Citation:

Gaurav Kashyap, 2023. "AI-Driven Smart Contracts for Blockchain Networks", ESP Journal of Engineering & Technology Advancements, 3(4): 85-90.

Abstract:

With its decentralized structure and unchangeable record-keeping system, blockchain technology has gained widespread acceptance in a number of industries, including supply chain management, healthcare, and finance. However, there are issues with scalability, security, and efficiency with its conventional implementation. One way to automate transactions and processes on the blockchain is through smart contracts, which are self-executing agreements with the terms of the contract directly written into lines of code. When combined with smart contracts, artificial intelligence (AI) can unleash a new range of capabilities, such as predictive analytics, adaptive contract execution, and autonomous decision-making. The potential, design, implementation, and effects on blockchain networks of AI-driven smart contracts are the main topics of this paper. It explores the advantages, difficulties, and uses of this integration in addition to the direction that AI-enhanced smart contract systems will take in the future.

References:

[1] V. Mehta and S. More, “Smart Contracts: Automated Stipulations on Blockchain,” Jan. 01, 2018. doi: 10.1109/iccci.2018.8441347.

[2] S. Chattopadhyay, “Smart Contract Technology for Blockchain-based Systems: Design and Implementation Challenges.,” Dec. 15, 2020, Karadeniz Technical University. doi: 10.17762/turcomat.v11i3.13598.

[3] B. Hu et al., “A comprehensive survey on smart contract construction and execution: paradigms, tools, and systems,” Patterns, vol. 2, no. 2. Elsevier BV, p. 100179, Feb. 01, 2021. doi: 10.1016/j.patter.2020.100179.

[4] K. Salah, M. H. ur Rehman, N. Nizamuddin, and A. Al‐Fuqaha, “Blockchain for AI: Review and Open Research Challenges,” Jan. 01, 2019, Institute of Electrical and Electronics Engineers. doi: 10.1109/access.2018.2890507.

[5] H. R. - and B. G. -, “Artificial Intelligence Applied to Contracts: Panacea or Poison?,” May 31, 2023. doi: 10.36948/ijfmr.2023.v05i03.3245.

[6] lhizaoui, “How AI is Changing Contracts,” Jan. 01, 2020. Accessed: Nov. 2023. [Online]. Available: https://www.ajcact.org/publications/how-ai-is-changing-contracts/

[7] C. Maple et al., “The AI Revolution: Opportunities and Challenges for the Finance Sector,” Jan. 01, 2023, Cornell University. doi: 10.48550/arxiv.2308.16538.

[8] N. Kshetri, “Complementary and Synergistic Properties of Blockchain and Artificial Intelligence,” Nov. 01, 2019, IEEE Computer Society. doi: 10.1109/mitp.2019.2940364.

[9] C. Clifton, R. Blythman, and K. Tulusan, “Is Decentralized AI Safer?,” Jan. 01, 2022, Cornell University. doi: 10.48550/arxiv.2211.05828.

[10] Z. Zhang, X. Song, L. Liu, J. Yin, Y. Wang, and D. Lan, “Recent Advances in Blockchain and Artificial Intelligence Integration: Feasibility Analysis, Research Issues, Applications, Challenges, and Future Work,” Jun. 24, 2021, Hindawi Publishing Corporation. doi: 10.1155/2021/9991535.

[11] K. D. Pandl, S. Thiebes, M. Schmidt-Kraepelin, and A. Sunyaev, “On the Convergence of Artificial Intelligence and Distributed Ledger Technology: A Scoping Review and Future Research Agenda,” IEEE Access, vol. 8. Institute of Electrical and Electronics Engineers, p. 57075, Jan. 01, 2020. doi: 10.1109/access.2020.2981447.

[12] Y. Bengio, “Learning Deep Architectures for AI,” Foundations and Trends® in Machine Learning, vol. 2, no. 1, pp. 1-127, Jan. 2009.

[13] A. Radford et al., "Learning Transferable Visual Models From Natural Language Supervision," in Proceedings of the 2021 International Conference on Machine Learning (ICML), Jul. 2021.

[14] T. H. Nguyen and S. T. Pham, "A Survey of Transfer Learning Techniques," International Journal of Computer Science & Engineering, vol. 8, no. 2, pp. 45-56, Apr. 2020.

[15] X. Zhang et al., “Few-Shot Learning with Transferable Representations,” Proceedings of NeurIPS, Dec. 2019.

[16] R. A. Schuler et al., “Domain Adaptation for Transfer Learning: A Survey,” Artificial Intelligence Review, vol. 40, no. 3, pp. 2005-2023, Mar. 2022.

Keywords:

Blockchain, Artificial Intelligence (AI), smart contracts, Decentralization, Machine Learning (ML).