AI Bias Mitigation: A Manager's Guide

While bias detection and mitigation is often seen as a technical problem, it is fundamentally a team effort, and managers play a critical role at every stage of an Artificial Intelligence (AI) project. 

Building on our previous webinar Machine Learning and Human Prejudice: Understanding Bias in AI, this workshop takes the conversation further and closer to where decisions are actually made. Participation in the webinar is not a prerequisite for this course.

This session is designed for those who lead teams, allocate resources, and are responsible for the impact of AI systems on people and organizations. Through real-world case studies, hands-on exercises, and a structured bias risk assessment, participants will learn to identify where bias enters the AI development lifecycle, assess the risks of their own use cases, and implement efficient governance practices, leaving with a concrete action plan they can bring back to their teams.

Agenda & Content

For a detailed timetable and additional information, please see Agenda & Content in the left menu.

Target audience, eligibility & prices

Managers and team leads who oversee, commission, or approve AI systems. No technical background is required.

This course is open and free of charge for all participants from academia, industry, and public administration from EU and/or EuroHPC JU member countries.

Entry level & prerequisites

Basic – basic familiarity with what AI systems are and how they are used in your organization is helpful, but no prior knowledge of AI bias or machine learning is needed.

Course format

This course will be delivered as a LIVE ONLINE COURSE (using Zoom).

Lecturers

Giulia Bianchi (AIT Austrian Institute of Technology GmbH)     
Giulia Bianchi is a Research Engineer at AIT Austrian Institute of Technology, where she leads the Machine Learning Group within the AI Task Force. With a background spanning linguistics and AI, she develops LLM-based systems including digital twins, chatbots, and knowledge extraction tools. Her work focuses on ensuring AI systems are not only technically robust but also fair and contextually appropriate across different user groups.

Daniel Lehner (AI Factory Austria AI:AT)                       
Dr. Daniel Lehner works as expert in AI knowledge transfer at AI Factory Austria AI:AT. He also works as a consultant and trainer at TwinTech, helping companies to efficiently exploit the potential of digitalization through the use of artificial intelligence and digital twins. In addition to his work with various companies, he also draws on his many years of experience in researching digital twins and artificial intelligence at Johannes Kepler University in Linz.

Language

English

Date, time, and location

15.04.2026, 09:00 – 12:00 (CEST), LIVE ONLINE COURSE (Zoom)

Registration

Registration is required, the registration form can be found on top of this page in the menu on the left.

Please register with your official institutional email address to prove your affiliation.

You will get an automatic confirmation by email (subject starting with "[Indico] Registration"), please check your Spam/Junk folders.

Following your successful registration, you will receive further information a few days before the course.

Please do not hesitate to contact us at training@ai-at.eu if you have any questions.

Waitinglist

After the number of registrations has reached its maximum or the registration form has been closed, you may want to send us an email (training@ai-at.eu) stating that you are interested to be put on the waiting list (vacancies may occur due to cancelations, etc.).

Modification, withdrawal & no-show policy

Your registration is binding. Please only register for the course if you are really going to attend.

You can update your registration data or withdraw your registration anytime before the registration form has been closed via the link "Manage my registration" which you can find at the bottom of your automatic email confirmation (subject starting with "[Indico] Registration").

Alternatively, or after the registration form has been closed, please inform us about your cancelation or any change in your registration data (especially your mobile-phone number) via email (training@ai-at.eu).

No-show policy: If you do not cancel and do not show up at the course you will be blacklisted and excluded from future training events.

Organizers

This course is organized by AI Factory Austria AI:AT.

Acknowledgements

AI Factory Austria AI:AT has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101253078. The JU receives support from the Horizon Europe Programm of the European Union and Austria (BMIMI / FFG).