Ethics and Responsible Practices in Generative AI is a self-paced course that helps you build a clear understanding of how to use generative AI in a thoughtful and responsible way. You do not need any technical background, just a curiosity about the role AI plays in our world and how to use it ethically.
In less than 10 hours, you will do more than explore what generative AI is. You will learn how to think critically about its impact across different fields, including media, education, healthcare, and business. You will discover how to recognize ethical risks, such as bias or misuse of data, and how to apply practical strategies to address them. This course is designed to support both professionals and learners who want to use AI in ways that are both effective and responsible.
You will also take a step back to consider the bigger questions. What does it mean to be human in a world where machines can create and decide? How is AI shaping our values, decisions, and society? Through reflection and real-world examples, you will explore how ethics and technology intersect in powerful ways.
By the end of this course, you will be able to:
• Explain the key ethical principles that guide the use of generative AI
• Identify ways to manage data privacy, fairness, and other challenges in AI projects
• Apply responsible AI practices using real case studies and examples
• Reflect on how generative AI influences human values and social norms
• Think ahead to the future of ethical challenges in AI
This course will help you gain the confidence to engage with AI technologies in a way that is informed, respectful, and centered on human responsibility.
This module introduces ethical frameworks to guide the utilization of GenAI, ensuring fair and transparent AI practices. Through lessons and case studies, students will learn to assess ethical considerations, implement best practices, and navigate the balance between innovation and ethical standards
涵盖的内容
17个视频3篇阅读材料1个作业3个讨论话题
显示有关单元内容的信息
17个视频•总计87分钟
Course Introduction•6分钟
Meet your instructor: Jill Kowalchuk•1分钟
Why should we care about GenAI ethics?•3分钟
Introduction to Key Terminology•3分钟
Key Issues in Ethical AI Development•4分钟
Understanding Strategies Creating and Maintaining GenAI Systems•2分钟
Bias Mitigation Strategy: Fairness•9分钟
Bias Mitigation Strategy: XAI•10分钟
Bias Mitigation Strategy: Causality•10分钟
Balancing innovation with ethical constraints•6分钟
GenAI Project Example•6分钟
Introduction•2分钟
Case Study 1: Marketing- Willy Wonka Experience•5分钟
Case Study 2: Air Canada chatbot lies•6分钟
Case Study 3: Lawyer using AI for legal citations•4分钟
Case Studies: Key Lessons•4分钟
Module 1 Recap•6分钟
3篇阅读材料•总计30分钟
Welcome reading and Course Syllabus•10分钟
Steps in Developing a Bias Mitigation Plan•10分钟
Responsible AI development and best practices for organizations•10分钟
1个作业•总计45分钟
Module 1 Quiz•45分钟
3个讨论话题•总计30分钟
Learning Goal•10分钟
Meet & Greet•10分钟
Google and IBM’s Principles for Responsible AI•10分钟
Data Privacy and Security in GenAI
第 2 单元•小时 后完成
单元详情
In this module, we will dive deep into the world of data privacy and security, specifically exploring what privacy means in the age of GenAI and questioning how governments, organizations and individuals should address privacy concerns and issues. In this module you will be instructed on the key components of a bias mitigation plan when utilizing GenAI, specifically focusing on the importance of transparency and accountability in GenAI systems.
涵盖的内容
8个视频3篇阅读材料1个作业2个讨论话题
显示有关单元内容的信息
8个视频•总计30分钟
Introduction•2分钟
What is data privacy?•5分钟
What does GenAI mean for data privacy?•3分钟
Introduction•2分钟
Understanding the Risks in Data Handling in GenAI•4分钟
User Responsibilities in Data Handling with GenAI•3分钟
Overview of AI Data Collection Methods•5分钟
Module 2 Recap•5分钟
3篇阅读材料•总计30分钟
Plagiarism in the age of GenAI•10分钟
Privacy Breaches and Data Misuse in the Real World•10分钟
Strategies for Safeguarding your Data •10分钟
1个作业•总计45分钟
Module 2 Quiz•45分钟
2个讨论话题•总计20分钟
Plagiarism•10分钟
GenAI Bias Mitigation•10分钟
Global AI Regulations and Governance
第 3 单元•小时 后完成
单元详情
In this module we will cover key international AI regulations, highlighting differences and similarities across regions. It emphasizes the importance of governance in ethical AI deployment and regulatory compliance. Learners will examine the regulatory framework for generative AI in Canada and other Western countries and critically analyze various viewpoints on AI regulation, considering ethical, economic, and technological aspects.
涵盖的内容
12个视频3篇阅读材料1个作业
显示有关单元内容的信息
12个视频•总计41分钟
Introduction•4分钟
Overview of Global AI Regulations and Standards•8分钟
The Role of Governance in AI Ethics and Compliance•4分钟
Introduction•2分钟
Historical Development of AI Regulation in Canada•2分钟
Comparing Canada and Europe•2分钟
High Impact and Risk-Based Approaches to Regulation•5分钟
AI Impact Assessments in AI Governance•2分钟
lesson introduction•2分钟
Global Enforcement Mechanisms•2分钟
Accountability Case Studies •4分钟
Module 3 Recap•3分钟
3篇阅读材料•总计30分钟
A Deep Dive into AIDA•10分钟
PIPEDA and its Evolution•10分钟
Building Transparent and Accountable AI Systems: Lessons from GDPR's 'Right to Explanation•10分钟
1个作业•总计45分钟
Module 3 Quiz•45分钟
Societal Impacts of GenAI
第 4 单元•小时 后完成
单元详情
In this module we will analyze the impact of generative AI on jobs, media, education, and global ethics. Learners will explore ethical concerns and governance approaches across cultures and develop skills to critically evaluate AI-generated content and its societal implications. The module also explores foundational philosophical concepts of technology relevant to GenAI. Through lessons and case studies, students will examine the influence of generative AI across various sectors, ethical considerations beyond data privacy, and the philosophical underpinnings shaping AI ethics.
涵盖的内容
13个视频7篇阅读材料1个作业1次同伴评审2个讨论话题
显示有关单元内容的信息
13个视频•总计51分钟
Introduction - Societal Impacts of GenAI•2分钟
Generative AI and Jobs•7分钟
Generative AI and the Media•7分钟
GenAI in Education and Learning•5分钟
lesson introduction•2分钟
Introduction•2分钟
Ethical concerns beyond data privacy•3分钟
Cognitive Extension vs. Cognitive Atrophy•4分钟
Moral Agency & the Rubber Stamp Phenomenon•3分钟
Consent•3分钟
Module recap•5分钟
Peer review assignment overview•4分钟
Course Recap•4分钟
7篇阅读材料•总计70分钟
Public Perception and Trust in GenAI•10分钟
Case Study 1: Indigenous AI•10分钟
Case Study 2: Forgotten Stakeholders•10分钟
Case Study 3: Global South•10分钟
Overview of the Philosophy of Technology Origins•10分钟
AI-Human Value Alignment•10分钟
Welcome to peer review assignments•10分钟
1个作业•总计45分钟
Module 4 Quiz•45分钟
1次同伴评审•总计120分钟
Navigating the Ethical Landscape of Generative AI: Challenges and Solutions•120分钟
The Alberta Machine Intelligence Institute (Amii) is home to some of the world’s top talent in machine intelligence. We’re an Alberta-based
research institute that pushes the bounds of academic knowledge and guides business understanding of artificial intelligence and machine learning.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.