# kaal:claim:3128900-003

**Claim.** The performance of an AI neural network's learning algorithm during supervised training rises with the quality and quantity of the labelled datasets it is trained on, which ties AI progress directly to micro task work.

**Type.** mechanism  **Support.** evidenced

**Holds when.**

- supervised training process

**Source quote.**

> The higher the quality and quantity of such labelled datasets the better the AI neural network's learning algorithm during the supervised training process.

**From.** Wulf A. Kaal, *Decentralized Mechanical Turk Through Verified Reputation* (2018), 1 Problems in Centralized Mechanical Turk, page 6

**Cite as.** Wulf A. Kaal, Decentralized Mechanical Turk Through Verified Reputation (2018). SSRN: https://ssrn.com/abstract=3128900

**Verify.** sha256 of source PDF `381d72e85d976e2af852e8ec3bba87bc6a05ccb3349a2c3dd6f9e64de96ab4b0` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202018%20-%20Decentralized%20Mechanical%20Turk%20Through%20Verified%20Reputation.pdf

**Topics.** ai-and-agents, education-and-practice

**Keywords.** training-data, artificial-intelligence, data-quality, micro-tasks

**Related claims.**

- restated_by: https://wulfkaal.github.io/claims/4755632-008
- restated_by: https://wulfkaal.github.io/claims/4734750-031
- extended_by: https://wulfkaal.github.io/claims/4755632-041
- extended_by: https://wulfkaal.github.io/claims/4734750-032

**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.