📘 AI-Assisted Learning Workbook #9
Power, Governance, and Responsibility in AI Systems
By Laurence “Lars” Svekis
When intelligence scales, power concentrates.
The real question is not whether systems work — but who they work for.
🎯 Who This Workbook Is For
This workbook is for:
- Leaders and decision-makers
- Educators and policy influencers
- Technologists building platforms
- Managers shaping rules and incentives
- Anyone asking: “Who controls the system?”
📌 Core Shift:
From participating in systems → understanding and shaping them
🧠 Workbook Philosophy
AI does not remove power dynamics.
It accelerates them.
This workbook trains learners to:
- See power structures clearly
- Understand how incentives shape behavior
- Recognize hidden decision-makers
- Use AI responsibly within systems
- Protect human agency at scale
🧩 Workbook Structure (12 Issues)
Each issue focuses on system-level thinking, not personal tactics.
1️⃣ WHERE POWER ACTUALLY LIVES
Goal: Identify real control points.
Exercise
Who sets the rules?
Who benefits most?
Who absorbs the risk?
📌 Power is rarely where it’s advertised.
2️⃣ AI AS A FORCE MULTIPLIER
Goal: Understand amplification effects.
Exercise
What existing power does AI strengthen here?
📌 AI rarely creates new power — it scales existing power.
3️⃣ INCENTIVES OVER INTENTIONS
Goal: Stop judging systems by promises.
Exercise
What behavior does this system reward?
What does it quietly punish?
📌 Incentives outvote values.
4️⃣ GOVERNANCE VS CONTROL
Goal: Separate healthy governance from domination.
Exercise
Who can say no?
Who can override decisions?
📌 A system without refusal points is fragile.
5️⃣ TRANSPARENCY & OPAQUE DECISIONS
Goal: Detect hidden logic.
Exercise
What decisions are automated?
Who understands how they work?
📌 Opacity concentrates power.
6️⃣ BIAS AT SCALE
Goal: Recognize systemic bias.
Exercise
Which groups are consistently advantaged or harmed?
📌 Bias becomes structural when it repeats quietly.
7️⃣ RESPONSIBILITY GAPS
Goal: Prevent “nobody decided this.”
Exercise
When harm occurs, who is accountable?
📌 Diffused responsibility enables harm.
8️⃣ HUMAN OVERSIGHT & FAILSAFES
Goal: Protect agency.
Exercise
Where must humans retain final authority?
📌 Automation without oversight is abdication.
9️⃣ PARTICIPATION & VOICE
Goal: Ensure affected people matter.
Exercise
Who is impacted but unheard?
📌 Exclusion is a governance failure.
🔟 RESISTING TECH DETERMINISM
Goal: Reject “inevitable” narratives.
Exercise
Who benefits from claiming this is unavoidable?
📌 Inevitability is often a power move.
1️⃣1️⃣ DESIGNING FOR HUMAN DIGNITY
Goal: Put people before efficiency.
Exercise
Does this system preserve dignity under failure?
📌 How systems treat edge cases reveals their values.
1️⃣2️⃣ THE POWER & GOVERNANCE PLAYBOOK
Goal: Define personal responsibility within systems.
Final Prompts
I challenge systems when…
I refuse to participate when…
I use AI responsibly by…
🔗 How Workbook #9 Fits the Series
| Workbook | Focus |
|---|---|
| #1–3 | Learning, thinking, action |
| #4–5 | Leadership, ethics |
| #6–7 | Meaning, creativity |
| #8 | Collective intelligence |
| #9 | Power & governance |
The arc now becomes:
Individual → Collective → Institutional Intelligence
🚀 Ideal Uses
- Leadership programs
- University AI ethics courses
- Policy & governance discussions
- Tech organizations
- Responsible AI initiatives