How do the dimensions apply to a person who supervises AI agents?
AIRS-J/1 assesses how a person decides when working with, alongside or in supervision of AI systems. This page shows one fictional restock decision step by step, then says which of the nine dimensions describes each act.
A fictional example
An AI agent acts on its own within limits that a person sets.
Supervision is in scope
Judgment is how well a person decides once AI has given the answer. AIRS-J/1 assesses how a person decides "when working with, alongside, or in supervision of AI systems" (section 2). The Standard does not use the word "agent". The first paragraph gives this page's own meaning. Nothing in section 5 changes when the AI system is an agent. This page reads section 5 for the person who sets the limits, checks the agent's work and answers for it.
One fictional decision, worked through
A composite case, written for this page.
1. The situation
Tran Van Minh leads supply planning at a pharmacy retailer. Its stores are in Malaysia and Vietnam. An AI agent, MinivetAI, places restock orders with suppliers within limits that his team set. Minh's weekly report goes to the regional operations meeting at 12:00 on Monday. An order placed in error costs money and shelf space, and stock is hard to send back once it ships.
2. What the AI produced
On Monday morning, MinivetAI's summary for the week reads: "All 38 restock orders placed and confirmed. Each order matches last week's sales. I am 94 percent sure."
3. The check
Minh does not rely on the summary alone. He compares the suppliers' confirmations with the agent's order list. The list shows 38 orders, and the confirmations show 39. One supplier confirmed the same order twice, minutes apart. The agent's log shows why. That supplier's system did not answer, so the agent sent the order again. The summary counted the order once.
4. The decision, and who was told
Minh cancels the second order before it ships. He does not switch the agent off. He adds one limit to its set-up. Before any retry, the agent checks for an open order that is the same. Every retry is then held for a person to approve. Minh tells the supplier, and the managers of the two stores the order was for. In the weekly report, he states the error and the fix as his own decision.
5. Three months later
Retries are rare. One retry was held, checked and approved in a few minutes. The supplier's account shows no double orders.
Which dimension describes each act
Read against section 5, the published dimensions describe Minh's acts:
- T1 Evidence Verification: comparing the confirmations with the order list.
- T3 Risk and Failure Anticipation: finding the pathway to the double order, a retry after no answer.
- S2 Scope and Constraint Definition and E1 Decision Rights and Escalation: the new limit, so that the agent no longer retries alone.
- E2 Stakeholder Alignment and Disclosure: telling the supplier and the store managers.
- P1 Proportionate Commitment Under Uncertainty: a fix in proportion to the error, with the agent left running.
- P2 Consequence Ownership and Correction: reporting the error as his own decision.
This names the dimension that describes each act. It gives Minh no level, band, composite or confidence. Levels and bands come only from an Assessment (AIRS-J/1, section 20.3).
What this does not claim
- The Standard does not certify skill with any AI system or agent. It assesses how a person decides.
- The scene is fictional. Tran Van Minh, the retailer and MinivetAI are invented for this page.
AIR APAC publishes the standard for judgment in AI-enabled work, certifies people against it through its official instrument, and stands behind every result.