Trustworthiness of AI in Automated Vehicles Webinar

Mind the Gaps Webinar Series

Trustworthiness of AI in Automated Vehicles

4 March 2026

8:30 AM ET - 10:00 AM ET

Currently there is real hype about Agentic AI. Automotive certainly is one of the most critical applications. There are many different approaches for utilizing all kinds of AI techniques to implement highly automated driving functions. What about safety, security and reliability of automated vehicles? Will the public trust AI driven vehicles?

This webinar, presented by IEEE SA's Mobility Practice, will address the potential, risks, soundness, and feasibility of AI in highly automated vehicles.

This webinar will cover the following topics:

AI versus human intelligence
Which AI techniques are crucial for automated driving systems?
How to mitigate AI embedded risks?
Are there any changes/challenges in daily use of vehicles?
Are there standardization or regulatory challenges not addressed yet?

Each speaker will have 20 minutes to present their point of view followed by 15 minutes for audience questions at the end of all presentations.

Who should attend the webinar?

The Webinar is a great opportunity to learn about cutting-edge research results and industrial practices. New ideas and novel approaches will be presented and discussed.

Key automotive industry leaders such as OEMs and suppliers
Researchers / Innovators
Engineers of the mobility industry
Mobility service providers
Road operators as well as Traffic Managers
Software and internet companies
Public Authorities
Private and Public Operators (Fleet Managers, Service Providers)
Semiconductor firms (AI platforms)
Telecom operators

The information presented will deepen your understanding regarding AI as an enabler for automated driving functions. Renowned speakers may answer questions such as how it is used, how it works, its capabilities, and its potential to accelerate the large-scale deployment of automated vehicles globally.

SPEAKERS

Thomas Walloschke

Strategy Advisor, Cyber Security Consulting

Topic: Multi-Stage LLM-Driven Policy and Code Generation for Zero Trust Access Control in Automotive Data Spaces: A Proof-of-Concept Addressing Developer Pitfalls