The book discusses algorithms in relation to hardware and material conditions, code, data, and subjects such as users, programmers, but also βdata doublesβ. The individual chapters bridge critical discussions on bias, exclusion, or responsibility with the necessary detail on the contemporary state of information technology. The examples include state-of-the-art applications of machine learning, such as self-driving cars, and large language models such as GPT.
The book will be of interest for everyone engaging critically with algorithms, particularly in the social sciences, media studies, STS, political theory, or philosophy. With its broad scope it can serve as a high-level introduction that picks up and builds on more than two decades of critical research on algorithms.
Tobias Matzner is a professor for Digital Cultures and Digital Humanities at Paderborn University, Germany. His research focuses on the intersections of technology, culture, and politics, with a particular focus on algorithms and machine learning.