Abstract

As AI technologies rapidly evolve, building trust goes beyond technical robustness — it also requires sound legal foundations. In this session, legal expert Jos brings his deep expertise in data law, AI governance, and intellectual property to the forefront. As a core team member of the NL AI Coalition and a contributor to the Dutch NEN Standards Committee on AI and Big Data, Jos helps shape the legal frameworks and standards that enable responsible AI adoption.

He advises startups, scale-ups, and corporate clients on a wide range of legal topics, from data contracts and IP strategies to AI impact assessments (IAMI) and the legal aspects of M&A transactions involving AI-driven companies. Jos also represents clients in patent litigation, balancing innovation protection with fair market practices.

Join this talk to learn how legal considerations, impact assessments, and emerging standards play a vital role in fostering trust in AI implementations.

At the roundabout, take the second exit”, “recalculating route ...”, “ you have reached your destination” these are very well-known sentences coming from your “TomTom” when driving.

Why do so many people trust these messages? Even when stories about hiccups of navigation devices are popular small-talk topics, people still tend to follow navigation instructions blindly. When a driver follows our navigation instructions, they're placing their safety, time, and confidence in our hands.

How has TomTom managed to gain such a high level of trust? And, as we integrate advanced AI systems into our navigation technology how can we maintain trust? Illustrated with many practical examples, you will hear about TomTom's journey to win its drivers trust.

Abstract

The term "trustworthy AI" is everywhere these days, and rightfully so. AI systems are becoming an integral part of our society, from healthcare to transportation, so they absolutely need to be reliable.

But here's where it gets interesting: many AI systems are inherently untrustworthy by nature. They make mistakes, harbor biases, and behave unpredictably. 

This creates a paradox that raises a crucial question: how do we build a stable society on a technology that has this fundamental reliability problem?

Abstract

Cordis SUITE is a low-code software development platform focused on industrial automation and machine control. It enables engineers to develop complex control software through graphical models, without requiring extensive programming knowledge. By using UML diagrams, multidisciplinary teams can collaborate on designing machine behavior, with error-free code automatically generated for various hardware platforms such as PLCs and embedded controllers.

How does formal verification help build trust?