Module 3 – Ethical AI Identity

Overview

Ethical AI Identity

As AI gets better at sounding like a person — any person — leaders face a quieter risk than misinformation or bias: the slow erosion of their own voice. When a draft, a strategy, or a public statement can be produced in seconds, it becomes easy to publish work that's technically yours but authentically no one's.

Ethical AI Identity introduces a simple, repeatable framework — Voice → Disclosure → Verification → Ownership — for using AI without quietly outsourcing your judgment, your reputation, or your identity to it. Rather than a general ethics lecture, the module focuses on four concrete questions leaders can apply to any AI-assisted output: Does this sound like me? Does anyone need to know AI was involved? Have I actually checked this? And am I willing to stand behind it?

What You Will Learn

Across the module you'll learn:

• Why AI-assisted work creates identity risk, not just accuracy risk
• The four checkpoints in the Authenticity Framework and where leaders skip them
• Common mistakes that quietly erode trust and voice over time
• The leader's role in disclosure and accountability
• Practical before/after examples
• Three habits to build into any AI-assisted work you publish or send

From Insight to Practice

The masterclass video (approx. 15–20 minutes) is the primary learning format. The companion guide is not an article to read — it's a working document to use: a quick-reference framework, a checklist, and an Identity Audit exercise where you take a recent piece of AI-assisted work and run it back through Voice, Disclosure, Verification, and Ownership to see what, if anything, you'd change.

This module isn't about banning AI from your voice. It's about staying deliberate — using AI to support your identity, not replace it.