Defining and Classifying AI Systems | Lesson 1 | AI Governance Course

AI Governance Course | Lesson 1: Learn how to define and classify AI systems for risk and compliance.
Welcome to Lesson 1 of our comprehensive AI Governance course!
Learn the crucial first step to effective AI risk management: how to define and classify any AI system.
We’ll go beyond the buzzwords and provide a practical, actionable framework used in real-world governance and compliance.

📚 What You’ll Learn in This Video:
What is AI — really? A multidimensional, operational definition

The 4 Key Axes of AI System Classification:

Axis 1: Scope of Intelligence — Understand the difference between Narrow AI (ANI) and General AI (AGI)
Axis 2: Learning Method — ML vs. DL: why it matters for transparency and control
Axis 3: Purpose — Analytical vs. Generative AI and the 4 unique risks of GenAI
Axis 4: Architecture — Symbolic (“white box”) vs. Connectionist (“black box”) AI systems

👥 About the Creators
This course is developed by the team at EthicaLogic — a consulting firm specializing in AI governance, privacy compliance, and responsible technology deployment - ethicalogic.com
It is led by Viacheslav Gasiunas, a legal and governance expert with over 15 years of experience in data protection, AI policy, and ethical risk management.

How precise classification affects:
Risk assessment
Compliance planning
Choice of technical safeguards

Whether you're:

Preparing for an AI governance certification
Transitioning into a role in AI compliance
Managing real AI-based systems in your organization

➡️ This foundational lesson is where it all begins.

🧠 Bonus: End-of-Lesson Knowledge Check Quiz
Test what you’ve learned and get instant feedback!


🕒 Chapters & Timestamps

00:00 — Introduction: Why Classification Matters
01:34 — What Is an AI System? OECD’s Practical Definition
03:03 — Comparing Global AI Frameworks (EU, NIST, ISO)
04:50 — Overview: The Four Axes of Classification
05:24 — Axis 1: Scope of Intelligence (ANI vs. AGI)
08:19 — Axis 2: Learning Method (ML vs. DL)
09:57 — Deep Learning and the Governance Challenge
12:59 — Axis 3: Purpose (Analytical vs. Generative AI)
14:15 — Four Unique Risks of Generative AI
15:27 — Axis 4: Architecture (Symbolic vs. Connectionist)
18:58 — Mini Quiz: Knowledge Check
19:40 — Course Progress: What’s Next?

👉 Subscribe for future modules:
AI Risk Matrix, Compliance Roadmaps, Auditing Tools and more.

Let’s build ethical, trustworthy, and accountable AI—together.

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