4 research outputs found
More Than Accuracy: Towards Trustworthy Machine Learning Interfaces for Object Recognition
This paper investigates the user experience of visualizations of a machine
learning (ML) system that recognizes objects in images. This is important since
even good systems can fail in unexpected ways as misclassifications on
photo-sharing websites showed. In our study, we exposed users with a background
in ML to three visualizations of three systems with different levels of
accuracy. In interviews, we explored how the visualization helped users assess
the accuracy of systems in use and how the visualization and the accuracy of
the system affected trust and reliance. We found that participants do not only
focus on accuracy when assessing ML systems. They also take the perceived
plausibility and severity of misclassification into account and prefer seeing
the probability of predictions. Semantically plausible errors are judged as
less severe than errors that are implausible, which means that system accuracy
could be communicated through the types of errors.Comment: UMAP '20: Proceedings of the 28th ACM Conference on User Modeling,
Adaptation and Personalizatio
Building Credibility, Trust, and Safety on Video-Sharing Platforms
Video-sharing platforms (VSPs) such as YouTube, TikTok, and Twitch attract millions of users and have become influential information sources, especially among the young generation. Video creators and live streamers make videos to engage viewers and form online communities. VSP celebrities obtain monetary benefits through monetization programs and affiliated markets. However, there is a growing concern that user-generated videos are becoming a vehicle for spreading misinformation and controversial content. Creators may make inappropriate content for attention and financial benefits. Some other creators also face harassment and attack. This workshop seeks to bring together a group of HCI scholars to brainstorm technical and design solutions to improve the credibility, trust, and safety of VSPs. We aim to discuss and identify research directions for technology design, policy-making, and platform services for video-sharing platforms. © 2023 Owner/Author