CASE STUDY: INBO TRAINING
A Blueprint for Responsible AI
“Inbo supported both the design process and the final product including delivery of the program. They also created an inclusive space for the entire team to contribute. They are creative and so much fun to work with!”
The Client
Mila - Quebec Artificial Intelligence Institute, is recognized worldwide for its major contributions to AI. Today, the Mila community boasts the largest concentration of deep learning academic researchers globally. The institute is recognized for its expertise and significant contributions in areas such as modeling language, machine translation, object recognition and generative models.
The Challenge
Designing for diverse learners across AI research and application
Designing the TRAIL Certificate Program required addressing the needs of a highly diverse audience—spanning academia and industry, research and application. Inbo’s core challenge was to create a unified learning experience that delivered value across this spectrum, while maintaining depth, accessibility, and real-world relevance.
Key Challenges:
Audience Diversity:
Engage participants from vastly different backgrounds—including PhD students, university faculty, and AI professionals from government, tech, and policy sectors.Bridging Academia and Industry:
Balance theoretical depth with practical application to ensure the content was relevant for both academic exploration and real-world implementation.Content Accessibility & Depth:
Develop modules that challenged advanced learners without overwhelming those with less technical expertise or formal training in AI ethics.Cross-Disciplinary Engagement:
Foster dialogue and participation across disciplines such as machine learning, public policy, law, and human rights.Cohesive Learning Journey:
Create a program structure that allowed all participants—regardless of sector or seniority—to develop a shared vocabulary and understanding of responsible AI principles.
The Inbo Approach
We designed a hands-on, cross-sector AI ethics program.
The program blended interdisciplinary content—from ethics and governance to legal frameworks and human rights—with active learning formats such as case studies and collaborative exercises. By bridging academic insight with practical tools, we equipped participants to critically evaluate the societal impacts of AI and lead with integrity in complex, fast-evolving environments.
To ensure long-term impact and relevance, we designed the TRAIL program with a strategic, interdisciplinary approach:
Grounded the curriculum in real-world challenges related to responsible AI, including governance, bias, legal frameworks, and human rights.
Integrated cross-sector perspectives to ensure the content resonated with participants across academia, industry, and policy backgrounds.
Facilitated active learning experiences through case studies, group discussions, and scenario-based exercises to deepen engagement and understanding.
Developed modules to build critical interdisciplinary skills, enabling participants to connect ethical, technical, and societal dimensions of AI.
Equipped participants with practical tools and frameworks for evaluating AI systems and navigating ethical dilemmas in complex environments.
Created a psychologically safe learning environment that encouraged reflection, dialogue, and diverse viewpoints.
The Results
The program fostered lasting alignment, critical thinking,
and real-world application of AI ethics
A Cohort of Ethical AI Leaders:
Participants left the program with a shared language and deeper understanding of AI’s societal impacts, including governance, fairness, and human rights.
Practical Tools for Complex Contexts:
The curriculum equipped learners with real-world frameworks to assess ethical risks, navigate ambiguity, and apply responsible AI principles in academic, policy, and industry settings.
Cross-Sector Alignment:
The program successfully bridged academia and industry, enabling participants from varied backgrounds to collaborate and learn from diverse perspectives.
Lasting Impact and Application:
Participants reported increased confidence in engaging with AI ethics in their work, with many integrating key insights into research, teaching, and product development.
Why It Worked
Inbo partnered closely with MILA to design an experience that was both intellectually rigorous and deeply grounded in real-world relevance. Our facilitation created space for critical reflection, dialogue, and cross-disciplinary learning—ensuring participants could internalize and apply responsible AI principles long after the program concluded.