Detailed answer
Key answer: LERA-J is the judgment-formation function of the LERA architecture.
Core explanation
LERA-J is the judgment-formation function of the LERA architecture.
Its role is to form a structured basis for determining whether a proposed action should continue toward governance and possible execution.
An Agent may generate a plan, recommendation, command, or preferred option. But Agent reasoning is not yet LERA judgment.
Agent reasoning may focus on:
- completing a task;
- optimizing an objective;
- predicting an outcome;
- selecting an efficient route;
- maximizing performance;
- satisfying an instruction.
LERA-J considers the proposed action from a different perspective.
It asks what must be understood before the action may be governed.
At a public architectural level, LERA-J may consider factors such as:
- the relevant facts;
- the consequence of the proposed action;
- the reversibility or irreversibility of the outcome;
- the level of uncertainty;
- the reliability of available information;
- affected people, assets, systems, or institutions;
- feasible alternatives;
- the context level of the judgment;
- whether the action requires stronger governance.
LERA-J does not simply reproduce the Agent’s reasoning.
Its function is to form judgment facts and organize the information required for governance.
This separation is essential because a system can reason correctly about how to achieve an objective while still failing to judge whether the objective should be pursued in that way.
For example, a robotic system may determine that crossing a human-occupied area is the fastest way around an obstacle.
The route calculation may be correct.
LERA-J addresses a different set of questions:
- What is the human-proximity risk?
- Is the action reversible?
- What happens if the environment changes?
- Are safer alternatives available?
- Does the action move into a higher-consequence context?
- Is the available information sufficiently reliable?
LERA-J then provides a structured judgment basis for LERA-G.
The relationship can be summarized as:
The Agent proposes what can be done.
LERA-J forms judgment about the proposed action.
LERA-G governs whether execution may proceed.
LERA-J is therefore not the final permission authority. It does not independently grant execution.
Its engineering importance lies in ensuring that governance is not based only on raw Agent output, model confidence, or optimization results.
Governance must receive a structured judgment, not merely a machine recommendation.