# kaal:claim:4755632-041

**Claim.** Combining decentralized governance with gamification of micro task work is the condition under which gamification does not compromise dataset quality and accuracy, and this combination is what allows gamified micro task work to scale high-quality diverse datasets for AI learning.

**Type.** condition  **Support.** argued

**Holds when.**

- applies to the ALE Platform design

**Source quote.**

> combination of decentralized governance and gamification of micro task work, ALE Platform ensures that gamification techniques do not compromise the quality and accuracy

**From.** Wulf A. Kaal, *AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning* (2024), Gamification of Micro Task Work, page 52

**Cite as.** Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632

**Verify.** sha256 of source PDF `972ccebf0c06ac1767a9e443bb95942b7670e806a63c25ee817c368a64c8eca8` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202024%20-%20AI%20Learning%20-%20Decentralized%20Governance%20to%20Optimize%20Human%20Output%20Datasets%20for%20AI%20Learning.pdf

**Topics.** decentralization, governance-design, empirical-evidence, ai-and-agents

**Keywords.** decentralized-governance, gamification, dataset-accuracy, ai-learning, scaling

**Related claims.**

- extends: https://wulfkaal.github.io/claims/3128900-003
- extends: https://wulfkaal.github.io/claims/4734750-031
- extended_by: https://wulfkaal.github.io/claims/6244278-033
- extends: 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.