AIDRC Seminar Series - Juliette Mattioli

Title:

CONFIANCE.AI: TRUSTWORTHY AI-BASED CRITICAL SYSTEMS

Abstract:

Today, we are in the renewal of AI with unprecedented growth. What has changed is that research in  recent years turns from theoretical insights into practical applications. Some very promising results are revolutionizing our  daily lives. However, in some areas, too few AI Proof of Concept (PoC) are reaching production level deployment. One of the  causes is that deployment in industries as aeronautics, energy, automotive, defense, health, manufacturing, etc. requires conformity to quality, safety, security, reliability objectives that are from being completed by state-of-the-art AI systems. Thus, as any critical system, an AI based critical system needs to have well defined development methods from its design to its  deployment and qualification. This requires a complete tool chain ensuring trust at all stages, as (in a top-down view): (1)  specification, knowledge and data management; (2) algorithm and system architecture design; (3) characterization, verification  and validation of AI functions; (4) deployment, particularly on embedded architecture; (5) qualification, certification from a system point of view. All that needs a sound and tooled trustworthy AI engineering methodology that encompasses with objective of trustworthy AI algorithm engineering, data and knowledge engineering and AI system engineering.
At French national level major industrial players in the fields of Automotive, Aeronautics, Defense, Manufacturing and Energy (Air Liquide, Airbus, Atos, Naval-Group, Renault, Safran, SopraSteria, Thales, Total and Valeo) with the support of academic partners (CEA, INRIA, IRT Saint Exupéry and IRT SystemX) are collaborating together to address such issues through the French National Program “Confiance.ai”. This program aims to bridge the gap between AI PoCs and AI deployment within critical systems toward certification by providing an interoperable engineering workbench to support AI processes and practices through methods and tools during the over-all lifecycle of the AI-based system.

Bio:

In 1993, she received a Ph.D. in Applied Mathematics for AI from PSL Univ. and became a R&D Engineer on computer vision and Combinatorial Problem Solving at Thomson-CSF (former name of Thales). In 2001, she led a research lab. at Thales Research & Technology France, dedicated on problem solving focusing on AI-based combinatorial optimization, AI-planning, anytime constraint programming and multi-criteria decision making. In 2005, She set-up a new research axis on soft information fusion combining semantics and knowledge-based reasoning. From 2005 to 2016, she led few research labs on information fusion, combinatorial problem solving and optimization, multi-criteria decision and big data. She was appointed “Strategy & Innovation Director” at Thales Technical Directorate in 2010 and as “AI Senior Expert” in 2012. In 2017, she was a member of the #FranceIA mission (2016), one of the 5 representatives of France at the G7 innovators (2017), contributor of “Plan IA 2021” for Paris Region (2018) and since 2020, VP of the “Data Science & Artificial Intelligence” Hub with the Pôle Systematic-Paris Région. Today, she is deeply involved in Confiance.ai, the French national program dedicated on Trustworthy AI Engineering. She is also co-author of a book with Michel Schmitt on mathematical morphology, published numerous scientific articles and filed 9 patents. She has also led numerous R&D projects for Thales programs and European projects.