
Discover responsible AI and AI ethics with Mila, the Quebec AI Institute that helps Canada lead in AI, governance, and the core technical work around deployment.
Assess responsible AI ethics through a case study of a retailer using an AI-powered personalized credit offering system, highlighting governance, risk, and compliance with fair lending and EU AI Act.
Prioritize values and navigate ethical tensions to implement responsible AI in real life by defining equity in context, weighing privacy versus public health, and aligning design decisions with stakeholder voices.
Examine how organizations operationalize responsible AI through self-regulation and external oversight, guided by the EU AI Act and ISO standards, and the EU Code of Practice for general purpose AI.
Learn how organizations should implement self-regulation and governance from the start, covering data governance, development practices, and open-source tools to assess bias and privacy in artificial intelligence products.
Leadership drives the operationalization of responsible AI through policy, governance, and execution, with change management, education, and a define, measure, analyze, improve, and control cycle.
Explore how safety engineering and risk management frameworks help identify and mitigate AI harms, including representational bias and socio-technical risks, through traceable design decisions and accountability.
Become a responsible AI champion by asking about bias testing and governance whenever new tools deploy, and apply this in your life, role, and work.
Explore how responsible AI has emerged and evolved, outlining principles, tools, and a practical framework for design, development, and deployment, while embracing a mindset of ongoing learning and critical thinking.
In today's rapidly evolving technological landscape, Artificial Intelligence (AI) is transforming every industry. But with great power comes great responsibility. This concise and impactful course is proudly organized by Mila - Quebec AI Institute, designed to equip you with the essential knowledge and practical steps needed to build, deploy, and manage AI systems ethically and safely.
The aim of this course is to equip participants with a solid foundation to understand and engage with AI in a responsible way. The course is informed by the expertise of Mila’s researchers and experts, offering practical and up-to-date perspectives to support informed decision-making and thoughtful adoption of AI within organizations.
What You Will Learn:
Section 1: Why Responsible AI? Setting the Stage (16 min): Understand the compelling business, ethical, and societal case for prioritizing responsible AI practices in every project.
Section 2: Responsible AI – Core Concepts That Matter (13 min): Master the foundational concepts, including fairness, transparency, privacy, and accountability, that form the bedrock of ethical AI.
Section 3: Principles, Risks, and Real-World Dilemmas (14 min): Explore leading industry principles, identify common AI risks (bias, harm, misuse), and analyze complex, real-world case studies that challenge your perspective.
Section 4: Putting Responsible AI into Action (19 min): Learn tangible, practical steps to integrate responsible AI practices into the full AI/ML lifecycle—from ideation and data collection to model training and deployment.
Section 5: Wrapping Up and Moving Forward (3 min): Review key takeaways and discover resources and strategies for continuously learning and adapting to the future of ethical AI.
Who is this course for?
This course is designed for anyone who wants to learn about the responsible applications of AI and how it can be a tool for positive change. Specifically, this includes:
AI/ML Practitioners: Engineers, Data Scientists, and Developers seeking to embed ethics directly into the build process.
Product and Strategy Leaders: Product Managers, Business Executives, and Technologists defining roadmaps, mitigating risk, and leading AI governance.
Students and Learners: Individuals at any stage of their career who want to master the ethical and societal impact of AI and prepare for the future.
Course Intructors:
Shingai Manjengwa, Senior Director, AI Education and Development, Mila
Rose Landry, AI Governance Manager, Mila
Shalaleh Rismani, Postdoctoral Research Fellow, McGill and Mila
Khaoula Chehbouni, PhD Student at McGill University and Mila
Enroll now to build your skills and knowledge for a responsible and sustainable future with AI, guided by Mila’s experts.