Designing for uncertainty
Designing when a system's capabilities or outputs are not fully predictable.
6 papers carry this themeView in grid →
In these papers
- 01Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI LiteratureShuning Zhang, Hui Wang et al. · 2025Configurations of agency and control are still unsettled.
- 02Creating Design Resources to Scafold the Ideation of AI ConceptsNur Yildirim · 2023Scaffolds ideation of hard-to-envision AI capabilities.
- 03Data in design: How big data and thick data inform design thinking projectsStefano Magistretti b, Claudio Dell'Era b · 2023Helps firms cope with uncertainty and complexity.
- 04Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to DesignQian Yang · 2020Uncertainty around AI's capabilities and output complexity.
- 05Investigating How Experienced UX Designers Effectively Work with Machine LearningQian Yang · 2018Hard to envision what ML can do for UX.
- 06UX Design Innovation: Challenges for Working with Machine Learning as a Design MaterialGraham Dove, Kim Halskov · 2017ML's unpredictability complicates UX design innovation.