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Ethics and Responsible Practices in GenAI

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Ethics and Responsible Practices in GenAI

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Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

Build your subject-matter expertise

This course is part of the Generative AI Essentials Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

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: β€’ Explain the key ethical principles that guide the use of generative AI β€’ Identify ways to manage data privacy, fairness, and other challenges in AI projects β€’ Apply responsible AI practices using real case studies and examples β€’ Reflect on how generative AI influences human values and social norms β€’ 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

What's included

17 videos3 readings1 assignment3 discussion prompts

17 videosβ€’Total 87 minutes
  • Course Introductionβ€’6 minutes
  • Meet your instructor: Jill Kowalchukβ€’1 minute
  • Why should we care about GenAI ethics?β€’3 minutes
  • Introduction to Key Terminologyβ€’3 minutes
  • Key Issues in Ethical AI Developmentβ€’4 minutes
  • Understanding Strategies Creating and Maintaining GenAI Systemsβ€’2 minutes
  • Bias Mitigation Strategy: Fairnessβ€’9 minutes
  • Bias Mitigation Strategy: XAIβ€’10 minutes
  • Bias Mitigation Strategy: Causalityβ€’10 minutes
  • Balancing innovation with ethical constraintsβ€’6 minutes
  • GenAI Project Exampleβ€’6 minutes
  • Introductionβ€’2 minutes
  • Case Study 1: Marketing- Willy Wonka Experienceβ€’5 minutes
  • Case Study 2: Air Canada chatbot liesβ€’6 minutes
  • Case Study 3: Lawyer using AI for legal citationsβ€’4 minutes
  • Case Studies: Key Lessonsβ€’4 minutes
  • Module 1 Recapβ€’6 minutes
3 readingsβ€’Total 30 minutes
  • Welcome reading and Course Syllabusβ€’10 minutes
  • Steps in Developing a Bias Mitigation Planβ€’10 minutes
  • Responsible AI development and best practices for organizationsβ€’10 minutes
1 assignmentβ€’Total 45 minutes
  • Module 1 Quizβ€’45 minutes
3 discussion promptsβ€’Total 30 minutes
  • Learning Goalβ€’10 minutes
  • Meet & Greetβ€’10 minutes
  • Google and IBM’s Principles for Responsible AIβ€’10 minutes

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.

What's included

8 videos3 readings1 assignment2 discussion prompts

8 videosβ€’Total 30 minutes
  • Introductionβ€’2 minutes
  • What is data privacy?β€’5 minutes
  • What does GenAI mean for data privacy?β€’3 minutes
  • Introductionβ€’2 minutes
  • Understanding the Risks in Data Handling in GenAIβ€’4 minutes
  • User Responsibilities in Data Handling with GenAIβ€’3 minutes
  • Overview of AI Data Collection Methodsβ€’5 minutes
  • Module 2 Recapβ€’5 minutes
3 readingsβ€’Total 30 minutes
  • Plagiarism in the age of GenAIβ€’10 minutes
  • Privacy Breaches and Data Misuse in the Real Worldβ€’10 minutes
  • Strategies for Safeguarding your Data β€’10 minutes
1 assignmentβ€’Total 45 minutes
  • Module 2 Quizβ€’45 minutes
2 discussion promptsβ€’Total 20 minutes
  • Plagiarismβ€’10 minutes
  • GenAI Bias Mitigationβ€’10 minutes

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

12 videosβ€’Total 41 minutes
  • Introductionβ€’4 minutes
  • Overview of Global AI Regulations and Standardsβ€’8 minutes
  • The Role of Governance in AI Ethics and Complianceβ€’4 minutes
  • Introductionβ€’2 minutes
  • Historical Development of AI Regulation in Canadaβ€’2 minutes
  • Comparing Canada and Europeβ€’2 minutes
  • High Impact and Risk-Based Approaches to Regulationβ€’5 minutes
  • AI Impact Assessments in AI Governanceβ€’2 minutes
  • lesson introductionβ€’2 minutes
  • Global Enforcement Mechanismsβ€’2 minutes
  • Accountability Case Studies β€’4 minutes
  • Module 3 Recapβ€’3 minutes
3 readingsβ€’Total 30 minutes
  • A Deep Dive into AIDAβ€’10 minutes
  • PIPEDA and its Evolutionβ€’10 minutes
  • Building Transparent and Accountable AI Systems: Lessons from GDPR's 'Right to Explanationβ€’10 minutes
1 assignmentβ€’Total 45 minutes
  • Module 3 Quizβ€’45 minutes

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.

What's included

13 videos7 readings1 assignment1 peer review2 discussion prompts

13 videosβ€’Total 51 minutes
  • Introduction - Societal Impacts of GenAIβ€’2 minutes
  • Generative AI and Jobsβ€’7 minutes
  • Generative AI and the Mediaβ€’7 minutes
  • GenAI in Education and Learningβ€’5 minutes
  • lesson introductionβ€’2 minutes
  • Introductionβ€’2 minutes
  • Ethical concerns beyond data privacyβ€’3 minutes
  • Cognitive Extension vs. Cognitive Atrophyβ€’4 minutes
  • Moral Agency & the Rubber Stamp Phenomenonβ€’3 minutes
  • Consentβ€’3 minutes
  • Module recapβ€’5 minutes
  • Peer review assignment overviewβ€’4 minutes
  • Course Recapβ€’4 minutes
7 readingsβ€’Total 70 minutes
  • Public Perception and Trust in GenAIβ€’10 minutes
  • Case Study 1: Indigenous AIβ€’10 minutes
  • Case Study 2: Forgotten Stakeholdersβ€’10 minutes
  • Case Study 3: Global Southβ€’10 minutes
  • Overview of the Philosophy of Technology Originsβ€’10 minutes
  • AI-Human Value Alignmentβ€’10 minutes
  • Welcome to peer review assignmentsβ€’10 minutes
1 assignmentβ€’Total 45 minutes
  • Module 4 Quizβ€’45 minutes
1 peer reviewβ€’Total 120 minutes
  • Navigating the Ethical Landscape of Generative AI: Challenges and Solutionsβ€’120 minutes
2 discussion promptsβ€’Total 20 minutes
  • Case Studiesβ€’10 minutes
  • Self-Reflectionβ€’10 minutes

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Alberta Machine Intelligence Institute
2 Coursesβ€’726 learners

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