Storytelling scaffolds meaning-making within human–nonhuman relationships. While more-than-human design, particularly in the multispecies design, has established storytelling as a productive lens for noticing the world, this work extends this foundation toward active sense-making through The Cat Fiction—a method leveraging generative AI to craft situated stories grounded in daily human–cat interactions. The method orchestrates empathy through an anthropomorphic first-cat narrator and defamiliarization through interplay of reality and fiction. A month-long exploratory study revealed that AI-generated stories evoked affective resonance and curiosity, supporting participants in reframing their relationships with cats through iterative reflection and interpretation. This paper contributes: (1) The Cat Fiction, a method orchestrating empathy and defamiliarization for situated multispecies storytelling; (2) empirical insights on how AI-generated narratives support relational sense-making; and (3) a conceptual framework for orchestration at three levels of narrative strategies, narrative materials, and researcher stance for responsible more-than-human design.

Generative Artificial Intelligence (GAI) offers new opportunities for reconstructing these unrecorded memory scenes, yet existing web-based tools undermine users’ sense of agency through disengaging and unpredictable interactions. In this work, we advance three design arguments about how slow, tangible interaction can reshape human–AI relationships by making temporality, embodied agency, and generative processes experientially legible. We instantiate these arguments by presenting Memory Printer, a tangible design that combines silk-screen printing metaphors with text-to-image generation. The design features layered reconstruction that decomposes image generation into incremental steps, a physical wooden scraper enabling embodied control over image revelation, and built-in printing that produces tangible photos. We examine these arguments through a comparative study with 24 participants, exploring how participants engage with, interpret, and respond to this interaction stance. The study surfaces both opportunities—such as vivid memory evocation, heightened sense of control, and creative exploration—and critical tensions, including risks of false memory formation, algorithmic bias, and data privacy. Together, these findings articulate important boundaries for deploying generative AI in emotionally sensitive contexts.

Play is pivotal in fostering the emotional, social, and cultural dimensions of urban spaces. While generative AI (GAI) potentially supports playful urban interaction, a balanced and critical approach to the design opportunities and challenges is needed. This work develops iWonder, an image-to-image GAI tool engaging fourteen designers in urban explorations to identify GAI's playful features and create design ideas. Fourteen citizens then evaluated these ideas, providing expectations and critical concerns from a bottom-up perspective. Our findings reveal the dynamic interplay between users, GAI, and urban contexts, highlighting GAI's potential to facilitate playful urban experiences through generative agency, meaningful unpredictability, social performativity, and the associated offensive qualities. We propose design considerations to address citizen concerns and the `tourist metaphor' to deepen our understanding of GAI's impact, offering insights to enhance cities' socio-cultural fabric. Overall, this research contributes to the effort to harness GAI's capabilities for urban enrichment.

New digital tools offer biodesign with unprecedented opportunities for monitoring, fabricating, iterating, and scaling designs. Serving aligned purposes and beyond, the Digital Twin (DT) is an emerging concept in bioindustries including bioprocessing and agri-food. In these fields, DTs enable comprehensive digital representations of a living system or process with continuous bidirectional connection to the physical world. Despite the concept’s potential to address certain challenges of uncertainty in designing (with) living systems, its applications and implications in biodesign and research remain largely underexplored. To bridge this gap, we propose a conceptual framework that synthesizes existing instantiations of DTs within bioindustries through a dataflow lens. We mobilize the framework through a proof-of-concept DT for biofabrication with mycelium, by unpacking the dataflows within the identified design and operation cycles. We conclude with a discussion on how DT capabilities respond to uncertainties in designing with living systems, limitations, and future work.

Good explanations help people understand hateful memes and mitigate sharing. While AI-enabled automatic detection has proliferated, we argue that quality-controlled crowdsourcing can be an effective strategy to offer good explanations for hateful memes. This paper proposes a Generate-Annotate-Revise workflow to crowdsource explanations and presents the results from two user studies. Study 1 evaluated the objective quality of the explanation with three measurements: detailedness, completeness, and accuracy, and suggested that the proposed workflow generated higher quality explanations than the ones from a single-stage workflow without quality control. Study 2 used an online experiment to examine how different explanations affect users' perception. The results from 127 participants demonstrated that people without prior cultural knowledge gained significant perceived understanding and awareness of hateful memes when presented with explanations generated by the proposed multi-stage workflow as opposed to single-stage or machine-generated explanations.

