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In this talk I want to give people a better understanding of why and how algorithmic systems are biased and how people are trying to solve problems these biases cause. Specifically, we will see how data collection and interpretation, model creation, problem definition, definition of success and even the design of outputs can impact algorithmic systems – or improve justice and equality, if proper thought and care is put into designing them.
As a computer science student, students' rights activist and privacy activist, I have worked on the topic of algorithmic bias at various institutions and with different groups of people.
A one-page article I co-authored on the topic of algorithmic bias aimed at students in Austria can be found at <a href="https://www.progress-online.at/artikel/wenn-der-algortihmus-zum-unterdr%C3%BCcker-wird">Progress magazines' website</a>.
A write-up for the masters' course "Critical Algorithm Studies" at TU Wien can be found on <a href="https://pascoda.fairydust.space/index.php/2018/09/write-up-bias-in-algorithmic-systems/">my blog</a>. It discusses which current issues in algorithmic systems are, in my opinion, the most urgent ones.