Terry Mccarthy

My name is Terry McCarthy, and my research is centered on the convergence of artificial intelligence (AI) and blockchain technologies. With a background in computer science and distributed systems, I have been exploring how these two transformative fields can complement each other—AI offering intelligence and adaptability, and blockchain offering transparency, security, and decentralization. As AI becomes increasingly integrated into decision-making systems, the need for explainability, auditability, and trust makes blockchain a critical enabler. My work focuses on identifying and advancing real-world use cases where their synergy creates added value.

In my current research, I investigate AI-on-blockchain architectures, federated learning with decentralized data trust layers, and smart contract-driven AI governance. Applications include secure data marketplaces, verifiable model training, decentralized autonomous organizations (DAOs), and tamper-proof AI decision logs. I also explore how blockchain can provide provenance tracking for AI models, enabling greater accountability in sectors such as healthcare, finance, and supply chain management. Through experimental prototypes and simulation environments, I aim to assess both the technical feasibility and performance trade-offs of integrated systems.

While the potential of AI-blockchain fusion is immense, the ecosystem remains nascent and fragmented. Key challenges include scalability limitations, interoperability across platforms, regulatory uncertainty, and the complexity of integrating real-time AI inference with consensus-driven blockchain mechanisms. My research seeks to bridge these gaps by exploring hybrid architectures (on-chain/off-chain), privacy-preserving machine learning (e.g., using zero-knowledge proofs), and token-based incentive structures for collaborative AI training. I believe that solving these issues will be essential for building trustworthy, decentralized AI systems in the future.

Looking ahead, my vision is to help shape a future where AI systems are not only intelligent but also auditable, decentralized, and aligned with human values. I am currently working on a framework for AI model certification using blockchain-based registries, and exploring how Web3 infrastructure can support transparent, community-governed AI services. I aim to contribute to the development of open protocols and interdisciplinary standards that make the AI–blockchain fusion both practical and ethical. Through academic research, industry partnerships, and open-source collaboration, I hope to drive forward the architecture of a more equitable and intelligent digital future.