Course 12: Digitization and Data Materialism in Digital Humanities

Selena Savic · FHNW

Lecturer

Selena Savic is a researcher and architect whose work interrogates the material conditions of data, digital archives, and artificial intelligence through feminist, postcolonial, and posthumanist frameworks. She previously headed the Make/Sense PhD programme at the Basel Academy of Art and Design (FHNW) and is currently Assistant Professor for Proto-history of Artificial Intelligence and Machines in the Arts at the University of Amsterdam. Her concept of data materialism challenges idealist views of digital data by emphasizing the labor, infrastructures, and power relations embedded in data collection, classification, and circulation. She has contributed to critical media studies, digital humanities methodology, and the emerging field of AI art history.

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Lecture Overview

Overview

Savic develops a critical account of digitization through the lens of data materialism. Rather than treating digital data as abstract or immaterial, she emphasizes the infrastructures, classifications, labor, and power relations that make data possible and shape how it is used in digital humanities.

Main Points

The lecture argues against data idealism and proposes data materialism as a way of understanding digitization as a material, situated process.
Savic brings together new materialism, feminist methods, and anti-colonial critique to rethink how digital humanities handles data.
Classification is a central concern: once data is collected and organized, socially produced categories can become naturalized and appear neutral.
Access is also material and political; search infrastructures, databases, and platforms shape what becomes visible, retrievable, and usable.
The lecture combines theoretical reflection with practical methodological concerns, including programmatic work on textual corpora and social media data.

Examples Mentioned

Topic modeling and analysis of Twitter discourse
Data feminism and related critical methods
Database critique and classification bias
Search and access problems linked to platform power and colonial assumptions

Source transcript: transcripts/Course 12_Savic_Digitization.txt

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