Visualizing Machine Learning Uncertainty Part of Project IKON From qualitative research I conducted, we concluded that our use case called for an ML-driven visualization, as this could show stakeholders potential thematic overlaps between research projects and knowledge transfer activities. At the same time as we concluded that an ML-driven visualization was needed, we predicted that […]
Category: Project IKON
Sense-Making of Machine Learning by Non-ML experts Part of Project IKON To understand how stakeholders would make sense of the proposed prototype, we developed a method for conducting co-design workshops with actual ML technologies. Designing bespoke transparencies that represented possible explanations (see left), participants engaged in a series of open tasks. We studied the patterns […]