
4. A. Kirilenko et al., "The flash crash: High-frequency trading in an electronic market," Journal of Finance, vol. 72, no. 3, pp. 967-998, 2017.
5. Z. Obermeyer et al., "Dissecting racial bias in an algorithm used to manage the health of populations," Science, vol. 366, no. 6464, pp. 447-
453, 2019.
6. Y. Bai et al., "Constitutional AI: Harmlessness from AI feedback," arXiv preprint arXiv:2212.08073, 2022.
7. Khairnar, S., Bansod, G., Dahiphale, V. (2019). A Light Weight Cryptographic Solution for 6LoWPAN Protocol Stack. In: Arai, K., Kapoor,
S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 857. Springer,
Cham. https://doi.org/10.1007/978-3-030-01177-2_71
8. A. F. Winfield and M. Jirotka, "Ethical governance is essential to building trust in robotics and artificial intelligence systems," Philosophical
Transactions of the Royal Society A, vol. 376, no. 2133, 2018.
9. J. H. Moor, "The nature, importance, and difficulty of machine ethics," IEEE Intelligent Systems, vol. 21, no. 4, pp. 18-21, 2006.
10. F. Doshi-Velez and B. Kim, "Towards a rigorous science of interpretable machine learning," arXiv preprint arXiv:1702.08608, 2017.
11. P. Vamplew et al., "Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021)," Autonomous Agents and Multi-
Agent Systems, vol. 36, no. 2, pp. 1-9, 2022.
12. D. Ganguli et al., "Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned," arXiv preprint
arXiv:2209.07858, 2022.
13. Sushil Khairnar and Deep Bodra. “Recommendation Engine for Amazon Magazine Subscriptions”. International Journal of Advanced
Computer Science and Applications (ijacsa) 16.7 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160796
14. Z. Kenton et al., "Alignment of language agents," arXiv preprint arXiv:2103.14659, 2021.
15. A. Askell et al., "A general language assistant as a laboratory for alignment," arXiv preprint arXiv:2112.00861, 2021.
16. P. F. Christiano et al., "Deep reinforcement learning from human preferences," Advances in Neural Information Processing Systems, vol. 30,
2017.
17. L. A. Dennis et al., "Agent-based autonomous systems and abstraction engines: Theory in practice," in Proc. International Conference on
Autonomous Agents and Multiagent Systems, 2016, pp. 1784-1785.
18. W. Wallach and C. Allen, "Moral machines: Teaching robots right from wrong," Oxford University Press, 2008.
19. Sushil Khairnar. “Application of Blockchain Frameworks for Decentralized Identity and Access Management of IoT Devices”. International
Journal of Advanced Computer Science and Applications (IJACSA) 16.6 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160604
20. S. Tolmeijer et al., "Implementations in machine ethics: A survey," ACM Computing Surveys, vol. 53, no. 6, pp. 1-38, 2020.
21. J. F. Bonnefon et al., "The social dilemma of autonomous vehicles," Science, vol. 352, no. 6293, pp. 1573-1576, 2016.
22. I. Chen et al., "Ethical machine learning in healthcare," Annual Review of Biomedical Data Science, vol. 4, pp. 123-144, 2021.
23. J. Larson et al., "How we analyzed the COMPAS recidivism algorithm," ProPublica, May 23, 2016.
24. A. Tampuu et al., "Multiagent deep reinforcement learning with extremely sparse rewards," arXiv preprint arXiv:1707.01495, 2017.
25. I. Rahwan et al., "Machine behaviour," Nature, vol. 568, no. 7753, pp. 477-486, 2019.
26. J. W. Crandall et al., "Cooperating with machines," Nature Communications, vol. 9, no. 1, pp. 1-12, 2018.
27. D. Gunning et al., "XAI—Explainable artificial intelligence," Science Robotics, vol. 4, no. 37, 2019.28. M. T. Ribeiro et al., "Why should I trust you?: Explaining the predictions of any classifier," in Proc. 22nd ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining, 2016, pp. 1135-1144.
29. Sushil Khairnar, Deep Bodra . Analysis and Evaluation of Modern Lightweight Cryptographic Algorithms: Standards, Hardware
Implementation, and Security Considerations. International Journal of Computer Applications. 187, 37 ( Sep 2025), 10-15.
DOI=10.5120/ijca2025925634
30. T. Miller, "Explanation in artificial intelligence: Insights from the social sciences," Artificial Intelligence, vol. 267, pp. 1-38, 2019.
31. R. Binns et al., "Fairness in machine learning: Lessons from political philosophy," in Proc. 2018 Conference on Fairness, Accountability and
Transparency, 2018, pp. 149-159.
32. A. Dosovitskiy et al., "CARLA: An open urban driving simulator for autonomous driving research," in Proc. Conference on Robot Learning,
2017, pp. 1-16.
33. A. E. Johnson et al., "MIMIC-III, a freely accessible critical care database," Scientific Data, vol. 3, no. 1, pp. 1-9, 2016.