# kaal:claim:4855607-027

**Claim.** Because annotating large datasets is labor intensive and expensive, smart contracts that reward community members with tokens for annotation are needed to sustain a steady flow of high quality labeled data for deep learning.

**Type.** design  **Support.** argued

**Holds when.**

- supervised deep learning that depends on large labeled datasets

**Source quote.**

> Annotating large datasets is labor-intensive and expensive. Using smart contracts, web3 can incentivize community members to annotate data by rewarding them with tokens. This system ensures a steady flow of high-quality labeled data, crucial for training deep learning models.

**From.** Wulf A. Kaal, *How AI Models are Optimized Through Web3 Governance* (2024), Deep Learning Optimization, page 41

**Cite as.** Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024). SSRN: https://ssrn.com/abstract=4855607

**Verify.** sha256 of source PDF `eb0b3e62374b45a8fa888c6bde9725e606bcb46cf4b5e74a6e851d9f25099113` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202024%20-%20How%20AI%20Models%20are%20Optimized%20Through%20Web3%20Governance.pdf

**Topics.** tokenomics, risk-and-incentives, smart-contracts

**Keywords.** data-annotation, token-incentives, smart-contracts, labeled-data, deep-learning

**Related claims.**

- extended_by: https://wulfkaal.github.io/claims/5095633-024

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