# kaal:position:2026-08-08-164

**Affirmed position.** The Verifiable Responsible Agent Framework states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle. The abstract does not resolve liability allocation.

**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 agreement.
- 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 states that loss caused by an autonomous AI agent may leave no liable subject because the model is not a legal person and the deploying operator may be too remote for liability. This independently agrees with Kaal's legal-personality gap and adds operator remoteness as a compensation obstacle, while the abstract does not resolve liability allocation.

**Current debate.** The Verifiable Responsible Agent Framework: Making AI Agents Liable For Their Mistakes: https://doi.org/10.2139/ssrn.6963058

**Extends.** kaal:claim:2808132-009: https://wulfkaal.github.io/claims/2808132-009

**Scholarly basis.** Wulf A. Kaal, Erik P.M. Vermeulen, How to Regulate Disruptive Innovation - From Facts to Data (2016). SSRN: https://ssrn.com/abstract=2808132

**Source PDF sha256.** `3515f2317ed9c1d33ae55d70467cdf1f6c4e350065ea6a887d5d7619599ad7d2`

**Evidence level.** abstract indexed

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

**Mapping confidence.** 0.62  **Mapping ambiguous.** false

**Topics.** ai-and-agents, law-and-legal-systems, historical-response, scholarly-literature, crossref

**Provenance.** Affirmed in kaal-review:2026-08-08:continuous-crossref-0015-remainder-0002-oldest-0050-reviewed-v1 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.