Despite the widespread use of artificial intelligence (AI), designing user experiences (UX) for
AI-powered systems remains challenging. UX designers face hurdles understanding AI …

Thinking of technology as a design material is appealing. It encourages designers to explore
the material's properties to understand its capabilities and limitations—a prerequisite to …

Prototyping AI user experiences is challenging due in part to probabilistic AI models making
it difficult to anticipate, test, and mitigate AI failures before deployment. In this work, we set …

Technology companies continue to invest in efforts to incorporate responsibility in their
Artificial Intelligence (AI) advancements, while efforts to audit and regulate AI systems …

To design with AI models, user experience (UX) designers must assess the fit between the
model and user needs. Based on user research, they need to contextualize the model's …

When prototyping AI experiences (AIX), interface designers seek useful and usable ways to
support end-user tasks through AI capabilities. However, AI poses challenges to design due …

Recently, artificial intelligence (AI) has been introduced into a variety of consumer
applications for creative work. Although AI-driven features in design tooling are nascent …

Artificial Intelligence (AI) plays an increasingly important role in improving HCI and user
experience. Yet many challenges persist in designing and innovating valuable human-AI …

What does it mean for a generative AI model to be explainable? The emergent discipline of
explainable AI (XAI) has made great strides in helping people understand discriminative …

AI models and services are used in a growing number of high-stakes areas, resulting in a
need for increased transparency. Consistent with this, several proposals for higher quality …