Blockchain-Powered AI Governance: Ensuring Ethical and Transparent Decision-Making

Authors

  • Prof. Rachel Fernandez

Abstract

With the increasing adoption of AI in critical decision-making systems, ensuring transparency and accountability has become a pressing concern. This paper presents a decentralized blockchain-based framework for AI governance, where smart contracts regulate model updates, decision logging, and bias detection. By leveraging blockchain’s immutability and consensus mechanisms, we propose a trustless and auditable AI ecosystem. Our experimental implementation demonstrates the feasibility of blockchain-driven AI accountability, mitigating risks associated with bias, unfairness, and lack of interpretability in AI models.

References

Krutthika H. K. & A.R. Aswatha (2020). Design of efficient FSM-based 3D network-on-chip architecture. International Journal of Engineering Trends and Technology, 68(10), 67–73. https://doi.org/10.14445/22315381/IJETT-V68I10P212

Krutthika H. K. & Rajashekhara R. (2019). Network-on-chip: A survey on router design and algorithms. International Journal of Recent Technology and Engineering, 7(6), 1687–1691. https://doi.org/10.35940/ijrte.F2131.037619

S. Ajay, et al., & Krutthika H. K. (2018). Source hotspot management in a mesh network-on-chip. 22nd International Symposium on VLSI Design and Test (VDAT-2018). https://doi.org/10.1007/978-981-13-5950-7_51

Krutthika Hirebasur Krishnappa, Hiremath, M. M., & Manasa, R. (2024). Semiconductor fault diagnosis using deep learning-based domain adaptation. International Journal of Intelligent Systems and Applications in Engineering, 12(9s). DOI: https://ijisae.org/index.php/IJISAE/article/view/4333

Shashidhar, R., Balivada, D., Shalini, D. N., Krutthika Hirebasur Krishnappa, & Roopa, M. (2023). Music emotion recognition using convolutional neural networks for regional languages. 2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE), 1–7. DOI: 10.1109/AIKIIE60097.2023.10390450

Shashidhar, R., Aprameya, C. V., Bharadwaj, R. R., Gontamar, S. M., & Krutthika Hirebasur Krishnappa. (2023). Seismic signal processing and aftershock analysis using machine learning. 2023 International Conference on Recent Advances in Science and Engineering Technology (ICRASET), 1–9. DOI: 10.1109/ICRASET59632.2023.10420268.

Reddy, M. S., Sarisa, M., Konkimalla, S., Bauskar, S. R., Gollangi, H. K., Galla, E. P., & Rajaram, S. K. (2021). Predicting tomorrow’s Ailments: How AI/ML Is Transforming Disease Forecasting. ESP Journal of Engineering & Technology Advancements, 1(2), 188-200.

Mahida, A., Mandala, V., Bauskar, S. R., Konkimalla, S., & Reddy, M. S. (2024). Real-Time Fraud Mitigation in Digital Payments: Big Data and AI-Driven Biometric Authentication. Nanotechnology Perceptions, 20, 1176-1193.

Madhavaram, C. R., Galla, E. P., Reddy, M. S., Sarisa, M., & Nagesh, V. (2021). Predicting Diabetes Mellitus in Healthcare: A Comparative Analysis of Machine Learning Algorithms on Big Dataset. Journal homepage: https://gjrpublication. com/gjrecs, 1(01).

Bauskar, S. R., Reddy, M. S., Sarisa, M., & KONKIMALLA, S. The Future of Cloud Computing_ Al-Driven Deep Learning and Neural Network Innovations. BUDHA PUBLISHER.

Konkimalla, S., SARISA, M., REDDY, M. S., & BAUSKAR, S. DATA ENGINEERING IN THE AGE OF AI GENERATIVE MODELS AND DEEP LEARNING UNLEASHED. BUDHA PUBLISHER.

Reddy, M., Konkimalla, S., Rajaram, S. K., Bauskar, S. R., Sarisa, M., & Sunkara, J. R. (2022). Using AI And Machine Learning To Secure Cloud Networks: A Modern Approach To Cybersecurity. Available at SSRN 5045776.

Patra, G. K., Kuraku, C., Konkimalla, S., Boddapati, V. N., & Sarisa, M. (2023). Sentiment Analysis of Customer Product Review Based on Machine Learning Techniques in E-Commerce. Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-408. DOI: doi. org/10.47363/JAICC/2023 (2), 389(1), 7211-7224.

Patra, G. K., Kuraku, C., Konkimalla, S., Boddapati, V. N., Sarisa, M., & Reddy, M. S. (2024). An Analysis and Prediction of Health Insurance Costs Using Machine Learning-Based Regressor Techniques. Journal of Data Analysis and Information Processing, 12(4), 581-596.

Rajaram, S. K., Konkimalla, S., Sarisa, M., Gollangi, H. K., Madhavaram, C. R., & Reddy, M. S. (2023). AI/ML-Powered Phishing Detection: Building an Impenetrable Email Security System. ISAR Journal of Science and Technology, 1(2), 10-19.

Gummadi, V., Ramadevi, N., Udayaraju, P., Ravulu, C., Seelam, D. R., & Swamy, S. V. (2024, September). A Deep Learning-based Optimization Model for Advertisement Campaign. In 2024 5th International Conference on Smart Electronics and Communication (ICOSEC) (pp. 1783-1790). IEEE.

