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Intersections of Web3 and AI -- View in 2024

David Hyland-Wood, Sandra Johnson

Abstract

This paper summarises the intersection of Web3 and AI technologies, synergies between these technologies, and gaps that we suggest exist in the conception of the possible integrations of these technologies. The summary is informed by a comprehensive literature review of current academic and industry papers, analyst reports, and Ethereum research community blogposts. We focus our contribution on the perceived gaps and detail some novel approaches that would benefit the blockchain/Web3 ecosystem. We believe that the overview presented in this paper will help guide researchers interested in the intersection of Web3 and AI technologies.

Intersections of Web3 and AI -- View in 2024

Abstract

This paper summarises the intersection of Web3 and AI technologies, synergies between these technologies, and gaps that we suggest exist in the conception of the possible integrations of these technologies. The summary is informed by a comprehensive literature review of current academic and industry papers, analyst reports, and Ethereum research community blogposts. We focus our contribution on the perceived gaps and detail some novel approaches that would benefit the blockchain/Web3 ecosystem. We believe that the overview presented in this paper will help guide researchers interested in the intersection of Web3 and AI technologies.

Paper Structure

This paper contains 23 sections, 6 figures.

Table of Contents

  1. Introduction
  2. The Impact of ai on the Economy
  3. Unintended Consequences
  4. Structure of this Paper
  5. Literature Review
  6. Overview
  7. Applications of Web3 and AI
  8. Sustainability
  9. Non-LLM-based AI
  10. Ownership and Copyright
  11. Philosophical and Ethical Implications
  12. Future Prospects and Research Directions
  13. Research Gap Analysis
  14. Risks and Mitigations
  15. Organisational Risks
  16. ...and 8 more sections

Figures (6)

  • Figure 1: Evolving relationship between Web3 and AI
  • Figure 2: There are many branches of ai (After: Chethan Kumar GN, Incedo Technologies)
  • Figure 3: Model learning performance vs model explainability (image by gunning2019)
  • Figure 4: Taxonomy mindmap of machine learning interpretability techniques. (image by linardatos_pantelis_explainable_2021)
  • Figure 5: Example user chat with a blockchain-aware llm
  • ...and 1 more figures