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Utrecht ľ�ϸ���Ӱ�� aims for diversity and societal inclusion. For instance, the Gender and Diversity Hub provides an interdisciplinary platform for academic expertise and societal impact. One of the ways in which they do this is with monthly lunch meetings on themes such as gender equality and diversity.

“We've got plenty, so don't be shy!” reassured Rosemarie Buikema, one of the leaders of the Hub, while she gestures towards the full scales of bread rolls in the corner of the room. As soon as everyone has a full plate and a seat, Buikema notices that there are a few new faces.

That is why she briefly explains what the goal of the Hub is and why it is part of the strategic theme Institutions for Open Societies (IOS): “We want to make irreversible differences. So not ‘just’ crank up the diversity of institutions for a while, but actively involving ourselves with the question of what it means to change the structures of our community.”

“I'm more interested in the conversation that we can have than in the presentation.”

A new topic is discussed every month, and today, �鲹���ë���� Xenidis, a postdoc in EU laws regarding gender equality, and Rosa Wevers, a PhD candidate in gender studies, lead the meeting on gender and diversity in the digital era.

The research into algorithmic discrimination and data-driven inequality is one of the Seed Money Projects of IOS. “Feel free to interrupt me,” says �鲹���ë���� when she starts, “I'm more interested in the conversation we can have than in the presentation.” The tone is set.

About the research

Algorithms often influence our choices and preferences without our notice. They are deployed on a large scale, and it is important to investigate how harmful stereotypes and representations of minority groups find its effects.

Computers are seen as objective, but the way we 'raise' them still provokes questions.

Although computers are often advertised as objective and neutral, the way in which the computers are ‘raised’ provokes questions. Doubts arise on whether or not the current anti-discrimination laws are well-equipped enough to deal with this and if they provide the necessary safeguards.

While Xenidis and Wevers continue their story, everbyeone is taking notes. According to the two researchers, important questions need to be reasked and legal, sociological, cultural and technological expertises should come together. The lunch meeting provides a first opportunity.

The conversation

Now that the foundation has been laid, hub leader Linda Senden opens the floor for the conversation. We quickly see that the presentation has made people think. Many questions are raised.

Isn't discrimination inevitable when using Artificial Intelligence?

How can discrimination be defined? Isn't discrimination inevitable when Artificial Intelligence based on neural networks is used? Is the discrimination by algorithms comparable to when it is done by humans?

Isn't Artificial Intelligence just learning patterns? And how to cope with people denying their guilt, ‘It wasn't me, it was the algorithm?’

Contributions are being made from various angles. Xenidis and Wevers are happy with the input. Xenidis ends the meeting: “I like how we are filling in the gaps, thankyou for this.”

Leftovers

The meeting gets closed. Bags are picked up and notes are taken at hand. Small groups get together and the sparring continues.

The remaining bread rolls are left behind.

It looks as if the conversation is only just getting started. Addresses are shared and the remaining bread rolls are left behind in the corner.

The next Brown Bag Lunch Meeting will take place on 10 December. Are you interested? Please take a look at the event. Do you have a topic of your own that you would like to discuss with the hub one day? That is also possible! Please contact genderanddiversityhub@uu.nl.