Gummadi, V., Udayaraju, P., Kolasani, D., Kotaru, C., Sayana, R., & Neethika, A. (2024, December). NLP Based TAG Algorithm for Enhancing Customer Data Platform and Personalized Marketing. In 2024 International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS) (pp. 60-67). IEEE.

Mane, S., & Immidi, K. (2024). Strategic Insights and Best Practices for Upgrading to SAP S/4HANA: A Comprehensive Framework for Business Transformation. International Journal of Creative Research In Computer Technology and Design, 6(6).

Mane, S. (2024). Optimizing Returns and Refunds Management in SAP: Leveraging Data-Driven Insights and Advanced Automation. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-13.

Mane, S., & Immidi, K. (2023). Enhancing SAP Available-to-Promise (ATP) Capabilities through AI Integration: A Transformative Approach to Supply Chain Optimization. International Journal of Creative Research In Computer Technology and Design, 5(5), 1-24.

Mane, S. (2023). Optimizing SAP Sales Order Processing: Strategies, Technologies, and Impact on Operational Efficiency. International Journal of Interdisciplinary Finance Insights, 2(2), 1-32.

Adusumilli, S., Damancharla, H., & Metta, A. (2020). Artificial Intelligence-Driven Predictive Analytics for Educational Behavior Assessment. Transactions on Latest Trends in Artificial Intelligence, 1(1). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/638

Adusumilli, S., Damancharla, H., & Metta, A. (2020). Machine Learning Algorithms for Fraud Detection in Financial Transactions. International Journal of Sustainable Development in Computing Science, 2(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/639

Adusumilli, S., Damancharla, H., & Metta, A. (2021). Deep Learning Techniques for Image Recognition in Autonomous Vehicles. (2021). International Meridian Journal, 3(3). https://meridianjournal.in/index.php/IMJ/article/view/94

Adusumilli, S., Damancharla, H., & Metta, A. (2021). Integrating Machine Learning and Blockchain for Decentralized Identity Management Systems. (2021). International Journal of Machine Learning and Artificial Intelligence, 2(2). https://jmlai.in/index.php/ijmlai/article/view/46

Adusumilli, S., Damancharla, H., & Metta, A. (2022). Blockchain-Based Secure Framework for IoT Data Management. International Journal of Sustainable Development in Computing Science, 4(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/640

Adusumilli, S., Damancharla, H., & Metta, A. (2022). Optimizing Supply Chain Efficiency Through Blockchain and Smart Contracts. (2022). International Numeric Journal of Machine Learning and Robots, 6(6). https://injmr.com/index.php/fewfewf/article/view/183

Adusumilli, S., Damancharla, H., & Metta, A. (2023). Enhancing Data Privacy in Healthcare Systems Using Blockchain Technology. Transactions on Latest Trends in Artificial Intelligence, 4(4). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/637

Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2021). AI-Powered Cybersecurity Solutions for Threat Detection and Prevention. International Journal of Creative Research In Computer Technology and Design, 3(3).

Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2020). Leveraging AI for Real-Time Sentiment Analysis in Social Media Networks. International Numeric Journal of Machine Learning and Robots, 4(4).

Krutthika H. K. & A.R. Aswatha. (2021). Implementation and analysis of congestion prevention and fault tolerance in network on chip. Journal of Tianjin University Science and Technology, 54(11), 213–231. https://doi.org/10.5281/zenodo.5746712

Krutthika H. K. & A.R. Aswatha. (2020). FPGA-based design and architecture of network-on-chip router for efficient data propagation. IIOAB Journal, 11(S2), 7–25.

Krutthika H. K. & A.R. Aswatha (2020). Design of efficient FSM-based 3D network-on-chip architecture. International Journal of Engineering Trends and Technology, 68(10), 67–73. https://doi.org/10.14445/22315381/IJETT-V68I10P212

Krutthika H. K. & Rajashekhara R. (2019). Network-on-chip: A survey on router design and algorithms. International Journal of Recent Technology and Engineering, 7(6), 1687–1691. https://doi.org/10.35940/ijrte.F2131.037619

S. Ajay, et al., & Krutthika H. K. (2018). Source hotspot management in a mesh network-on-chip. 22nd International Symposium on VLSI Design and Test (VDAT-2018). https://doi.org/10.1007/978-981-13-5950-7_51

Krutthika Hirebasur Krishnappa, Hiremath, M. M., & Manasa, R. (2024). Semiconductor fault diagnosis using deep learning-based domain adaptation. International Journal of Intelligent Systems and Applications in Engineering, 12(9s). DOI: https://ijisae.org/index.php/IJISAE/article/view/4333

Shashidhar, R., Balivada, D., Shalini, D. N., Krutthika Hirebasur Krishnappa, & Roopa, M. (2023). Music emotion recognition using convolutional neural networks for regional languages. 2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE), 1–7. DOI: 10.1109/AIKIIE60097.2023.10390450

Shashidhar, R., Aprameya, C. V., Bharadwaj, R. R., Gontamar, S. M., & Krutthika Hirebasur Krishnappa. (2023). Seismic signal processing and aftershock analysis using machine learning. 2023 International Conference on Recent Advances in Science and Engineering Technology (ICRASET), 1–9. DOI: 10.1109/ICRASET59632.2023.10420268.

Published

2024-12-03

How to Cite

Fernandez, P. R. (2024). Blockchain-Powered AI Governance: Ensuring Ethical and Transparent Decision-Making. International Journal of Sustainable Development in Computer Science Engineering, 10(10). Retrieved from https://journals.threws.com/index.php/IJSDCSE/article/view/332

Issue

Section

Articles