kaal:position:2026-07-31-7767

Ai-Driven Autonomous Vehicles And Legal Liability: Redefining Accountability In Human-Ai Collaborative Systems presents the following source proposition: The research focuses on how the decisions of machine learning algorithms in AVs are interpreted by the law. This proposition is pertinent to Kaal's source-bound claim that Under certain restrictive assumptions it has been proven that no protocol can guarantee fair exchange with decentralized arbiters, so no design on this architecture can promise absolute certainty of fair machine arbitration. The proposed response is an extension: the relationship should remain limited to the retrieved source proposition and the mapped Kaal claim unless fuller source review supports a broader conclusion.

• 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: moderate-confidence claim review.
• Primary mapping confidence: 0.385.
• The source-to-claim mapping remains explicitly ambiguous and is published with that limitation.

Ai-Driven Autonomous Vehicles And Legal Liability: Redefining Accountability In Human-Ai Collaborative Systems

kaal:claim:3125822-036
Craig Calcaterra, Wulf A. Kaal, Vlad Andrei, Blockchain Infrastructure for Measuring Domain Specific Reputation in Autonomous Decentralized and A (2018). SSRN: https://ssrn.com/abstract=3125822
Source PDF sha256: d4d0bbaa3260968226186131d60e6d64a53e904d94e4295c61fd17042f1191ef

Evidence: abstract indexed
Review tier: moderate-confidence claim review
Mapping confidence: 0.385
Mapping ambiguous: true

defidecentralizationlaw-and-legal-systemshistorical-responsescholarly-literaturecrossref

Affirmed in kaal-review:2026-07-31:streaming-etl-0010 on 2026-07-31. Review record.

Canonical markdown sha256: 734929269428a9de5e72a8f09fb79fabd833e9ab019b89ae7e46dfa49eef3df7
curl -s https://wulfkaal.github.io/positions/2026-07-31-7767.md | sha256sum