The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis

Les gouvernements se préoccupent actuellement de l’efficacité des orientations pratiques en matière d’éthique de l’IA. Cependant, en raison de leur complexité, de leur dépendance au contexte ou de leur abstraction, les orientations pratiques actuelles comportent des lacunes. En compagnie de Lionel Tidjon, de, regard sur ces enjeux et leur solutions potentielles. 

  • 22 mars 2024

12h00 à 13h00


En ligne.



À propos de la conférence

Artificial Intelligence (AI) is transforming our daily life with many applications in healthcare, space exploration, banking, and finance. This rapid progress in AI has brought increasing attention to the potential impacts of AI technologies on society, with ethically questionable consequences.
In recent years, several ethical principles have been released by governments, national organizations, and international organizations. These principles outline high-level precepts to guide the ethical development, deployment, and governance of AI. However, the abstract nature, diversity, and context-dependence of these principles make them difficult to implement and operationalize, resulting in gaps between principles and their execution. Most recent work analyzed and summarized existing AI principles and guidelines but did not provide findings on principle-to-practice gaps nor how to mitigate them. These findings are particularly important to ensure that AI practical guidances are aligned with ethical principles and values.
In this talk, we provide a contextual and global evaluation of current ethical AI principles for all continents, with the aim to identify potential principle characteristics tailored to specific countries or applicable across countries. Next, we analyze the current level of AI readiness and current practical guidances of ethical AI principles in different countries, to identify gaps in the practical guidance of AI principles and their causes. Finally, we propose recommendations to mitigate the principle-to-practice gaps.

À propos du conférencier

Lionel Tidjon, founder & CTO,

Lionel Tidjon is currently founder at, software development lead at Innovobot Inc, and lecturer at Polytechnique Montreal. He have more than 10 years of industry experience in AI, Security, and Software Engineering in several companies such as Nokia Canada, Airudi Inc, Noveto Systems Ltd, and AddHaptics Inc. Previously, he was Postdoctoral researcher at Polytechnique Montreal, working on AI Security & Trust with Prof. Foutse Khomh. Lionel Tidjon obtained a Ph.D. in Computer Science from the Universite de Sherbrooke jointly with Telecom SudParis under Prof. Marc Frappier and Prof. Amel Mammar. During his thesis, he worked on a cybersecurity language for graphical modeling of complex cyber attacks and the compiler to generate intrusion detection systems from the language to efficiently detect malicious patterns in big event streams.

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