Cite this Article

Dr. M. Siva Sankari, 2025. "AI Governance Models Using Blockchain-Based Transparency Mechanisms", International Journal of Research in Artificial Intelligence and Data Science(IJRAIDS)1(1): 31-44.

The International Journal of Research in Artificial Intelligence and Data Science (IJRAIDS)
© 2025 by IJRAIDS
Volume 1 Issue 1
Year of Publication : 2025
Authors : Author Name
Doi : XXXX XXXX XXXX

Keywords

AI governance, blockchain, openness, responsibility, smart contracts, decentralised decision-making, AI ethics, traceability, privacy-preserving technologies, and public trust altering industries, governments, and society. But as AI systems becoming more powerful and independent, people are more worried about how accountable, open, and ethical they are. This research paper looks at how blockchain technology, which is known for being unchangeable and having decentralised trust mechanisms, could improve AI governance models. Adding blockchain-based transparency tools to the processes of building and deploying AI could make AI systems easier to track, hold accountable, and trust. The paper talks about what other people have said about the topic, recommends various ways to govern it, and talks about challenges that happen in the actual world and what research could be done in the future.

Abstract

AI is making major changes in business, government, and society, but its rapid expansion has also brought up a lot of moral, clear, and responsible problems. It is vitally crucial to have solid governance frameworks in place as AI systems become more self-sufficient and start to make significant choices. Traditional ways of keeping an eye on things don't function well with AI technology that is decentralised, crosses borders, or isn't obvious. Blockchain technology is a good place to start when it comes to making AI governance models better because it is open, unchangeable, and has decentralised trust.

This article talks about how to include blockchain-based tools for transparency in AI governance frameworks. Blockchain can create unchangeable audit trails, decentralised systems for making decisions, and smart contracts that automatically enforce regulations. These traits could help with some of the biggest issues with AI governance, such as how hard it is to comprehend algorithms, how hard it is to hold individuals accountable, and how power is concentrated among a small group of AI stakeholders.

Blockchain technology is used in a number of AI governance frameworks. First, keeping explicit development records on a blockchain can make it easier to find things, which implies that people who aren't working on the project can check AI models, training datasets, and development procedures. Second, smart contracts can make sure that norms and morals are observed without any help. Third, blockchain-based decentralised AI governance consortia can help make decisions that are open and include a lot of different people. Finally, public audit trails based on blockchain can make people more responsible, especially in sensitive areas like healthcare, banking, and public administration.

There are still challenges in the actual world, even with these benefits. It's challenging to keep track of AI judgements in real time since blockchain doesn't scale well. When private AI data is stored on immutable ledgers, it can be hard to keep it private. That's why we need privacy-preserving methods like zero-knowledge proofs. Blockchain systems and AI platforms need to function together, and it's challenging to regulate decentralised models.

Future research should focus on making blockchain solutions that make AI governance more private, architectures that can be scaled up and used with other systems, and real-world case studies that show how blockchain and AI can function together in governance. To preserve rights and cope with new risks, legal and regulatory frameworks need to change. They also need to support these new concepts.

In conclusion, using blockchain to make things more clear is a promising strategy to make AI governance better. By making AI systems more accountable, transparent, and open to input from stakeholders, blockchain can help people trust them more and decrease the dangers that come with them. People from different professions, like technology, law, and policy, need to work together to make this happen.

Introduction

Artificial intelligence (AI) technologies have spread so quickly to practically every sector of society that they have revolutionised how people make decisions, how services are delivered, and how organisations work. AI systems are currently helping to run significant parts of healthcare, banking, transportation, and public administration. They offer degrees of efficiency, predictive power, and automation that have never been seen before. But as AI systems become more widespread in important circumstances, they also raise new, tough difficulties for government, especially when it comes to ethics, accountability, transparency, and justice.

There have been a number of high-profile events in the previous few years that have made it evident that we need to take control of AI right soon. Some examples are biassed AI hiring tools that disadvantage minority groups, credit-scoring algorithms that are hard to understand and make it harder for individuals to secure loans, and AI-driven surveillance systems that violate people's right to privacy. These events indicate that AI can make social problems worse without meaning to, break basic rights, and work without clear means to hold individuals accountable if it is not kept in check. It's challenging to understand AI systems, especially those that use machine learning and deep learning, because they don't explain how they make judgements or who is to blame when something goes wrong.

Governance mechanisms that were made for making decisions about conventional software or people don't necessarily function well for controlling AI technologies. AI systems are hard to grasp, do their jobs on their own, and are always learning and changing. This makes it exceedingly challenging for businesses, authorities, and society as a whole to cope with them. It is also tougher to govern because AI development is happening all over the world and is not centralised. Many countries work together to make AI models, and they train them on different sets of data. They are then utilised in regions with very different laws and moral standards. This broken ecosystem makes it challenging to create standard, enforceable AI governance frameworks and leaves gaps in regulation. Blockchain technology has become a viable approach to fix these challenges with AI governance. Blockchain was first made to serve cryptocurrencies, but it includes qualities that make it a viable choice for strong AI governance. These include decentralisation, transparency, immutability, and resistance to manipulation. Blockchain can make the AI lifecycle more accountable and traceable by retaining records of AI development processes, decision-making events, and compliance procedures that can't be changed.