Blockchain-Based Decentralized AI Systems: Enhancing Data Integrity and Model Trustworthiness

Authors

  • Alice Thompson Ph.D., Senior Researcher, Innovation Labs, San Francisco, USA Author

Keywords:

Blockchain, artificial intelligence

Abstract

The integration of blockchain technology with artificial intelligence (AI) systems has emerged as a transformative approach to addressing challenges related to data integrity and trustworthiness in AI predictions. This paper explores how decentralized blockchain infrastructures can enhance the security and reliability of AI models by preventing tampering and ensuring the authenticity of data used for training and inference. By establishing immutable records of data transactions and enabling transparent model evaluation, blockchain can provide robust solutions for data provenance and accountability. The paper discusses the technical frameworks for integrating blockchain with AI, examines various use cases across industries, and identifies the implications for stakeholders in AI development. Ultimately, this research highlights the potential of blockchain-based decentralized AI systems to foster greater trust in AI technologies, thereby promoting broader adoption and acceptance.

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Published

01-10-2024

How to Cite

[1]
A. Thompson, “Blockchain-Based Decentralized AI Systems: Enhancing Data Integrity and Model Trustworthiness”, J. of Artificial Int. Research and App., vol. 4, no. 2, pp. 70–76, Oct. 2024, Accessed: Dec. 23, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/259

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