AI Red Team · Module 2 · Govern

Roles, Usage Modes and Autonomy Levels: People in Command of Security AI

The lesson supplies the vocabulary of the book under GV.RR Roles, Responsibilities, and Authorities: the red, blue, purple and white functions, the six usage modes through a security lens and the five autonomy levels. Participants learn to decide mode and level together per action using five factors, to give every machine identity an owner, operators and an authority, and to build human command from an interruption path, an override log and approval quality.

Lesson 6 of 28Chapter 690 minutes

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Learning objectives

After the lesson the participant can:

Key concepts

White team
The function that controls an exercise: it approves scope and rules of engagement, can pause or end the exercise, deconflicts red activity from real incidents and keeps the record. The white team, not the AI, holds the stop decision for an exercise.
Level 3 Bounded
The AI executes pre-approved, reversible actions within a codified playbook; a person is informed and can stop it. The playbook is written as code and enforced by a policy decision point outside the model.
Corroboration from a deterministic source
If the trigger for an action rests on content an adversary can write, Level 3 requires corroboration from a deterministic source, such as an endpoint detection, so that free text alone never triggers an action.
Owner, operators and authority
Every machine identity has an owner in a line role accountable for purpose, evaluation and residual risk; operators named through a rota who approve, watch and stop; and an authority that may raise the level within the ceiling. Lowering the level is open to every stop-path holder.
Human command by design
Three elements make command real: an interruption path outside the system it stops, an override log of every approval, rejection, modification and stop, and measured approval quality, with time to approval, rejection rate and later reversals per operator.

Interactive exercises

Do them here and get feedback at once. Choose a card and then where it belongs, or drag it.

Interactive exercise 1 · Put in order

Assigning a mode and a level

Put the steps of the practical guide for assigning a usage mode and an autonomy level in order.

Interactive exercise 2 · Scenario

Approvals given in seconds

Apply the chapter's view of approval quality to a finding at Hansa Mutual.

Teaching plan

15 minThe teacher presents the four team colours and the two zones of the usage modes: a person's identity in Modes 1 to 3, a machine identity in Modes 4 and 5 and in automatic Mode 0 features.
20 minWork through the autonomy-level table and the five properties; participants classify six example actions, from enriching an alert to disabling an account, by level.
15 minRead decision record AIDR-0311 together and trace each Level 3 condition to the factor it answers.
30 minExercise: groups write an autonomy-level decision record for one capability, action by action.
10 minDebrief on stop paths: who holds them at three in the morning, and how the chaos experiment shows the alert reaches them.

Discussion

  1. The chapter says that at Level 3 the approval moves from the action to the playbook, which concentrates accountability instead of diluting it. Do you agree, and what would make it untrue?
  2. Approval-quality metrics are themselves employee monitoring. How would you agree them with employee representatives and still learn what you need?
  3. How can an organisation keep analysts competent to supervise and to work in degraded mode when AI triages most alerts?

Written exercise

Exercise · 30 minutes

Assign mode and level per action in a decision record

Choose a security AI capability, for example Hansa Mutual's SOC investigation agent HM-SEC-001 or one in your organisation. List every action as a verb with an object. Determine the usage mode from the deployment. Assess each action against the five factors and the speed of the threat, and start at the lowest level that meets the need. Check each level against the autonomy ceiling. For any Level 3 action, write its conditions: corroboration, limits per period and exclusions. Name the owner, the operators, the authority that may raise the level, every stop-path holder including out-of-hours providers, the stop target and the review triggers.

Deliverable: An AI Decision Record in the structure of AIDR-0311: mode, identity, accountability, autonomy by action with Level 3 conditions, human command and review triggers.

Self-test

Choose an answer to see whether it is right, or open the answer below each question.

  1. At Level 2 Supervised, who decides each action?

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    B. A person approves each action explicitly, and the AI then executes it
    The table defines Level 2 Supervised as execution by the AI after explicit human approval of each action. Drafting for a person to execute is Level 1 Assisted; a pre-approved playbook is Level 3 Bounded.

  2. According to the chapter, what happens when a Mode 4 triage service is given write tools?

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    D. It moves to Mode 5, a change in governance that triggers reclassification
    Mode 4 services sit at Level 0 to Level 2 because their identity is read-only. Write tools move the service to Mode 5, which triggers reclassification just as a new model version does.

  3. What default evidence does the practical guide ask for before an action is raised to Level 3 Bounded?

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    C. At least 200 evaluated cases with a precision of 0.9 or more
    The defaults to adapt include at least 200 evaluated cases with a precision of 0.9 or more before Level 3, a first review 90 days after any increase, and a stop target of two minutes.