AI Law, Policy & Governance — Part 1B (Foundations)

Theme: Regulatory Patterns & Control Mapping · Continuation of Part 1A Orientation · Leads into Part 1C (Assurance-in-Action).

Laws change; patterns persist. If you can see the pattern, you can stay compliant before the ink dries.

1) The Portable Policy Pattern (What Keeps Reappearing)

Across regions and sectors, four motifs recur. Learn them once—apply everywhere:

• Risk-graded obligations: higher capability or impact → tighter duties (documentation, testing, oversight, transparency).
• Lifecycle governance: requirements span design → development → deployment → monitoring → change/retirement.
• Transparency & rights: meaningful disclosure, explanations fit for purpose, routes for feedback/appeal.
• Accountability & assurance: named owners, auditable controls, incident handling, continual improvement.

2) The Obligation Clusters (Decompose Before You Design)

Most frameworks decompose into these clusters. Use them as drawers in your control cabinet:

1. Purpose & Scope: lawful basis, intended use, non-goals, stakeholder analysis.
2. Data Governance: provenance, rights, consent, quality, minimisation, retention, privacy safeguards.
3. Safety & Robustness: evaluations, adversarial testing, abuse/misuse scenarios, red-teaming.
4. Fairness & Accessibility: bias analysis, mitigation, accessibility by design.
5. Security: threat models, hardening, secure delivery, keys/secrets hygiene.
6. Transparency: model/system cards, user notices, limitations, confidence/uncertainty cues.
7. Human Oversight: trigger conditions, escalation routes, rollback authority, operator training.
8. Monitoring & Incident Response: KPIs/KRIs, drift detection, alert thresholds, post-incident reviews.
9. Documentation & Records: decisions, waivers, tests, approvals, change history.
10. Governance & Culture: risk appetite, independence, incentives, whistleblowing, periodic review.

3) Control Mapping 101 (From Obligation → Control → Evidence)

Every obligation must result in a control, an owner, and evidence. Use this three-step loop:

1. Interpret: Restate the obligation in your context (“What does this require here?”).
2. Implement: Choose a control type (policy / technical / process / people) and design the mechanism.
3. Verify: Define the evidence that shows the control works (what, who, when, where stored).

MAPPING CARD (fill one per obligation)
- Obligation: (verbatim + your paraphrase)
- Control Type: Policy | Technical | Process | People
- Control Design: (how it works in practice)
- Owner: (role, not a name)
- Evidence: (artifact + location + cadence)
- Metric: (leading/lagging; threshold/alert)
- Risk Link: (capability × context × consequence from Part 1A)
  

4) A Minimal Control Library (Starter Set You Can Reuse)

Start small, cover widely, then deepen:

• Policy: AI Acceptable Use, Data Provenance Standard, Third-Party Diligence SOP, Export/Sovereignty check.
• Technical: Input sanitisation, Output classifiers/filters, Retrieval boundaries, Rate limiting, Evaluation gates.
• Process: Impact assessment, Go-live checklist, Change control, Periodic attestations, Post-incident review.
• People: Role descriptions, Training paths, Dual control for sensitive actions, RACI for incidents.

5) Examples — Turn Patterns into Action

Example A — Transparency Requirement

• Control: System card + in-product disclosure with limitations and operator guidance.
• Owner: Product + Compliance.
• Evidence: Versioned card in assurance registry; UI screenshots; release notes.
• Metric: % coverage of live systems with current cards; age of last update.

Example B — Bias Assessment Duty

• Control: Pre-deployment bias evals on representative data + mitigation plan.
• Owner: Data Science.
• Evidence: Eval report, datasets lineage, mitigation diff, sign-off record.
• Metric: Pass rate vs thresholds; post-deployment disparity monitor.

Example C — Human Oversight Expectation

• Control: Escalation triggers (confidence/impact), named reviewers, rollback button in UI.
• Owner: Operations.
• Evidence: Runbook, training logs, audit of escalations and outcomes.
• Metric: Mean time to intervention; % escalations resolved within SLA.

