# Bias detection

`kaal:entity:bias-detection`

**Status.** derived

This node is assembled mechanically from the 2 claims that carry the concept tag `bias-detection`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

2 claims across 2 works, 2024 to 2024.

**2024**

- [4796714-007](https://wulfkaal.github.io/claims/4796714-007) [failure/evidenced] *(failure mode)* -- The black box character of deep learning models is a governance failure and not merely a technical inconvenience: opacity obstructs debugging, obscures bias detection and mitigation, and prevents comprehension of how inputs become outputs.
  > This opacity can obstruct the debugging process, obscure bias detection and mitigation, and hinder comprehension of AI decision-making.
  Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714
- [4941807-008](https://wulfkaal.github.io/claims/4941807-008) [failure/evidenced] *(failure mode)* -- The opacity of deep learning models obstructs debugging, obscures the detection and mitigation of bias, and prevents comprehension of how AI decisions are reached.
  > This opacity can obstruct the debugging process, obscure bias detection and mitigation, and hinder comprehension of AI decision-making.
  Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/bias-detection.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.