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Bias in GLAM: From Data Creation to Algorithmic Access

Bias in Galleries, Libraries, Archives, and Museums (GLAM) operates across the full data lifecycle – from collection decisions and cataloguing practices to algorithmic systems increasingly deployed for discovery and access. While research on bias in digital libraries has grown substantially, it has focused predominantly on textual data and metadata, leaving the multimodal nature of GLAM collections – encompassing image, audio, and audiovisual archives – without systematic attention. This workshop brings together researchers and practitioners from AI and machine learning, digital library science, and humanities, including art history, media studies, history, film studies, archaeology, and adjacent fields, to address data and algorithmic bias in multimodal GLAM collections, working toward a shared research agenda.

The workshop is co-located with the 17th International Conference on Theory and Practice of Digital Libraries (TPDL 2026) and will take place during the conference 22 September - 25 September 2026 in Faro, Portugal. We are planning a hybrid format to allow remote participation.