Algorithms

Technology, Culture, Politics
1. Auflage 2023
ISBN: 978-1-032-29061-4
Verlag: Routledge

Buch, Englisch, 202 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 461 g

Algorithms: Technology, Culture, Politics develops a relational, situated approach to algorithms. It takes a middle ground between theories that give the algorithm a singular and stable meaning in using it as a central analytic category for contemporary society and theories that dissolve the term into the details of empirical studies.

The book discusses algorithms in relation to hardware and material conditions, code, data, and subjects such as users, programmers, but also “data doubles”. 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.

Zielgruppe

General, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Matzner, Tobias

Fachgebiete

• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein

Inhaltsverzeichnis

Part I; 1. Towards a relational theory of algorithms; 2. Algorithms as relational from the beginning: three historical sketches; 3. Theorizing complimentary abstractions: from ontological to radical situatedness; Part II; 4. Algorithms and Material Conditions; 5. Algorithms and Code; 6. Algorithms and Data; 7. Algorithms and Subjects; 8. Algorithms and Humans; 9. Conclusion

Über Autor(innen)

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.