SINGAPORE -- HJS Foundation (Human Judgment Systems Foundation) released two complementary solutions: the Judgment Event Protocol (JEP) and the Human Judgment Structure (HJS) framework. As a minimalist open standard, JEP generates tamper-proof records of AI decision accountability, just like an aircraft black box; HJS embeds human judgment logic into AI operation processes — together, they transform “human oversight” from a regulatory requirement into a verifiable technical fact, providing an optional technical solution for AI accountability.

How to prove that AI decisions (such as loan approvals, medical diagnoses, border screenings, etc.) have undergone human review? JEP generates immutable audit trails of human intervention through four cryptographic primitives — Judge, Verify, Delegate, Terminate; HJS builds a controllable and accountable system to prevent risks such as AI drift and ensure that human judgment guides AI operations.

Current systems rely on alterable post-hoc documentation, while JEP and HJS work in tandem: JEP acts like an aviation black box, not judging performance but ensuring traceability; HJS embeds human oversight into AI workflows — together, they provide an undeniable factual basis for regulators, developers, and users.

Paired with the HJS framework, the JEP protocol provides a compliant technical option for trustworthy AI. Together, they achieve cross-platform and cross-model interoperability, solving core issues such as difficult accountability and inconsistent standards.