AI Governance and Ethics

Name: AI Governance and Ethics
Rating: 4.7 (14 reviews)

Practical AI governance and ethics for everyone: data privacy, prompting, agents, and responsible use at work

Created byGrant Gamble

Last updated 8/2026

English

English [Auto],

What you'll learn

Understand what responsible AI use means in 2026 and why old rules don't cover tools like ChatGPT, Claude, and Copilot
Recognize the everyday risks of using AI at work, from data privacy to bias to fabricated information
Recognize the everyday risks of using AI at work, from data privacy to bias to fabricated information
Apply core AI ethics principles — transparency, accountability, fairness, and human oversight — to your own AI use
Know what data is safe to share with AI tools, and what should never be pasted into a prompt
Spot AI-specific security risks like prompt injection, data leakage, and unsafe agent behaviour
Write safer, more effective prompts and critically review AI-generated content before using it
Understand key AI regulations, including the EU AI Act, and what they mean for everyday users
Build the habits and judgment needed to use AI responsibly, whatever your role or industry

Course content

8 sections • 43 lectures • 3h 43m total length

GVE1-0.1 Welcome to AI Governance and Ethics1:23
GVE1-0.2 Downloading the Courseware PDF1:00
Before you start the course, download the AI Governance and Ethics Visual Reference using the link in the Resources section below this lecture. The guide is provided as a single PDF, organised to match the course exactly — each section and topic has its own set of pages, so you can look up a concept the moment it comes up on screen, or return to it any time after you've finished watching.
GVE1-0.3 Downloading the Files for the Practical Exercises0:55
Each section ends with a practical exercise. Here, you an download the work files necessary to complete each exercise.
GVE1-1.1 What AI Governance Means Now4:57
Defines AI governance as an operational discipline in 2026, the shift from models to systems, why legacy frameworks fall short, and five objectives that matter in practice.
GVE1-1.2 The Current AI Product Landscape6:09
Tours ChatGPT, Claude and Microsoft 365 Copilot as they are actually used in business, and what changes when each of them switches from assistant into agent mode.
GVE1-1.3 Core Principles for Responsible AI Use5:07
Covers transparency and disclosure, accountability and ownership, fairness and non-discrimination, and what genuine human agency and contestability require.
GVE1-1.4 Governance Across the AI Lifecycle16:42
Walks the full lifecycle: use-case intake and approval, design and prototyping controls, deployment monitoring, escalation and rollback, and planned retirement.
GVE1-1.5 Risk-Based Thinking for AI5:39
Practical Exercise 11:05
Deciding the Risk Level of a New AI Tool

GVE1-3.1 Data Governance for Generative AI6:31
GVE1-3.2 Security Threats Unique to Modern AI4:58
Prompt injection and instruction hijacking, data leakage and sensitive output risk, tool misuse and agent overreach, and identity, access and permission design.
GVE1-3.3 Privacy and Personal Data in AI Operations5:45
GVE1-3.4 Provenance, Integrity, and Content Authenticity6:40
Practical Exercise 31:02
Scoping an Over-Permissioned Knowledge Agent

GVE-4.1 Prompting as a Governance Issue6:53
GVE1-4.2 Working with AI Agents6:43
GVE1-4.3 Agent Mode in Workplace Productivity Tools5:56
GVE-4.4 Working with APIs and Tool Calls4:48
GVE-4.5 Review, Verification, and Approval Design5:27
Setting review checkpoints by risk level, output validation techniques, exception handling and escalation, and measuring whether review is genuinely effective.
Practical Exercise 41:05
Confronting a Rubber-Stamped Review Step

GVE1-5.1 Content Risk in Generative AI5:50
Harmful, misleading and manipulative outputs, brand and reputational risk, copyright and ownership questions, and practical content moderation strategies.
GVE1-5.2 Bias, Fairness, and Inclusion in AI Use6:08
Where bias originates in modern AI, fairness in generative and decision-support systems, bias testing and red teaming, and inclusive design with real recourse.
GVE1-5.3 Explainability and Decision Support4:15
Practical Exercise 51:09
When Every Output Looks Fine: Arguing for Population-Level Fairness Testing

GVE1-6.1 Corporate AI Governance Structures6:17
AI steering groups and risk committees, the roles of legal, compliance, security, HR and IT, business-owner responsibilities, and federated versus centralised models.
GVE1-6.2 AI Use-Case Intake and Approval4:58
Use-case registration and triage, risk scoring and approval routing, sandboxes for controlled experimentation, and moving safely from pilot to production.
GVE1-6.3 Controls for Everyday Workplace AI6:44
Controls for drafting and summarisation, spreadsheet and data analysis, document and presentation creation, and search, research and knowledge retrieval.
GVE1-6.4 Incident Management for AI Failures10:22
Practical Exercise 61:08
Logging a Near Miss Nobody Wants on the Register

