Because a limited number of players control the code review market and its outputs, the quality of code review is often suboptimal, and clients have little or no recourse when code proves flawed even after functionality and quality review.
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Moreover, there is little or no recourse for clients in cases in which the code proved to be flawed even after functionality and quality review.
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Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024), Current Players in the Field: No Controls, p. 37 https://ssrn.com/abstract=4755632 · source PDF
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Wulf A. Kaal, AI Learning - Decentralized Governance to Optimize Human Output Datasets for AI Learning (2024). SSRN: https://ssrn.com/abstract=4755632
extendskaal:claim:4734750-020 Clients have little or no recourse when reviewed code turns out to be flawed even after a functionality and qu...
restateskaal:claim:4734750-006 The 2024 code review market is dominated by a few centralized firms that can charge exorbitant, monopoly-like ...
supportskaal:claim:3995709-026 Decentralized code review underwriting makes the code review market more efficient because it democratizes the...
extendskaal:claim:4734750-015 Market concentration among the top five audit firms itself creates high barriers to entry for new participants...
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