Jo Vermeulen

Vivian Liu, Jo Vermeulen, George Fitzmaurice et al.

Text-to-image AI are capable of generating novel images for inspiration, but their applications for 3D design workflows and how designers can build 3D models using AI-provided inspiration have not yet been explored. To investigate this, we integrated DALL-E, GPT-3, and CLIP within a CAD software in 3DALL-E, a plugin that generates 2D image inspiration for 3D design. 3DALL-E allows users to construct text and image prompts based on what they are modeling. In a study with 13 designers, we found that designers saw great potential in 3DALL-E within their workflows and could use text-to-image AI to produce reference images, prevent design fixation, and inspire design considerations. We elaborate on prompting patterns observed across 3D modeling tasks and provide measures of prompt complexity observed across participants. From our findings, we discuss how 3DALL-E can merge with existing generative design workflows and propose prompt bibliographies as a form of human-AI design history.

Ian Drosos, Jo Vermeulen, George Fitzmaurice et al. · microsoft-research

People frequently use online forums to get help from experts to answer questions about feature-rich software. However, they may have to wait minutes, hours, or even days to receive advice. We investigate the potential to leverage experts to provide quicker help. We collected over 200 questions from online forums for two feature-rich software applications and suspected a quarter were short enough to be answered in less than one minute (defined as nanoquestions). We then conducted a study with 28 experts recruited from help forums to confirm this assumption, and explore whether there was a preference between text and audio answers. For more than half of the nanoquestions participants saw, they could give advice that they believed was helpful in under 60 seconds. Finally, we collected feedback about what makes a question quick to answer to inspire the design of future tools for ultra rapid human-to-human help.

Hang Chu, Amir Hosein Khasahmadi, Karl D. D. Willis et al.

User modeling is crucial to understanding user behavior and essential for improving user experience and personalized recommendations. When users interact with software, vast amounts of command sequences are generated through logging and analytics systems. These command sequences contain clues to the users' goals and intents. However, these data modalities are highly unstructured and unlabeled, making it difficult for standard predictive systems to learn from. We propose SimCURL, a simple yet effective contrastive self-supervised deep learning framework that learns user representation from unlabeled command sequences. Our method introduces a user-session network architecture, as well as session dropout as a novel way of data augmentation. We train and evaluate our method on a real-world command sequence dataset of more than half a billion commands. Our method shows significant improvement over existing methods when the learned representation is transferred to downstream tasks such as experience and expertise classification.

Tao Long, Kendra Wannamaker, Jo Vermeulen et al.

Design thrives on feedback. However, gathering constant feedback throughout the design process can be labor-intensive and disruptive. We explore how AI can bridge this gap by providing effortless, ambient feedback. We introduce FeedQUAC, a design companion that delivers real-time AI-generated commentary from a variety of perspectives through different personas. A design probe study with eight participants highlights how designers can leverage quick yet ambient AI feedback to enhance their creative workflows. Participants highlight benefits such as convenience, playfulness, confidence boost, and inspiration from this lightweight feedback agent, while suggesting additional features, like chat interaction and context curation. We discuss the role of AI feedback, its strengths and limitations, and how to integrate it into existing design workflows while balancing user involvement. Our findings also suggest that ambient interaction is a valuable consideration for both the design and evaluation of future creativity support systems.

Gonzalo Gabriel Méndez, Jagoda Walny, Søren Knudsen et al.

Constructive approaches to visualization authoring have been shown to offer advantages such as providing options for flexible outputs, scaffolding and ideation of new data mappings, personalized exploration of data, as well as supporting data understanding and literacy. However, visualization authoring tools based on a constructive approach do not scale well to larger datasets. As construction often involves manipulating small pieces of data and visuals, it requires a significant amount of time, effort, and repetitive steps. We present ReConstructor, an authoring tool in which a visualization is constructed by instantiating its structural and functional components through four interaction elements (objects, modifiers, activators, and tools). This design preserves most of the benefits of a constructive process while avoiding scalability issues by allowing designers to propagate individual mapping steps to all the elements of a visualization. We also discuss the perceived benefits of our approach and propose avenues for future research in this area.

Mirzel Avdic, Jo Vermeulen

The popularity of voice-controlled smart speakers with intelligent personal assistants (IPAs) like the Amazon Echo and their increasing use as an interface for other Internet of Things (IoT) technologies in the home provides opportunities to study smart speakers as an emerging and ubiquitous IoT device. Prior research has studied how smart speaker usage has unfolded in homes and how the devices have been integrated into people's daily routines. In this context, researchers have also observed instances of smart speakers' 'black box' behaviour. In this position paper, we present findings from a study we conducted to specifically investigate such challenges people experience around intelligibility and control of their smart speakers, for instance, when the smart speaker interfaces with other IoT systems. Reflecting on our findings, we discuss new possible directions for smart speakers including physical intelligibility, situational physical interaction, and providing access to alternative interpretations in shared and non-shared contexts.