kaal:claim:4755632-019

The collective of reviewers in legacy code review is not incentivized to find flaws in the code, because the review is treated as the work product of the initial reviewer with minor input from follow-up reviewers rather than as a product of the collective.

The collective of reviewers is also not incentivized to find flaws in the code to optimize code as a work product of the collective.

Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024), Market for Code Reviews, p. 34
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 legacy hierarchical code review firms

failuresupport: arguedfailure: No Incentive to Find Flawsfamily: staking-and-incentive-misalignmentai-and-agentsrisk-and-incentivesopen-source-and-codecitation-and-knowledge

• restates kaal:claim:4734750-008 In hierarchical review, the first reviewer's output receives the highest priority and later reviewers add only...
• restates kaal:claim:3995709-013 In hierarchical legacy review processes the first reviewer's output gets the highest priority and follow on re...
• supports kaal:claim:4734750-009 Multiple reviewers asking clarifying questions tends to make code simpler and clearer and therefore higher qua...
• extends kaal:claim:4734750-010 Hierarchical code review undermines long-term participation by reviewers at the edges of the reviewer spectrum...

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