New version: SAIAD 2024

SAIAD 2023 

5th Workshop

Safe Artificial Intelligence for All Domains

former Safe Artificial Intelligence for Automated Driving

in conjunction with CVPR 2023

Accepted papers will be published in  the CVPR workshop proceedings!

Date: Monday the 19th of June.

Fields of SAIAD

Safe AI in automotive industry

Safe AI in medical, rail traffic, aviation and aerospace

Ethics and legal in Safe AI

Standardization of Safe AI

Invited Speakers


After the success of ML and AI-based approaches in outperforming traditional vision algorithms, recently a lot of research effort is dedicated to understanding of the limitations and the general behavior of AI methods in a broad range of computer vision applications. Specifically for a successful introduction of ML and AI in a wider range of products, safety is often a top priority. Being able to ensure safety of ML based computer vision is key to unlock its potential in a broad range of safety related applications and future products. In domains like automotive, aviation and the medical domain, it paves the way towards systems with a greater degree of autonomy and assistance for humans. 

Accepted papers will be published in IEEE Xplore!

What we aim to achieve

The workshop focuses on bringing together researchers, engineers, and practitioners from academia, industry, and government to exchange ideas, share their latest research, and discuss the latest trends and challenges in this field. The workshop also aims to foster collaboration between different stakeholders, including computer vision researchers, machine learning experts, robotics engineers and safety experts, to create a comprehensive framework for developing safe AI systems for all domains. 

Overall, the SAIAD workshop aims to advance the state-of-the-art in safe AI, address the most pressing challenges, and provide a platform for networking and knowledge sharing among the experts in this field.

What is different from previous editions?

This workshop will focus on safe artificial intelligence in a wide range of application domains of Computer Vision and Pattern Recognition. Compared to previous editions of SAIAD, which focused exclusively on the automotive sector, the organizers decided to broaden the scope of topics to include (non-exhaustive listing):

This change has been reflected in the formation of the organizing committee as well as the proposed keynote speakers and other workshop content. We think that exchange across application domains of safe AI can stimulate the discovery of new approaches. We believe that regardless of the application domain, safety mechanisms for AI are implemented along the full development pipeline of safety-related AI-based systems: specification, data and model selection, training, evaluation / testing, monitoring and assurance argumentation.

Topics of Interest

1. Specification 

2. Data and DNN Architecture Selection 

3. Training  

4. Evaluation / Testing  

5. Monitoring  

Organized by

in conjunction with

Further Workshops in Safe AI