About this scholarly article

Suspicious Behavior: A fictional annotation tutorial by Linda Kronman; Andreas Zingerle is a scholarly article available to read on EtoBox.

Suspicious Behavior is a fictional annotation tutorial inviting readers to critically examine machine learning datasets assembled for anomaly detection in surveillance footage (Figure ). Mimicking existing annotation interfaces and practices [12] the tutorial, although fictive, provides insight into the hidden work of crowdsourced labor and how annotators engage in decision making (Figure ). Readers in the role of annotator-trainees, advance through an introduction and three 'advanced modules' of the tutorial performing what is called 'Human Intelligence Tasks.' The assignment is to spot suspicious behavior in video segments. Throughout the interactive story the reader gets trained for an optimized annotation workflow, balancing between accuracy and efficiency.Within the interactive story YouTube video montages are used to contextualize the hidden human labor of image annotators as fundamental for artificial intelligent. Research on dataset annotation on the other hand suggest that undesired bias gets embedded into datasets through the individual subjective annotator [3, 7]. However, traversing through Suspicious Behavior it becomes gradually evident that annotation work is more ab

Author

Linda Kronman; Andreas Zingerle

Publisher

ACM

Published

2022

Language

EN