Ai Ethics And Governance For Everyone 2025

A Practical Guide to AI Governance: Build Trust, Manage Risk, and Navigate Global Regulations.

What you'll learn

Implement practical AI Governance using the NIST AI Risk Management Framework to build trustworthy and compliant AI systems from the ground up.

Master techniques to detect and mitigate algorithmic bias. Learn to use industry tools like Fairlearn and AIF360 to ensure fairness in your AI models.

Navigate the complex global AI regulatory landscape. Understand and apply key requirements from the EU AI Act, US policies, and China's regulations.

Develop a complete Responsible AI strategy. Learn to create Model Cards, conduct ethical risk assessments, and lead with confidence in the age of AI.

Requirements

An Interest in AI and its Impact

No Technical Background Required

A Willingness to Think Critically

Description

AI Ethics and Governance for EveryoneGo from Theory to Practice. Learn to Build, Govern, and Lead Responsible AI with Real-World Frameworks and Tools.In an era powered by AI, ethical literacy is a critical skill. This course provides a clear, practical path to understanding and implementing AI ethics. You'll move beyond abstract concepts and learn to use globally recognized governance frameworks, test for bias, and navigate the complex regulatory landscape. By the end, you'll have the confidence and tools to build, manage, and lead trustworthy AI initiatives.What you'll learnImplement Practical AI Governance using the official NIST AI Risk Management Framework.Detect and Mitigate Algorithmic Bias with an understanding of industry tools like Fairlearn and AI Fairness 360.Navigate the Global Regulatory Landscape, including the EU AI Act and the divergent approaches of the US and China.Master the Core Principles of Fairness, Accountability, and Transparency (FAT) in real-world projects.Analyze Frontier Ethical Challenges in Generative AI, Autonomous Systems, and the emerging field of Neurorights.Create "Model Cards" and other structured documentation for responsible AI development.Who this course is for:AI/ML Developers & Data Scientists who want to build fairness and safety into their models.Product Managers & Business Leaders responsible for AI strategy and ethical oversight.Compliance, Legal, & Policy Professionals navigating AI regulations and risk.Any professional or student seeking to understand and shape the future of responsible technology.RequirementsAn interest in Artificial Intelligence and its impact on society.No programming or advanced technical background is required.This course includes:1 hour of on-demand video4 Downloadable Resources, including checklists and templates4 Course specific AI Role playsInteractive Role-Playing ScenariosArticles and links to key frameworksFull lifetime accessCertificate of completion

Overview

Section 1: Module 1: The Foundations of AI Ethics

Lecture 1 Building Responsible AI Systems

Lecture 2 Introduction: Why AI Ethics and Governance Matter Now

Lecture 3 The Core Principles: Fairness, Accountability, and Transparency (FAT)

Lecture 4 Beyond FAT: The Pillars of Trustworthy AI

Lecture 5 A Human-Centric Approach: Identifying Stakeholders and Societal Impact

Lecture 6 The Trolley Problem & Its Limits: From Philosophy to Practicality

Section 2: Module 2: Core Challenges in Practice

Lecture 7 Unpacking Algorithmic Bias: Types, Sources, and Dangers

Lecture 8 Case Study Deep Dive: Real-World Bias Failures

Lecture 9 The "Black Box" Problem: Explainability (XAI) and Interpretability

Lecture 10 Data Privacy in the AI Era: A Global Challenge

Lecture 11 Generative AI's Unique Ethical Minefield

Section 3: Module 3: AI Governance in Action

Lecture 12 Building an AI Governance Framework: From Principles to Policy

Lecture 13 The Responsible AI Lifecycle: Embedding Ethics from Day One

Lecture 14 Key Frameworks: An Introduction to NIST AI RMF and IEEE P7000

Lecture 15 A Tour of Industry Toolkits: Google, Microsoft, and IBM

Lecture 16 Your Open-Source Toolbox for Fairness and Explainability

Section 4: Module 4: The Future of AI Ethics and Governance

Lecture 17 The Global Regulatory Chessboard: EU vs. US vs. China

Lecture 18 Emerging Regulations: A Look at India, Brazil, and the Global South

Lecture 19 The Final Frontier? Lethal Autonomous Weapons (LAWS)

Lecture 20 The Next Human Right? The Debate Over Neurorights

Lecture 21 Conclusion: Your Role as an Ethical Leader and Future Trends

AI/ML Developers, Data Scientists, and Engineers: Professionals who are building AI systems and want to learn how to implement ethics-by-design, mitigate bias, and use technical toolkits for explainability.,Product Managers and Business Leaders: Individuals responsible for AI strategy, product roadmaps, and risk assessment who need to make informed decisions that align business goals with ethical standards.,Compliance, Legal, and Policy Professionals: Specialists who navigate the complex web of global regulations, internal governance policies, and liability issues emerging in the AI space.