# kaal:position:2026-08-08-011

**Affirmed position.** Rizwan Tanveer independently supports Kaal's source-bound position through Explainability, Transparency, and Accountability in AI Systems. The indexed proposition states that first, post-hoc explainability methods, including LIME and SHAP, are operationally available but do not guarantee the faithfulness, stability, or comprehensibility of their explanations, and are themselves subject to adversarial manipulation. This bears on Kaal's claim that post hoc explainability techniques do not by themselves establish trustworthiness; the explanations they produce must additionally be verified against human knowledge. The external work independently identifies faithfulness, stability, comprehensibility, and adversarial-manipulation limits in post-hoc explainers, supporting Kaal's warning that explanation output alone is not trustworthiness. The response is limited to the indexed proposition and does not imply review of the full external work.

**Status.** affirmed  **Published.** 2026-08-08

**Holds when.**

- The response is limited to the retrieved source proposition and mapped Kaal claim unless fuller source review supports a broader conclusion.
- External evidence level: abstract indexed.
- Mapping review tier: substantively reviewed abstract-level qualification.
- Primary mapping confidence: 0.5.
- The primary mapping cleared the automated ambiguity test; substantive scope remains review-bound.
- Evidence is limited to an indexed abstract proposition and bibliographic identity; full text was not reviewed in this pass.
- The response does not treat lexical overlap or the original automated mapping score as evidence.
- The relationship is limited to the stated proposition and the mapped Kaal claim.

**Current debate.** Explainability, Transparency, and Accountability in AI Systems: https://doi.org/10.2139/ssrn.6767278

**Extends.** kaal:claim:5541658-012: https://wulfkaal.github.io/claims/5541658-012

**Scholarly basis.** Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658

**Source PDF sha256.** `e543a2d698fcd522d4d02e034cc9ee1344d0015d2c824b40b9e05ab7c0728c60`

**Evidence level.** abstract indexed

**Mapping review tier.** substantively reviewed abstract-level qualification

**Mapping confidence.** 0.5  **Mapping ambiguous.** false

**Topics.** ai-and-agents, reputation, historical-response, scholarly-literature, crossref

**Provenance.** Affirmed in kaal-review:2026-08-08:backlog-substantive-0001-reviewed-v2 at https://kaal-signal-desk.wulf577462.chatgpt.site/#review.

**Record type.** This is a dated commentary position that extends a scholarly corpus claim. It is not a verbatim claim extracted from the paper.

**Canonical form.** This markdown file is the canonical hashed representation of the position.