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

Design In and From the Periphery: Building a Praxis of Resistance through Collective Investigations

This article presents notes resulting from qualitative research with a participatory approach, carried out in person and remotely with a group of young people from the Terra Firme neighborhood, in Belém-Pará, northern Brazil. The aim was to analyze how the engagement of designers in emancipation processes managed by socially oppressed groups can promote transformations in the practices of designers in participatory projects. The theoretical foundation is based on the Latin American critical thinking of authors such as Paulo Freire and Orlando Fals Borda, demonstrating how their legacy influenced designers in participatory projects. The theoretical framework and qualitative research allowed us to consider that the engagement of designers in popular struggles not only influences the change in the scope of projects, but also allows solidarity to emerge as their main element.

Customizations and Expression Breakdowns in Ecosystems of Communication Apps

International audienceThe growing adoption of emojis, stickers and GIFs suggests a corresponding demand for rich, personalized expression in messaging apps. Some people customize apps to enable more personal forms of expression, yet we know little about how such customizations shape everyday communication. Since people increasingly communicate via multiple apps side-by-side, we are also interested in how customizing one app influences communication via other apps. We created a taxonomy of customization options based on interviews with 15 "extreme users" of communication apps. We found that participants tailored their apps to express their identities, organizational culture, and intimate bonds with others. They also experienced expression breakdowns: frustrations around barriers to transferring personal forms of expression across apps, which inspired inventive workarounds to maintain cross-app habits of expression, such as briefly switching apps to generate and export content for a particular conversation. We conclude with implications for personalized expression in ecosystems of communication apps