date 07 November, 2026 – 2:40 PM
Conjontly Bonnie Mitchell (SIGGRAPH)
Online: Registration needed
ISEA2026 Dubai
ELYAH: Constellating Place, Data and Identity
Ten days of art, ideas, and innovation.
6 to 15 November 2026
Dubai, United Arab Emirates – Academic program online
Despite geopolitical instability and some delay, ISEA 2026 will be held this November in a hybrid format and globally available.
The special track 6th Summit in New Media Art Archives
will be held on 7 November from 13:00 to 22:30(CET)
The 6th Summit on New Media Art Archiving brings together artists, researchers, curators and cultural practitioners working at the intersection of digital media, emerging technologies and contemporary artistic practice. Positioned as one of the key special programme strands within ISEA2026, the Summit offers space to examine how new media art continues to evolve across platforms, cultures, institutions and publics. As part of the summit there is the presentation by Sanra Alvaro and Bonnie Mitchell:
Archiving New Media Art in the Age of AI: Transformations in Knowledge Acquisition, Processing and Dissemination
As new media art continues to expand rapidly, the need for extensive online and physical archives to document these works has become increasingly critical. New media art archiving differs from traditional archiving practice and introduces new challenges related to data ingestion, indexing, metadata extraction, validation, preservation, and accessibility.
These processes are increasingly complex, labour-intensive, and error-prone as collections expand in scale and heterogeneity. This paper examines the evolving role of artificial intelligence (AI) and other computational solutions in archival practice, with a focus on their application to new media art archives.
It explores how AI, specifically Machine Learning techniques like natural language processing, computer vision, and large language models, can support automated ingestion pipelines, metadata extraction and indexing, data validation, and advanced data analysis. Through concrete examples using the ACM SIGGRAPH and ISEA online archives, the paper discusses how AI can reduce manual labour, improve data quality, uncover relationships across large datasets, and enhance search and retrieval through semantic and user-centred interfaces.
At the same time, it critically addresses the limitations and risks of AI, including bias, transparency, accountability, environmental impact, and the potential erosion of archival expertise. The paper argues that AI should be understood not as a replacement for archivists but as an augmentative tool that, when critically applied, can strengthen archival workflows while preserving core archival values such as authenticity, provenance, and ethical responsibility.