People vs. Algorithms: Data Witchcraft and the Future of Data Activism
Recommender systems and personalisation algorithms, search engines and chatbots, big data and machine learning: digital technologies play an increasingly prominent role in the creation, collection, organisation, and dissemination of information in our digital world. These technologies have the potential to reshape our traditional practices and concepts of knowledge, to transform processes of learning and knowing. For example, personalised recommender systems have complemented, if not replaced, testimony from friends and expert opinion. Students increasingly depend on search engines for factual knowledge in lieu of rote learning, and scientists rely on big data and machine learning for novel insights.
These powerful technologies, however, also can be—and, indeed, have been—misused and abused: fake news and “alternative facts” are spread online via chatbots and trolls; personalisation may lead to filter bubbles and echo chambers; correlations are mistaken as causation in decision-making powered by data analytics. As a result, information technologies and data practices are challenging our basic understanding of ‚knowledge‘ and related concepts such as truth, trust, reliability.
If societies want to ensure that these new technologies and practices are conducive to our knowledge, it is essential to examine more closely these novel knowledge practices, their underlying assumptions and implications. This public lecture series invites internationally renowned scholars to discuss major epistemic questions related to information technologies.
Additional speakers may be added to the lecture series. To get the latest updates on the EIT Public Lecture series, please visit http://uhh.de/inf-eit