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There are 4 modules in this course
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
Understanding Strategies Creating and Maintaining GenAI Systems•2 minutes
Bias Mitigation Strategy: Fairness•9 minutes
Bias Mitigation Strategy: XAI•10 minutes
Bias Mitigation Strategy: Causality•10 minutes
Balancing innovation with ethical constraints•6 minutes
GenAI Project Example•6 minutes
Introduction•2 minutes
Case Study 1: Marketing- Willy Wonka Experience•5 minutes
Case Study 2: Air Canada chatbot lies•6 minutes
Case Study 3: Lawyer using AI for legal citations•4 minutes
Case Studies: Key Lessons•4 minutes
Module 1 Recap•6 minutes
3 readings•Total 30 minutes
Welcome reading and Course Syllabus•10 minutes
Steps in Developing a Bias Mitigation Plan•10 minutes
Responsible AI development and best practices for organizations•10 minutes
1 assignment•Total 45 minutes
Module 1 Quiz•45 minutes
3 discussion prompts•Total 30 minutes
Learning Goal•10 minutes
Meet & Greet•10 minutes
Google and IBM’s Principles for Responsible AI•10 minutes
Data Privacy and Security in GenAI
Module 2•2 hours to complete
Module details
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.
Understanding the Risks in Data Handling in GenAI•4 minutes
User Responsibilities in Data Handling with GenAI•3 minutes
Overview of AI Data Collection Methods•5 minutes
Module 2 Recap•5 minutes
3 readings•Total 30 minutes
Plagiarism in the age of GenAI•10 minutes
Privacy Breaches and Data Misuse in the Real World•10 minutes
Strategies for Safeguarding your Data •10 minutes
1 assignment•Total 45 minutes
Module 2 Quiz•45 minutes
2 discussion prompts•Total 20 minutes
Plagiarism•10 minutes
GenAI Bias Mitigation•10 minutes
Global AI Regulations and Governance
Module 3•2 hours to complete
Module details
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.
What's included
12 videos3 readings1 assignment
Show info about module content
12 videos•Total 41 minutes
Introduction•4 minutes
Overview of Global AI Regulations and Standards•8 minutes
The Role of Governance in AI Ethics and Compliance•4 minutes
Introduction•2 minutes
Historical Development of AI Regulation in Canada•2 minutes
Comparing Canada and Europe•2 minutes
High Impact and Risk-Based Approaches to Regulation•5 minutes
AI Impact Assessments in AI Governance•2 minutes
lesson introduction•2 minutes
Global Enforcement Mechanisms•2 minutes
Accountability Case Studies •4 minutes
Module 3 Recap•3 minutes
3 readings•Total 30 minutes
A Deep Dive into AIDA•10 minutes
PIPEDA and its Evolution•10 minutes
Building Transparent and Accountable AI Systems: Lessons from GDPR's 'Right to Explanation•10 minutes
1 assignment•Total 45 minutes
Module 3 Quiz•45 minutes
Societal Impacts of GenAI
Module 4•5 hours to complete
Module details
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.
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.
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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.