Can Algorithms be Fair?
Date & time: Dec 11, 17:00-18:30.
Location: University of Zurich (see attached flyer)
Arguably the most important consequence of a society producing zillions of data is the possibility of using these data to generate new predictive models and improve existing ones.
The models defined in this way however reflect the human biases and unjust social structures in the data used to train the models. In other words, discrimination and unfairness can be transmitted through the most common machine learning algorithms to statistical models or decision-making rules impacting the lives of citizens. On the other hand, some computer scientists claim to have developed machine learning algorithms that can guarantee that the models will be free of bias, non-discriminatory, or fair. In this workshop we present and discuss some of these approaches together with current attempts by companies to deal with the problem.
Join us at this public event to get key insights from our renowned invited speakers. Find more information here.
The event will have two keynote speakers: Bart Custers is an internationally renowned expert in Algorithmic bias. Matthias Spielkamp is the Executive Director of AlgorithmicWatch, this is a new German NonProfit organization which focuses on social and ethical aspects on algorithmic decision making.
Please send a short e-mail to email@example.com, if you would like to participate in the event, so that they can estimate the number of guests for the subsequent apero.
Link to event page.
(There will be an internal Data Ethics Expert Group meeting preceding this event with invited guests and group members. However, members of the Alliance who are interested in joining this meeting please contact Prof. Christoph Heitz for more information.)