Algorithms have risen to become one, if not the central technology for producing, circulating, and evaluating knowledge in multiple societal arenas. In this book, scholars from the social sciences, humanities, and computer science argue that this shift has, and will continue to have, profound implications for how knowledge is produced and what and whose knowledge is valued and deemed valid. To attend to this fundamental change, the authors propose the concept of algorithmic regimes and demonstrate how they transform the epistemological, methodological, and political foundations of knowledge production, sensemaking, and decision-making in contemporary societies. Across sixteen chapters, the volume offers a diverse collection of contributions along three perspectives on algorithmic regimes: the methods necessary to research and design algorithmic regimes, the ways in which algorithmic regimes reconfigure sociotechnical interactions, and the politics engrained in algorithmic regimes.

Juliane Jarke is Professor of Digital Societies at the University of Graz. Her research attends to the increasing importance of digital data and algorithmic systems in the public sector, education and for ageing populations. She received her PhD in Organisation, Work and Technology from Lancaster University and has a background in computer science, philosophy and STS.
Bianca Prietl is Professor for Gender Studies with a Focus on Digitalization at University of Basel. Her main area of expertise is feminist technoscience studies, with her more recent work focusing on the interrelations of knowledge, power, and gender in the context of (digital) datafication.
Simon Egbert, PhD, is a postdoc researcher at the faculty of sociology of Bielefeld University, working in the research project ‘The Social Consequences of Algorithmic Forecast in Insurance, Medicine and Policing’ (ERC grant agreement No. 833749). His research interests are science and technology studies, algorithm studies, sociology of testing and sociology of the future.
Yana Boeva is a Postdoctoral Researcher at the Institute for Social Sciences and the Cluster of Excellence “Integrative Computational Design and Construction for Architecture (IntCDC)”, University of Stuttgart. Her research explores the transformation of design, architectural practice, and different user expectations of computation and automation.
Hendrik Heuer, Dr., is a senior researcher at the University of Bremen. His research focuses on Human-Computer Interaction and Machine Learning. Currently, he is working on ways to fight misinformation. He studied and worked in Bremen, Stockholm, Helsinki, and Amsterdam and was a visiting postdoctoral research fellow at Harvard University.
Maike Arnold is a research associate at the KRITIS research training group and the Institute of Philosophy at TU Darmstadt. Their research focuses on trust in testimony in the context of critical decision making, especially concerning critical infrastructures and in the context of the algorithmization of information technology systems.

Algorithmic Regimes: Methods, Interactions, and Politics
Knowing in Algorithmic Regimes. An Introduction
METHODS
Revisiting Transparency Efforts in Algorithmic Regimes
Understanding and Analyzing Science’s Algorithmic Regimes – a Primer in Computational Science Code Studies
Sensitizing for Algorithms Foregrounding Experience in the Interpretive Study of Algorithmic Regimes
Reassembling the Black Box of Machine Learning: Of Monsters and the Reversibility of Foldings
Methods in algorithmic regimes
INTERACTIONS
Buildings in the Algorithmic Regime: Infrastructuring Processes in Computational Design
The Organization in the Loop: Exploring Organizations as Complex Elements of Algorithmic Assemblages
Algorithm-Driven Reconfigurations of Trust Regimes: An Analysis of the Potentiality of Fake News
Recommender Systems Beyond the Filter Bubble: Algorithmic Media and the Fabrication of Publics
Taking to Machines. Knowledge Production and Social Relations in the Age of Governance by Data Infrastructure
POLITICS The Politics of Data Science. Institutionalizing Algorithmic Regimes of Knowledge Production 308
Algorithmic Futures: Governmentality and Prediction Regimes
Power and resistance in the Twitter bias discourse
Making Algorithms Fair. Ethnographic Insights from Machine Learning Interventions
Commentary: The Entanglements, Failures And Uncertainties Of Algorithmic Regimes
Index