GVE1-7.1 Healthcare and Life Sciences5:43
Clinical support versus clinical decision making, patient data and privacy constraints, documentation and triage use cases, and human review in high-stakes settings.
GVE1-7.2 Financial Services and Insurance6:07
GVE1-7.3 Public Sector and Education5:31
AI in public services, surveillance, profiling and citizen rights, AI in teaching and assessment, and accessibility and inclusion in public-facing AI.
GVE1-7.4 Corporate Knowledge Work and Professional Services6:00
Practical Exercise 71:09
A Documentation Assistant That Started Suggesting Diagnoses

GVE1-8.1 Building an AI Governance Roadmap5:16
Current-state assessment, prioritising the highest-impact controls, using governance maturity models, and choosing metrics that show real progress.
GVE1-8.2 Training and Culture for Responsible AI7:00
Role-based AI literacy, prompting and review as core workplace skills, decision hygiene in AI-assisted work, and building a culture of challenge and escalation.
GVE1-8.3 Future-Proofing Governance for Fast-Moving AI10:39
Multi-agent orchestration risk, governing teams of AI systems, delegated authority and autonomous workflows, frontier models, and continuous policy refresh.
Practical Exercise 81:07
Scaling an Autonomous Agent on the Strength of a Clean Pilot

Requirements

No prior AI, legal, or compliance experience required — this course explains every concept from the ground up.
Just bring your everyday experience using tools like ChatGPT, Claude, or Microsoft Copilot at work — even casual, occasional use is enough.
A willingness to think critically about how AI is used in your role, whatever your job title or department.
No technical or coding background needed — this course focuses on judgment, policy, and everyday practice, not engineering.

Description

This course contains the use of artificial intelligence. AI tools are used in the production of this course, including AI-assisted speech delivery based on the instructor's own voice. All content, demonstrations, workbooks, and prompts have been personally designed, reviewed, and verified by the instructor to ensure accuracy and practical value.

AI is already part of your workday — whether you're drafting in ChatGPT, analyzing in Microsoft Copilot, or reasoning through a problem with Claude. But most organizations are still trying to govern these tools with rules written for a different era of technology. This course closes that gap.

AI Governance and Ethics is a practical, no-jargon introduction to using AI responsibly — designed for every employee, not just legal, compliance, or technical teams.

In this course, you'll learn how to:

Understand what AI governance actually means in 2026, and why old frameworks don't cover tools like ChatGPT, Claude, and Copilot
Apply core principles — transparency, accountability, fairness, and human oversight — to the AI tools you already use every day
Recognize everyday risks, including data privacy issues, bias, fabricated information, and prompt injection
Know what data is safe to share with AI, and what should never be pasted into a prompt
Write clearer, safer prompts and critically review AI-generated content before using it
Understand key regulations, including the EU AI Act, explained in plain language

Learn visually, not just in text. This course draws on the AI Governance and Ethics Visual Reference — a companion guide that pairs a clear visual with the essential point behind it on every page, covering:

Governance principles and lifecycle controls
Data privacy, security, and content authenticity
Prompting, agents, and human oversight
Risk, incident management, and enterprise operating structures

No technical background, coding experience, or prior governance knowledge is required. Just bring your everyday experience with AI tools and a willingness to think critically about how you use them.

By the end, you'll have the judgment and practical habits to use AI safely, responsibly, and with confidence — whatever your role.

Who this course is for:

Any employee who uses AI tools like ChatGPT, Claude, or Microsoft Copilot at work — even just occasionally — and wants to use them responsibly and safely.
Managers and team leads who need to guide their teams on acceptable AI use, without needing a legal or technical background.
HR, legal, compliance, IT, and risk professionals looking for a practical, non-technical foundation in AI governance before diving into specialized frameworks.
Business owners and decision-makers who want to understand what responsible AI adoption looks like across an organization.
Anyone curious about the ethical, legal, and practical issues raised by generative AI — no prior governance, compliance, or technical experience needed.

AI Governance and Ethics

What you'll learn

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Course content

Section 1: Modern AI Governance Fundamentals10 lectures • 43min

Section 2: Law, Policy, and Standards for AI Governance6 lectures • 29min

Section 3: Data, Security, and Privacy for AI Systems6 lectures • 25min

Section 4: Prompting, Agents, and Human Oversight7 lectures • 31min

Section 5: Governance of Generative AI Content and Decisions5 lectures • 17min

Section 6: Operating AI Governance in the Enterprise6 lectures • 29min

Section 7: Sector-Specific AI Governance Applications6 lectures • 25min

Section 8: Implementation, Maturity, and Future Readiness5 lectures • 24min

Requirements

Description

Who this course is for: