Computational tools for fabrication often treat materials as passive rather than active participants in design, abstracting away relationships between craftspeople and materials. For craft communities that value relational practices, abstractions limit the adoption and creative uptake of computational tools which might otherwise be beneficial. To understand how better tool design could support richer relations between individuals, tools, and materials, we interviewed expert woodworkers, fiber artists, and metalworkers. We identify three orders of convivial relations central to craft: immediate relations between individuals, tools, and materials; mid-range relations between communities, platforms, and shared materials; and extended relations between institutions, infrastructures, and ecologies. Our analysis shows how craftspeople engage and struggle with convivial relations across all three orders, creating workflows that learn from materials while supporting autonomy. We conclude with design principles for computational tools and infrastructures to better support material dialogue, collective knowledge, and accountability, along with richer and more convivial relations between craftspeople, tools, and the material worlds around them.
Most learners worldwide are multilingual, yet implementing multilingual education remains challenging in practice. EdTech offers an opportunity to bridge this gap and expand access for linguistically diverse learners. We conducted a quasi-experiment in Uganda with 2,931 participants enrolled in a non-formal radio- and mobile-based engineering course, where learners self-selected instruction in Leb Lango (a local language), English, or a Hybrid option combining both languages. The Leb Lango version of the course was used disproportionately by learners from rural areas, those with less formal education, and those with lower prior knowledge, broadening participation among disadvantaged learners. Moreover, the availability of Leb Lango instruction was associated with higher active participation, even among learners who registered for English instruction. Although Leb Lango learners began with lower performance, they demonstrated faster learning gains and achieved comparable final examination outcomes to English and Hybrid learners. These results suggest that providing local language options to learners is an effective way to make EdTech more accessible.
Credit scoring is an increasingly central and contested domain of data and AI governance, frequently framed as a neutral and objective method of assessing risk across diverse economic and political contexts. Based on a nine-month ethnography of credit scoring practices in Nairobi, Kenya, we examined the sociotechnical and institutional work of data science in digital lending. While established regional telcos and banks are leveraging proprietary data to develop digital loan products, algorithmic credit scoring is being transformed by new actors, techniques, and shifting regulations. Our findings show how practitioners construct alternative data using technical and legal workarounds, formulate risk through multiple interpretations, and negotiate model performance via technical and political means. We argue that algorithmic credit scoring is accomplished through the ongoing work of alignment that stabilizes risk under conditions of persistent uncertainty, which takes epistemic, modeling, and contextual forms. Extending work on alignment in HCI, we show how alignment operates as a two-way translation, where models are made “safe for worlds” while those worlds are reshaped to be “safe for models.”
Generative AI is increasingly shaping social media dynamics and the production of viral content, particularly among younger audiences. One recent example is Italian Brainrot, a meme phenomenon characterized by AI-generated, surreal visuals and absurd narratives, which has rapidly gained popularity among adolescents. Despite its widespread presence online, little is known about how such AI-generated content is perceived by young users and communicated across generational lines. This study investigates the attitudes and perceptions of 89 adolescents aged 12-14 regarding Italian Brainrot and related content. Specifically, it addresses two research questions: (1) How do young adolescents perceive and engage with the Italian Brainrot phenomenon? and (2) How do they communicate about this content with peers and adults? Our findings contribute to broader discussions on generative AI, internet language, and intergenerational communication. In particular, we highlight both the barriers and opportunities for fostering critical awareness and responsible engagement with AI-driven media among youth.
Empathy is widely regarded as inherently positive in supportive online interactions, but its value is shaped by context. This study argues that empathy should be understood not as a uniform good but as a multidimensional, relational practice. Rather than treating empathy as binary, we propose a framework that captures how empathy is solicited in posts and expressed in replies, emphasising that context is critical in determining its appropriateness and effectiveness. Using post–reply data from six Reddit and Stack Exchange communities, we conduct a three-phase study. First, we develop a fine-grained annotation framework to capture distinct empathy practices in both posts and replies. Second, we fine-tune language models to detect these nuanced practices. Third, we apply the models at scale and examine platform- and community-specific patterns of empathy elicitation and expression. Our findings challenge current assumptions about online empathy and offer a more contextualised understanding of its role in online discourse. We identify future directions for platform design and contextual community support.
There is an increasing interest in telling serious stories with data. Designers organize information, construct narratives, and present findings to inform audiences. However, many of these practices emerge from modern information visualization rhetoric and ethical frameworks which may marginalize communities with low digital and media literacy. In a ten-month-long ethnographic study in three Bangladeshi villages, we investigated how these communities use entertainment and cultural practices, namely Puthi, Bhandari Gaan, and Pot music, to instruct, communicate traditional moral lessons and recall history. We found that these communities embrace polyvocality and multiple ethical frameworks in their performances, construct narratives combining factuality, emotionality, and aesthetics, and adapt their performances to changing technology and audience needs. Our findings provide HCI, visualization, and ethical data practitioners with implications for the design of accessible and culturally appropriate ways of presenting data narratives in data-driven systems.
This work brings cultural depth to Hybrid Craft research by exploring Tatreez (Palestinian Arab embroidery) as a medium for Indigenous interaction design. We conducted four participatory workshops with 23 Palestinian, Arab, and Muslim individuals, incorporating traditional hand-stitching, digital embroidery, and reflective interviews. We investigate how digital design and machine embroidery can support handmaking and enable interactive Tatreez with e-textiles that connect to digital archives for storytelling and remembrance. We present a sampler book with embroidered braille, conductive threads, and seamless touch-sensing, bridging cultural heritage and accessible interaction. Our qualitative analysis highlights design opportunities (including co-crafting with machines and multisensory interaction) and design considerations for HCI such as respecting collectivist participation modes, decolonizing Hybrid Craft, and making politics in diasporic and marginalized communities. This work expands Hybrid Craft in HCI beyond neutral and Western norms, foregrounding cultural pride while offering practical insights for conducting user studies with underrepresented groups.