kaal:claim:4755632-040

Paying workers a share of incoming compensation pro rata to their reputation scores makes rigor self-enforcing, because workers who do not engage with the required care lose their spot in the reputation rankings and thereby lose their share of the job fee distribution.

they sacrifice their spot in the rankings of reputation scores which affects their participation in the job fee distribution, which is paid out pro rata to the respective reputation scores.

Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024), Gamification of Micro Task Work, p. 50
https://ssrn.com/abstract=4755632 · source PDF

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

• applies to the ALE Platform fee distribution design

mechanismsupport: arguedreputationrisk-and-incentives

• generalizes kaal:claim:4855607-029 In federated learning, validation pools coordinated by smart contracts should dispense rewards pro rata to the...

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