Fairness and Ethics in Artificial Intelligence

Benjamin Timmermans


In this lecture you will learn through practical examples about fairness, bias and ethics in artificial intelligence. The following topics are discussed:
* Positioning ethics in Artificial Intelligence
* Different types of Artificial Intelligence
* Practical examples of what not to do
* Defining fairness for artificial intelligence
* Bias and mistakes made by AI systems
* Guidelines and ethical considerations for developers
* Creating value and trust in AI
* How to mitigate bias in AI
* The role of data privacy


Photo of Benjamin Timmermans

As lead University Programs for IBM Netherlands, my work involves research, innovation and education together with our clients, IBM Research and Universities. My expertise is in Artificial Intelligence, AI Fairness and Ethics, Human Robotics and Crowdsourcing. I studied business informatics at the HZ University of Applied Sciences, followed by a masters degree in information sciences at the Vrije Universiteit Amsterdam. I continued working at the university as a scientific researcher on open-domain question answering in IBM Watson. In 2016 I won a national prize for our education at the Vrije Universiteit about the technology behind IBM Watson. After three years I joined the IBM Center for Advanced Studies and continued my work on Artificial Intelligence and developed Dutch speech models for IBM Watson. I am leading our university activities in the Netherlands since 2019, and am a member of the Dutch AI Coalition, and both IBM’s AI and AI ethics committee in the Benelux.

Requested 1 time

Lecture languages



AI / AutomationData Science / Machine Learning

Duration options

0.5 hour1 hour2 hours

Travel/delivery options

In-countryOutside of country: Open for discussionRemote via video conference



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