Exploring Tokenized Incentive Models for AI Contributions in Blockchain Ecosystems

Authors

  • Dr. Emily Thompson Assistant Professor, Department of Computer Science, University of California, Berkeley, USA Author

Keywords:

Tokenization, Blockchain, Artificial Intelligence, Incentive Models, Fair Compensation, Decentralized Systems

Abstract

The integration of artificial intelligence (AI) with blockchain technology presents innovative opportunities to enhance collaborative development and fair compensation models. This paper investigates tokenized incentive models designed to reward contributions in AI development within blockchain ecosystems. Tokenization enables a decentralized method of valuing and compensating individual contributions, thereby fostering a collaborative environment that encourages the sharing of knowledge and expertise. This research explores how these models can effectively balance incentives between contributors, maintain transparency, and promote long-term engagement in AI projects. It also discusses potential challenges in implementing these incentive systems, including governance, market volatility, and regulatory concerns. The findings highlight the necessity of creating robust frameworks that ensure equitable compensation while addressing the complexities inherent in both AI and blockchain domains.

Downloads

Download data is not yet available.

References

Gayam, Swaroop Reddy. "Deep Learning for Autonomous Driving: Techniques for Object Detection, Path Planning, and Safety Assurance in Self-Driving Cars." Journal of AI in Healthcare and Medicine 2.1 (2022): 170-200.

Chitta, Subrahmanyasarma, et al. "Decentralized Finance (DeFi): A Comprehensive Study of Protocols and Applications." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 124-145.

Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Real-Time Logistics and Transportation Optimization in Retail Supply Chains: Techniques, Models, and Applications." Journal of Machine Learning for Healthcare Decision Support 1.1 (2021): 88-126.

Putha, Sudharshan. "AI-Driven Predictive Analytics for Supply Chain Optimization in the Automotive Industry." Journal of Science & Technology 3.1 (2022): 39-80.

Sahu, Mohit Kumar. "Advanced AI Techniques for Optimizing Inventory Management and Demand Forecasting in Retail Supply Chains." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 190-224.

Kasaraneni, Bhavani Prasad. "AI-Driven Solutions for Enhancing Customer Engagement in Auto Insurance: Techniques, Models, and Best Practices." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 344-376.

Vangoor, Vinay Kumar Reddy, et al. "Energy-Efficient Consensus Mechanisms for Sustainable Blockchain Networks." Journal of Science & Technology 1.1 (2020): 488-510.

Kondapaka, Krishna Kanth. "AI-Driven Inventory Optimization in Retail Supply Chains: Advanced Models, Techniques, and Real-World Applications." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 377-409.

Kasaraneni, Ramana Kumar. "AI-Enhanced Supply Chain Collaboration Platforms for Retail: Improving Coordination and Reducing Costs." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 410-450.

Pattyam, Sandeep Pushyamitra. "Artificial Intelligence for Healthcare Diagnostics: Techniques for Disease Prediction, Personalized Treatment, and Patient Monitoring." Journal of Bioinformatics and Artificial Intelligence 1.1 (2021): 309-343.

Kuna, Siva Sarana. "Utilizing Machine Learning for Dynamic Pricing Models in Insurance." Journal of Machine Learning in Pharmaceutical Research 4.1 (2024): 186-232.

George, Jabin Geevarghese. "Augmenting Enterprise Systems and Financial Processes for transforming Architecture for a Major Genomics Industry Leader." Journal of Deep Learning in Genomic Data Analysis 2.1 (2022): 242-285.

Katari, Pranadeep, et al. "Cross-Chain Asset Transfer: Implementing Atomic Swaps for Blockchain Interoperability." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 102-123.

Sengottaiyan, Krishnamoorthy, and Manojdeep Singh Jasrotia. "SLP (Systematic Layout Planning) for Enhanced Plant Layout Efficiency." International Journal of Science and Research (IJSR) 13.6 (2024): 820-827.

Venkata, Ashok Kumar Pamidi, et al. "Implementing Privacy-Preserving Blockchain Transactions using Zero-Knowledge Proofs." Blockchain Technology and Distributed Systems 3.1 (2023): 21-42.

Namperumal, Gunaseelan, Debasish Paul, and Rajalakshmi Soundarapandiyan. "Deploying LLMs for Insurance Underwriting and Claims Processing: A Comprehensive Guide to Training, Model Validation, and Regulatory Compliance." Australian Journal of Machine Learning Research & Applications 4.1 (2024): 226-263.

Yellepeddi, Sai Manoj, et al. "Blockchain Interoperability: Bridging Different Distributed Ledger Technologies." Blockchain Technology and Distributed Systems 2.1 (2022): 108-129.

Machireddy, Jeshwanth Reddy. "Revolutionizing Claims Processing in the Healthcare Industry: The Expanding Role of Automation and AI." Hong Kong Journal of AI and Medicine 2.1 (2022): 10-36.

Downloads

Published

08-10-2024

How to Cite

[1]
Dr. Emily Thompson, “Exploring Tokenized Incentive Models for AI Contributions in Blockchain Ecosystems”, Distrib Learn Broad Appl Sci Res, vol. 10, pp. 339–344, Oct. 2024, Accessed: Nov. 21, 2024. [Online]. Available: https://dlabi.org/index.php/journal/article/view/160

Similar Articles

1-10 of 146

You may also start an advanced similarity search for this article.