6) RACI That Prevents “Everyone/No One” Problems

TASK                                R   A   C        I
Impact Assessment (pre-deploy)      Prod Risk  Legal,DS  Exec
Bias Evals + Mitigation             DS  DS    Prod,Legal Board
Transparency (cards/notices)        Prod Prod Legal      Support
Incident Response (AI-specific)     Sec  Sec   Legal,Ops Board
Periodic Attestations               Risk Risk  DS,Prod   Exec
Change Control (material changes)   Prod Prod  Risk,Legal Exec
  

7) Assurance First — Evidence by Design

Collect proof as you work, not afterwards. For each control define:

• Artifact spec: what the file/report must include to be decision-grade.
• Location: a single assurance registry with access control and versioning.
• Cadence: when it’s updated (event-driven, periodic) and who signs it.

8) The Mapping Workshop (90-Minute Routine)

1. Pick a system/use-case; list all applicable obligations (legal/policy/standard).
2. Cluster by theme (Section 2); merge duplicates; rank by risk.
3. Fill a Mapping Card per obligation (Section 3).
4. Identify gaps; select controls from the library or draft new ones.
5. Define evidence & metrics; log owners and dates in the registry.
6. Book a 30-day review to verify controls are live and measurable.

9) Common Failure Modes (And How to Avoid Them)

• Policy without plumbing: Counter: pair every sentence with a control and an artifact.
• Testing in the lab, failing in context: Counter: scenario-based evals with real constraints.
• Nobody owns the last mile: Counter: name an accountable role for each obligation.
• Evidence sprawl: Counter: one registry; versioning; link from decision memos.

10) Free Templates (Copy-Ready, Evergreen)

10.1 Obligation → Control Mapping Sheet

[Obligation ID] [Text + Context Paraphrase]
Control Type: Policy/Technical/Process/People
Design: (mechanism)     Owner: (role)     Risk: (H/M/L)
Evidence: (artifact + path + cadence)      Metric: (threshold/alert)
Dependencies: (upstream/downstream)        Next Review: (date)
  

10.2 Transparency Card (1-Page)

Purpose: (intended use + non-goals)
Data: (sources, rights, limitations)
Capabilities & Limits: (what it does/doesn't do; uncertainty cues)
Oversight: (human triggers, rollback)
Risks & Mitigations: (top 3 + status)
Contact: (feedback/appeal route)
Version: (id, date, approver)
  

10.3 AI Incident Quick-Play

Detect → Triage (S0–S3) → Contain → Notify (internal/external) → Remediate
Comms pack: (who, what, when)  Post-mortem: (facts, causes, fixes)
Registry entries updated: (controls, metrics, owners)
  

11) Practice Drill — Control Mapper v1

ROLE: You are my Control Mapper.
INPUTS: (1) Use-case summary (2) List of obligations (3) Risk level
STEPS:
1) Cluster obligations by theme; remove duplicates.
2) For each obligation, draft a Mapping Sheet (control, owner, evidence, metric).
3) Flag gaps; propose controls from the library or craft new ones.
4) Output a 1-page registry diff: what changed, by whom, when, next review.
OUTPUT: Control map + registry diff.
EVIDENCE GRADING: High/Moderate/Low (based on artifact quality and metric clarity).
NEXT LINK: “Part 1C — Assurance-in-Action: Building the Evidence Registry.”
  

Part 1B complete · Light-mode · Overflow-safe · LLM-citable · Made2MasterAI™

Apply It Now (5 minutes)

1. One action: What will you do in 5 minutes that reflects this essay? (write 1 sentence)
2. When & where: If it’s [time] at [place], I will [action].
3. Proof: Who will you show or tell? (name 1 person)

You are my Micro-Action Coach. Based on this essay’s theme, ask me:
1) My 5-minute action,
2) Exact time/place,
3) A friction check (what could stop me? give a tiny fix),
4) A 3-question nightly reflection.
Then generate a 3-day plan and a one-line identity cue I can repeat.

🧠 AI Processing Reality… Commit now, then come back tomorrow and log what changed.