# Labeled data

`kaal:entity:labeled-data`

**Status.** derived

This node is assembled mechanically from the 3 claims that carry the concept tag `labeled-data`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

3 claims across 3 works, 2024 to 2024.

**2024**

- [4734750-031](https://wulfkaal.github.io/claims/4734750-031) [condition/argued] -- Supervised learning currently depends on labeled data produced by micro task work, so the evolution and growth of AI is correlated with the evolution and growth of micro task work.
  > currently, supervised learning depends on labeled data that is produced via micro task work
  Wulf A. Kaal, Code Review DAO (2024). SSRN: https://ssrn.com/abstract=4734750
- [4755632-008](https://wulfkaal.github.io/claims/4755632-008) [mechanism/argued] -- The quality and quantity of labeled datasets directly governs the performance of the neural network's learning algorithm during supervised training, so the evolution of AI is correlated with the evolution of micro task work.
  > The higher the quality and quantity of such labeled datasets the better the AI neural network's learning algorithm during the supervised training process.
  Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632
- [4855607-027](https://wulfkaal.github.io/claims/4855607-027) [design/argued] -- 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.
  > 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.
  Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024). SSRN: https://ssrn.com/abstract=4855607

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/labeled-data.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.