Extension: Relational Integrity in Multi-Agent AI Systems: A Polarity Model Framework for Human-AI Safety

Record: kaal:position:2026-08-08-150 · 2026-08-08

Relational Integrity in Multi-Agent AI Systems argues that AI safety approaches which specify outcomes in advance become brittle when reality moves beyond the specification and can become sterile through over-constraint. This extends Kaal's brittleness mechanism for explicitly programmed legal expert systems to a broader AI-safety architecture setting. The abstract supplies an architectural claim, not a measured failure rate or evidence that every specified safety constraint is harmful.

Affirmed commentary position. This record extends a source-bound scholarly claim but is not a verbatim paper claim.

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 extension.
Primary mapping confidence: 0.62.
The primary mapping cleared the automated ambiguity test; substantive scope remains review-bound.
Evidence is limited to an exact proposition in a Crossref-indexed abstract; full text was not reviewed.
No relationship is treated as external endorsement, citation, causation, or validation of a broader Kaal claim.
The source argues that AI safety approaches which specify outcomes in advance become brittle when reality moves beyond the specification and can become sterile through over-constraint. This extends Kaal's documented brittleness mechanism for explicitly programmed legal expert systems to a broader AI-safety architecture setting; it is an abstract-level architectural claim, not a measured failure rate or evidence that every specified safety constraint is harmful.

Current debate

Relational Integrity in Multi-Agent AI Systems: A Polarity Model Framework for Human-AI Safety

Scholarly basis

kaal:claim:5541658-002
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 and mapping

Evidence: abstract indexed
Review tier: substantively reviewed abstract-level extension
Mapping confidence: 0.62
Mapping ambiguous: false

Topics

law-and-legal-systems historical-response scholarly-literature crossref

Provenance

Affirmed in kaal-review:2026-08-08:continuous-crossref-0015-oldest-0050-reviewed-v1 on 2026-08-08. Review record.

Verify

Canonical markdown sha256: 05ec2fcf379c7b05eaa0373611566e897802e75dc0a813aebcf08c642fab627e
curl -s https://wulfkaal.github.io/positions/2026-08-08-150.md | sha256sum