Developing AI systems we can all trust
Human-centred artificial intelligence
Artificial intelligence is playing an increasingly prominent role in our daily lives.
By helping us to build more secure systems and make better decisions, this versatile technology has a key role to play in addressing the challenges of tomorrow.
For Thales, the priority is to develop AI technologies that keep humans at the centre of the decision-making process.
Photo: Patricia Besson, Head of Thales’s Reasoning and Analysis in Complex Systems Lab.
Developing trusted AI
Patricia Besson is Head of Thales’s Reasoning and Analysis in Complex Systems Lab.
"How can AI help us make better decisions at critical moments? How do we build AI systems we can rely on?
Questions like these guide much of our AI work at Thales, and most of our products and systems already incorporate AI in one form or another. And because we operate in strategic industries such as aerospace, space, ground transportation and defence, we naturally set a high bar for ourselves.
Our approach to AI is based on the principles of validity, explainability, security and responsibility, which we consider the defining properties of trusted artificial intelligence. Our R&D teams are using innovate approaches to overcome the obstacles inherent in these four criteria so we can develop trusted AI applications for critical systems.
More broadly, we’re working to make human-machine dialogue more intuitive, and to make our systems more energy-efficient. AI is an exciting and challenging field that is not only driving growth and job creation at Thales, but unleashing a whole new wave of creative thinking."
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Writing 10 rules is hard enough, but writing 1,000 rules without each new rule causing a cascading effect on the others is a real mathematical challenge.
AI we can all trust – especially at decisive moments
Tomorrow's Technology: Trusted AI
Robust-by-design AI
Meet Teodora Petrisor, AI algorithm validation roadmap expert.
Knowledge of the real world will be incorporated into artificial neural networks to better interpret data and improve the speed and accuracy of systems in critical fields.
Trustable AI validation methodology
Meet Simon Fossier, Trustable AI validation methodology expert.
AI that has proven its reliability in real-life situations will help prevent the formation of contrails through the modification of aircraft trajectories, thus making a positive impact on the environment.
AI for safer drone traffic
Meet Mathieu Riou, Artificial neural networks expert.
AI and prediction models that can integrate physics, flight dynamics and weather data will enable safer drone traffic in built-up urban areas.
AI for radar optimisation
Meet Yann Brieche, Radar optimisation expert.
Artificial intelligence algorithms will allow radar systems to adapt dynamically to new weather conditions and operational situations.