Designing future IoT ecosystems requires new approaches and perspectives to understand everyday practices. While researchers recognize the importance of understanding social aspects of everyday objects, limited studies have explored the possibilities of combining data-driven patterns with human interpretations to investigate emergent relationships among objects. This work presents Thing Constellation Visualizer (thingCV), a novel interactive tool for visualizing the social network of objects based on their co-occurrence as computed from a large collection of photos. ThingCV enables perspective-changing design explorations over the network of objects with scalable links. Two exploratory workshops were conducted to investigate how designers navigate and make sense of a network of objects through thingCV. The results of eight participants showed that designers were actively engaged in identifying interesting objects and their associated clusters of related objects. The designers projected social qualities onto the identified objects and their communities. Furthermore, the designers changed their perspectives to revisit familiar contexts and to generate new insights through the exploration process. This work contributes a novel approach to combining data-driven models with designerly interpretations of thing constellation towards More-Than Human-Centred Design of IoT ecosystems.

Writing is challenging, especially for non-native speakers. To support English as a Second Language (ESL) writing, we propose StructFeed, which allows native speakers to annotate topic sentence and relevant keywords in texts and generate writing hints based on the principle of paragraph unity. First, we compared our crowd-based method with three naive machine learning (ML) methods and got the best performance on the identification of topic sentence and irrelevant sentence in the article. Next, we evaluated the StructFeed system with two feedback-generation mechanisms including feedback generated by one expert and by one crowd worker. The results showed that people who received feedback by StructFeed got the highest improvement after revision.

Effective space monitoring helps improve utilization of seminar rooms in the work place. This paper presents CrowdButtons as a simple solution to real-time space monitoring by crowdsourcing. CrowdButtons are tangible reporting devices designed to collect room status data from passersby. Anyone may participate in the micro QA task instantly by clicking a button, while the dashboard displays real-time room status as well as visualization of space usage patterns over time.

Humorous images can be seen in many social media websites. However, newcomers to these websites often have trouble fitting in because the community subculture is usually implicit. Among all the types of humorous images, Internet memes are relatively hard for newcomers to understand. In this work, we develop a system that leverages crowdsourcing techniques to generate explanations for memes. We claim that people who are not familiar with Internet meme subculture can still quickly pick up the gist of the memes by reading the explanations. Our template-based explanations illustrate the incongruity between normal situations and the punchlines in jokes. The explanations can be produced by completing the two proposed human task processes. Experimental results suggest that the explanations produced by our system greatly help newcomers to understand unfamiliar memes. For further research, it is possible to employ our explanation generation system to improve computational humanities.

We present an audio installation allowing participants to create sounds by looking at different parts of surfaces or objects in various color and texture. By hacking a desktop eye tracker to track gaze points in 3D space, and deploying a webcam to pick up the hue, saturation and brightness of gazed material, we create an experimental musical instrument that can be played by eye gaze. Users have the freedom of choosing different raw materials and explore ways of seeing as a mean of self-expression to create a unique audio experience.

This study aimed to explore the effects of the multimedia teaching material incorporated with TTS on college students’ English learning. 44 sophomore participants enrolled in the course “English Reading” were selected as volunteers at one selected university in Taiwan. The techniques of data collection in this study included (a) questionnaire, (b) open-ended questions, and (c) pre-test and post-test of vocabulary tests. This study found that the multimedia teaching material (a) enhanced students’ vocabulary learning, (b) facilitated students’ pronunciation and listening, (c) constructed knowledge, and (d) raised learning motivation. The effects of multimedia teaching material found in this study can be linked to students’ autonomous learning and teacher autonomy.

Interactive digital art in the field of performance is emerging as an increasingly important form of artistic expression in Taiwan. Dinner of Luciérnaga is an interdisciplinary project produced by more than ten talented members which include the director, dancer, choreographer, artist, interactive designer, sound designer, iPhone app engineer, image processing designer, stage designer and light designer. The goal of this project is to create new modes of interactive participation between the performers and audience through the use of an innovative iPhone application that links dancer to audience and audience to dancer. The application not only plays a key role in connecting the audience and dancer, but also uses an interesting sound generation application that enhances the spectators' experience. It creates and shares special interactive experiences. Dinner of Luciérnaga is a story about the relationship of light and human in the digital era. It is a stunning performance in visuals and interactive process with focus on new interface that are put into use in authentic environments for validation by audience. In this paper, we will discuss our artistic motivation, the development of the digitally interactive performances, and our process for creating the digitally interactive performance entitled Dinner of Luciérnaga.

A number of peak-to-average power ratio (PAPR) reduction techniques have been proposed for orthogonal frequency division multiplexing (OFDM) systems; however, most of them require transmitting side information and thus reduce the bandwidth efficiency. The existing constellation extension (CE) schemes do not need to transmit side information. In this paper, we propose an improved CE scheme for PAPR reduction of OFDM signals with 16-QAM modulation. The proposed CE scheme has four extendable constellation points, the four corners in the 16-QAM constellation, and each extendable constellation point has two possible extended constellation points. The proposed CE scheme, when compared with previous related CE schemes, has fewer extendable constellation points and more corresponding extended constellation points, resulting in better BER performance with almost the same PAPR reduction. Computer simulations are given to demonstrate the effectiveness of the proposed scheme.