# kaal:claim:4796714-017

**Claim.** Using human judgment to uncover unconscious bias in AI can perpetuate the very biases it is meant to remove, because human reviewers carry their own implicit biases and may lack the expertise to identify bias in complex AI systems.

**Type.** failure  **Support.** argued

**Holds when.**

- applies to human in the loop bias mitigation programs
- holds where reviewers lack technical expertise or bias awareness

**Source quote.**

> While human judgment is integral to risk management and bias mitigation, it inherently carries its own biases. Relying on human judgment to uncover unconscious biases in AI may inadvertently perpetuate these biases rather than eliminate them.

**From.** Wulf A. Kaal, *AI Governance* (2024), Challenges, page 29

**Cite as.** Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714

**Verify.** sha256 of source PDF `59fa63bae179e8f9b6b8efbdf90cee28400276512a1b04f9f579a48641305c93` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202024%20-%20AI%20Governance.pdf

**Failure mode.** human oversight bias recursion  (family: ai-oversight-and-alignment-gap)

**Topics.** institutional-design

**Keywords.** bias-mitigation, human-oversight, implicit-bias, human-in-the-loop

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