Slanted Speculation: Material Encounters with Algorithmic Bias
DIS’22: ACM SIGCHI Conference on Designing Interactive Systems (DIS)
Session: Computational design
Abstract
Over the past few years, AI bias has become a central concern within design and computing fields. But as the concept of bias has grown in visibility, its meaning and form have become harder to grasp. To help designers realize bias, we take inspiration from textile bias (the skew of woven material) and examine the topic across its myriad forms: visual, textual, and tactile. By introducing a slanted experience of bias, we explore the translation of fraught machine learning algorithms into personal and probing artifacts. In this pictorial, we present nine pieces that materialize complex relationships with machine learning; ground these relationships in the present and the personal; and point to generative ways of engaging with biased systems around us.
DOI:: https://doi.org/10.1145/3532106.3533449
WEB:: https://dis.acm.org/2022/
Video Presentations of DIS 2022
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