Introduction to Responsible Artificial Intelligence and AI Ethics

Your RAI journey starts here!


Format

Online
Course

Expert

Leah Davis

Live session date

April 15,  2026

Live session time

12:30 - 3:00PM

Individual preparatory work

1 Hour

Price

$165 + Tax

About the module

As the transformative potential of AI becomes increasingly evident, its rapid adoption raises significant concerns about its impact on our lives, organizations, societies, and the environment. In response, numerous initiatives have emerged to promote a more responsible development of AI systems, and to proactively incorporate ethical principles ensuring safer, better AI systems that are sustainable and respectful of everyone's rights.

In this module, participants will explore the evolving landscape of Responsible AI.

Your TRAIL journey starts here, with a first introduction to Responsible AI and AI ethics, designed to encourage critical thinking about AI projects and to develop essential competencies in AI ethics.

Learning Outcomes

Understand and articulate key concepts of Responsible AI and the fundamental ethical principles guiding its development and use.
Apply critical thinking skills to evaluate AI projects and their potential societal impacts.
Recognize and address value tensions and moral dilemmas in AI projects.
Consider diverse stakeholder perspectives in AI decision-making processes.
Discuss the ethical challenges of an AI project and propose strategies to address them and enhance the responsible development and deployment of AI systems.

Who is this module for?

All AI professionals, including executive leaders, Data Scientists, ML/AI engineers, AI developers, AI product managers, AI consultants and investors.

Tailored for all participants but is recommended for those with a foundational understanding of AI concepts and basic technical knowledge of AI systems.

Course Lessons

Leah Davis

Leah Davis is a PhD student in the Responsible Autonomy Intelligent Systems Ethics (RAISE) Lab in the Department of Electrical and Computer Engineering at McGill University, with affiliations at Mila – Quebec AI Institute, Université du Québec à Montréal, and Université de Montréal. She is a 2025 Pierre Trudeau Scholar and McGill Engineering Vadasz Doctoral Fellowship Scholar. Her research centres upon socially responsible AI evaluations, particularly within algorithmic auditing practices. She approaches this work through a regulatory lens, aiming to highlight the critical role of system integration within the AI policy ecosystem. Her perspective is particularly informed by industry experience in roles within requirements engineering, software quality assurance, and medical device regulation. She holds an MSc in Social Data Science from the University of Oxford and a BEng in Biomedical Engineering Co-op from the University of Guelph.