Veranstaltungen

​​​The public e-lecture is part of the seminar “Hacking Innovation Bias” by Dr. Clemens Striebing and Dr. Regina Sipos at TU Berlin. In their virtual talk they will discuss the question “How do you know if a data set is biased and how can we assess quality of data sets?” with Kasia Chmielinski, affiliated with the Berkman Klein Center for Internet and Society at Harvard University, and Co-Founder of The Data Nutrition Project.​​

Algorithms matter, and so does the data they’re trained on. To improve the accuracy and fairness of algorithms that determine everything from navigation directions to mortgage approvals, we need to make it easier for practitioners to quickly assess the viability and fitness of datasets they intend to train AI algorithms on.

​Kasia Chmielinski, affiliated with the Berkman Klein Center for Internet and Society at Harvard University, is the Co-Founder of The Data Nutrition Project. In their virtual talk at Fraunhofer IAO they will discuss:

• how you do know if a data set is biased,
• some recent case studies for bias in AI,
• some thoughts about governmental approaches to tackle these problems, and
• ​her thoughts how to tackle bias in AI bottom-up.

The event is aimed at

Scientists in the field of Data Science