AI and Blockchain: A Disruptive Integration
Abstract
AI and blockchain are among the most disruptive technologies and will fundamentally reshape how we live, work, and interact. The authors summarize existing efforts and discuss the promising future of their integration, seeking to answer the question: What can smart, decentralized, and secure systems do for our society?
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The integration or marriage of AI and blockchain seems inevitable, especially since they have the potential to complement each other and revolutionize the next digital generation.
“The integration or marriage of these two technologies seems inevitable; especially since they have the potential to complement each other and revolutionize the next digital generation [257, 258].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [258]
Extant research has proposed using DLT to establish explainability of AI, addressing the model opacity tension.
“Finally, extant research has proposed the use of DLT to establish explainability of AI (i.e., addressing the model opacity tension).”
From Trustworthy artificial intelligence (2021) · cites this paper as Dinh and Thai 2018
DLT ought to serve as a tamper-resistant trail for tracking the flow of data within AI-based systems, which may then be further analyzed to create explainable AI models.
“DLT is thereby ought to serve as a tamper resistant trail for tracking the flow of data within AI-based systems, which may then be further analyzed to create explainable AI models (Dinh and Thai 2018).”
From Trustworthy artificial intelligence (2021) · cites this paper as Dinh and Thai 2018
DLT can serve to organize the federated training of AI models.
“Next to DLT-based data markets, DLT can also serve to organize the federated (i.e., decentralized) training of AI models (Dinh and Thai 2018).”
From Trustworthy artificial intelligence (2021) · cites this paper as Dinh and Thai 2018
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Exploring the Joint Potential of Blockchain and AI for Securing Internet of Things
Tauseef, M., Kounte, M. R., Nalband, A. H., & Ahmed, M. R. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140498 · Cited by 21 · see citing works
Blockchain Intelligence: When Blockchain Meets Artificial IntelligencePreprint
Zheng, Z., Dai, H., & Wu, J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.06485 · Cited by 21 · see citing works
- Authors
- Dinh, T. N., & Thai, M. T.
- Affiliations
- Virginia Commonwealth University (US)
- University of Florida (US)
- Venue
- Computer
- Published
- 2018-09
- Volume
- 51
- Issue
- 9
- Pages
- 48-53
- ISSN
- 0018-9162 (ISSN-L)
- 1558-0814
- OpenAlex
- W2894710278
- Cited by
- 317
- References
- 10
- Citations by year
- 2026: 14 · 2025: 32 · 2024: 37 · 2023: 47 · 2022: 59 · 2021: 60 · 2020: 42 · 2019: 25 · 2018: 1
- FWCI
- 51.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computer (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence, blockchain, AI-blockchain integration, smart contracts, decentralized systems, security (computing), disruptive technologies, social impact
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