Admin: Fix 2 internal link(s)

2026-03-16T16:28:09Z

Fix 2 internal link(s)

← Older revision		Revision as of 16:28, 16 March 2026
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	== 🧭 Why this matters (Strategists start here) ==		== 🧭 Why this matters (Strategists start here) ==

	Individual verification habits (from [[~~Exercises/Ethical Prompting/Ep Intermediate 01~~\|EP-Intermediate-01]]) don't scale to teams. When five people use AI differently with different standards, the team's AI output quality is only as good as the weakest link. A governance framework creates '''shared standards without bureaucracy''' — it tells people what's safe to do quickly and what requires care, without making every AI interaction feel like a compliance exercise. This is also the document organizations will pay for: a practical, calibrated AI usage policy that actually gets followed.		Individual verification habits (from [[The Verification Checklist\|EP-Intermediate-01]]) don't scale to teams. When five people use AI differently with different standards, the team's AI output quality is only as good as the weakest link. A governance framework creates '''shared standards without bureaucracy''' — it tells people what's safe to do quickly and what requires care, without making every AI interaction feel like a compliance exercise. This is also the document organizations will pay for: a practical, calibrated AI usage policy that actually gets followed.

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	You've reached the advanced level for Ethical Prompting & Judgment. From here, consider:		You've reached the advanced level for Ethical Prompting & Judgment. From here, consider:
	* Presenting this framework to your actual team and iterating based on feedback		* Presenting this framework to your actual team and iterating based on feedback
	* Combining this with [[~~Exercises/~~Agent ~~Collaboration/Ac Advanced 01~~\|AC-Advanced-01]] to add governance to multi-agent workflows		* Combining this with [[Design Your Agent Workflow\|AC-Advanced-01]] to add governance to multi-agent workflows
	* Building a case study of how the framework changed AI usage behavior in your team		* Building a case study of how the framework changed AI usage behavior in your team

Admin: Imported from AI Fluency Playbook

2026-03-16T16:10:07Z

Imported from AI Fluency Playbook

New page

''Design a practical AI governance framework for a team or project. 40 minutes.''

<blockquote>
'''One-liner:''' Design a practical AI governance framework for a team or project — covering when to use AI, how to verify outputs, and what requires human judgment.
</blockquote>

----

== 🔧 Jump in (Tinkerers start here) ==

Pick a real team, project, or organization you work with. You're going to design an AI usage framework they could actually adopt.

'''Step 1 — Map the AI touchpoints.''' Send this prompt:

<blockquote>
I'm designing an AI governance framework for a '''[team type/project type]''' that does '''[describe the work]'''. Map out all the places where team members might use AI in their workflow. For each touchpoint, classify the risk level:

- '''Low risk:''' AI errors are easily caught and consequences are minor (e.g., drafting internal emails, brainstorming)
- '''Medium risk:''' AI errors could waste significant time or create confusion (e.g., research summaries, data analysis, first drafts of client deliverables)
- '''High risk:''' AI errors could cause reputational, legal, or financial harm (e.g., published content, financial recommendations, legal language, customer-facing decisions)

Present this as a table with: Touchpoint | Description | Risk Level | Why
</blockquote>

'''Step 2 — Design the verification tiers.''' Based on the risk map, create a tiered verification system:

<blockquote>
Based on the risk map above, design a 3-tier verification system:

'''Tier 1 (Low risk):''' What's the minimum verification needed? What can proceed without review?
'''Tier 2 (Medium risk):''' What checks are required? Who reviews? What's the turnaround expectation?
'''Tier 3 (High risk):''' What's the full review process? Who signs off? What documentation is needed?

For each tier, specify:
- Verification steps (checklist)
- Who is responsible
- What "approved" looks like
- What happens when issues are found
</blockquote>

'''Step 3 — Write the team guidelines.''' Now produce the actual document:

<blockquote>
Write a 1-page "AI Usage Guidelines" document for this team. It should be practical, not corporate. Include:

1. '''When to use AI''' — Green light scenarios
2. '''When to be careful''' — Yellow light scenarios with required verification
3. '''When NOT to use AI''' — Red light scenarios or scenarios requiring explicit approval
4. '''Verification standards''' — The tier system from above, simplified
5. '''Attribution''' — When and how to disclose AI usage
6. '''Escalation''' — What to do when you're unsure whether AI use is appropriate

Write it in the tone of a senior colleague giving practical advice, not a legal department issuing mandates.
</blockquote>

'''Step 4 — Red-team the framework.''' Test it:

<blockquote>
Now role-play as a team member who wants to use AI in a gray area. Come up with 3 realistic scenarios where the guidelines are ambiguous or where a reasonable person might interpret them differently. For each scenario, suggest how to clarify the guideline.
</blockquote>

Revise the guidelines based on the edge cases.

----

== 📋 Plan first (Planners start here) ==

Here's what you're about to do:
# '''Choose your context''' — Pick a real team or project. The framework should be one you could actually share or implement.
# '''Map AI touchpoints and risk levels''' — Identify every place AI could be used in the workflow and classify each by potential harm from errors.
# '''Design tiered verification''' — Create different verification processes for different risk levels. Not everything needs the same scrutiny.
# '''Write the guidelines''' — Produce a practical 1-page document that a team member could reference in their daily work.
# '''Red-team with edge cases''' — Test the framework against ambiguous scenarios. Fix any gaps before sharing.

'''"Done" looks like:''' A complete, practical AI governance framework (risk map + tiered verification + 1-page guidelines) that you could present to your team, plus documentation of edge cases you tested against.

----

== 🧭 Why this matters (Strategists start here) ==

Individual verification habits (from [[Exercises/Ethical Prompting/Ep Intermediate 01|EP-Intermediate-01]]) don't scale to teams. When five people use AI differently with different standards, the team's AI output quality is only as good as the weakest link. A governance framework creates '''shared standards without bureaucracy''' — it tells people what's safe to do quickly and what requires care, without making every AI interaction feel like a compliance exercise. This is also the document organizations will pay for: a practical, calibrated AI usage policy that actually gets followed.

----

== Reflection ==
* Which risk classification was hardest to assign? What does that ambiguity tell you?
* Would your team actually follow these guidelines? What would make them ignore it?
* Did the red-teaming step reveal fundamental gaps, or just edge cases?
* 💬 ''Present your framework to a colleague and ask: "Would you follow this?" Their honest reaction is more useful than any AI review.'' (Social Learners)

== ⬆️ Level up ==

You've reached the advanced level for Ethical Prompting & Judgment. From here, consider:
* Presenting this framework to your actual team and iterating based on feedback
* Combining this with [[Exercises/Agent Collaboration/Ac Advanced 01|AC-Advanced-01]] to add governance to multi-agent workflows
* Building a case study of how the framework changed AI usage behavior in your team

Back to [[Pillars/Ethical Prompting|Ethical Prompting & Judgment]]

[[Category:AI Fluency Playbook]]
[[Category:Exercises]]
[[Category:Ethical Prompting Exercises]]

The AI Governance Playbook - Revision history

Admin: Fix 2 internal link(s)

Admin: Imported from AI Fluency Playbook