In a World of Digital Transformation, Is AI Turning Us Into Superheroes?
Matthieu Deboeuf Rouchon, Capgemini Engineering, France
AI Engineering: A Necessary Condition to Deploy Trustworthy AI in Industry
Juliette Mattioli, Thales, France
In a World of Digital Transformation, Is AI Turning Us Into Superheroes?
Matthieu Deboeuf Rouchon
Capgemini Engineering
France
Brief Bio
Matthieu Deboeuf-Rouchon is a recognized expert in innovation and digital transformation. In 2008, he founded his own Digital Transformation and Innovation consultancy. In 2017 he joined the Capgemini Engineering teams. He is co-author of the "Consumer Electronics Show Survival Guide: how to organize, experience & optimize your visit to the world's biggest tech show!". He is also a member of the CES Innovation Awards 2024 jury. Passionate about the impact of technology on society, business and human beings, he co-hosts the podcast Innovation & Prospective Talk.
Abstract
In a world where digital transformation is no longer a "revolution" but a continuum serving the operational efficiency of companies. In a world where change is a natural phenomenon for every human being, both professionally and personally. In this world of perpetual acceleration, AI is becoming central and shaping a singular business paradigm, where the place of human beings, their skills and their interaction with technology have yet to be defined. Is AI, and even more so generative AI, giving us the illusion of an illusory superhero potential? Between addiction, new beliefs, ethics and "added human value", let's explore, for the time of this talk, the fascinating landscape of the company undergoing transformation in the age of AI.
AI Engineering: A Necessary Condition to Deploy Trustworthy AI in Industry
Juliette Mattioli
Thales
France
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Brief Bio
Juliette Mattioli is considered a reference in artificial intelligence not only within Thales but also in France. In 2017, she was one of the five representatives of France at the G7 Innovators Conference, contributing to the issue of AI, member of the #FranceIA mission. Since 2019, she is President of the "Data Sciences & Artificial Intelligence" Hub of the Systematic Paris-Region competitiveness cluster.
Recognized for her excellent knowledge of industrial AI issues, she contributes in the field of algorithmic engineering with a particular focus on trusted AI to accelerate the industrial deployment of AI-based solutions in critical systems.
Juliette Mattioli is also co-author of a book with Michel Schmitt on mathematical morphology, has published numerous scientific papers and filed seven patents. She has also led numerous R&D projects for Thales programs and European projects (FP6, FP7, H2020) and is now strongly involved in the "Grand Défi National pour Sécuriser, certifier et fiabiliser les systèmes fondés sur l'AI".
Abstract
Artificial Intelligence (AI) can bring competitive advantage to industry by improving system autonomy, decision support and the ability to offer higher value-added products and services. Delivering the expected service safely (conformance to requirements), meeting stakeholder expectations (trustworthiness, usability...) and maintaining service continuity will determine its adoption and use in industry. Moreover, concerns such as ethics, accountability, liability, security, privacy, and trust are receiving increasing attention in many industries. In addition, we see frenetic activity in standardization and regulatory bodies. For example, quality is the focus of the SQuaRE (Systems and software Quality Requirements and Evaluation) series of standards ISO/IEC 25000:2014, and AI quality is addressed in ISO/IEC DIS 25059. The principles of risk management are explained in ISO 31000:2018 and AI risk is specifically addressed in ISO/IEC FDIS 23894, and the High-Level Expert Group set up by the EU to advise on the European AI Strategy has published the European Commission's AI Act. A successful strategy to overcome these challenges requires collective actions around the objectives of a common industrial and reliable AI strategy to strengthen synergies and develop engineering best practices. The keynote will emphasize the importance of trustworthy AI engineering with a sound end-to-end methodology and tools to support the overall lifecycle of an AI system. This includes analyzing and meeting stakeholder expectations and specifications (such as regulation and standardization bodies, customers, and end-users) and assessing and managing AI-related risks to maintain trustworthiness in the system of interest, such as safety and security. The 'confiance.ai program' approach revisits conventional engineering, including data and knowledge engineering, algorithm engineering, system and software engineering, safety and cyber-security engineering, and cognitive engineering. The goal is to ensure the system's compliance with requirements and constraints, assess and master AI-technologies related risks, and maintain trustworthiness between stakeholders and the system of interest (e.g. RAMS - Reliability, Availability, Maintainability, and Safety - properties).