Tom Yeh

This paper reports findings from four AI literacy workshops conducted with secondary school teachers in Ibadan and Abuja, Nigeria. The workshops introduced foundational AI concepts through interactive lectures, hands-on activities, and group discussions designed for settings with limited digital infrastructure. Teachers expressed interest in integrating AI concepts into their classrooms but identified persistent constraints, including unreliable electricity and internet access, limited device availability, and the absence of locally relevant AI materials. We found that low-tech, analog activities, such as AI-by-hand exercises, supported conceptual understanding without requiring computational tools. Drawing on these findings, we propose a framework for designing AI literacy programs in resource-constrained educational contexts, with attention to infrastructural limitations and sustained teacher support through communities of practice.

Evaluating personalized, sequential treatment strategies for Alzheimer's disease (AD) using clinical trials is often impractical due to long disease horizons and substantial inter-patient heterogeneity. To address these constraints, we present the Alzheimer's Learning Platform for Adaptive Care Agents (ALPACA), an open-source, Gym-compatible reinforcement learning (RL) environment for systematically exploring personalized treatment strategies using existing therapies. ALPACA is powered by the Continuous Action-conditioned State Transitions (CAST) model trained on longitudinal trajectories from the Alzheimer's Disease Neuroimaging Initiative (ADNI), enabling medication-conditioned simulation of disease progression under alternative treatment decisions. We show that CAST autoregressively generates realistic medication-conditioned trajectories and that RL policies trained in ALPACA outperform no-treatment and behavior-cloned clinician baselines on memory-related outcomes. Interpretability analyses further indicated that the learned policies relied on clinically meaningful patient features when selecting actions. Overall, ALPACA provides a reusable in silico testbed for studying individualized sequential treatment decision-making for AD.

Portrayals of intelligent technologies and smart devices are becoming increasingly common in narrative media, such as novels, video games, and movies, targeted at children and teenagers. This media can shape children's understanding of technology and potentially inform how interact in a society increasingly influenced by artificial intelligence (AI) and machine learning (ML). In this work we seek to understand the potential benefits and limitations of these depictions by examining narrative media that portray intelligent technologies through an educational lens. We crafted systematic summaries of 64 examples of such media and used them as the basis for an interdisciplinary workshop involving nine subject matter experts from varying fields of education and technology. The workshop yielded insights regarding the qualities of these depictions; in particular our findings allowed us to draw important implications about how narrative depictions of intelligent technologies could be applied in K-12 education in ML and AI.

Creative storytelling with parents plays an important role in child development including language skills, social competence, and emotional understanding. Recognizing the challenges parents face in finding time for storytelling due to work and home responsibilities, we explore the feasibility of ChatGPT for engaging children in creative storytelling. This study investigates the use of ChatGPT, a conversational agent powered by GPT-4, in creative storytelling with children aged 5-6, comparing its interaction styles with those of parents. The current study included eight child-parent dyads. We found that children were engaged in shorter and more frequent interactions with parents compared to ChatGPT. ChatGPT and parents asked different types of questions, and ChatGPT more frequently provided positive feedback compared to parents. More children selected the interactions with ChatGPT as their favorite interactions. The study provides preliminary evidence on ChatGPT's interaction styles and insights into its potential role in supporting families in creative storytelling activities.

The field of Artificial Intelligence (AI) is leading transformative impacts across different sectors. However, these advancements are often developed with a Western-centric focus, neglecting the cultural diversity in regions such as the Global South. In this paper, we synthesize twelve research papers focusing on cultural considerations in designing AI systems for the Global South. Our findings revealed a significant focus on domains like healthcare and intelligent assistants and challenges, including usability, AI transparency, and data availability, that can hinder the design and deployment of culturally sensitive AI systems. Moreover, the results demonstrated the need to integrate cultural values to increase the acceptance and usefulness of AI systems for regions in the Global South. This paper guides future research towards developing culturally and contextually relevant AI systems for Africa, highlighting the need for increased visibility and representation of African researchers in HCI and AI domains.

This article examines the ways secondary computer science and English Language Arts teachers in urban, suburban, and semi-rural schools adapted a project-based AI ethics curriculum to make it better fit their local contexts. AI ethics is an urgent topic with tangible consequences for youths’ current and future lives, but one that is rarely taught in schools. Few teachers have formal training in this area as it is an emerging field even at the university level. Exploring AI ethics involves examining biases related to race, gender, and social class, a challenging task for all teachers, and an unfamiliar one for most computer science teachers. It also requires teaching technical content which falls outside the comfort zone of most humanities teachers. Although none of our partner teachers had previously taught an AI ethics project, this study demonstrates that their expertise and experience in other domains played an essential role in providing high quality instruction. Teachers designed and redesigned tasks and incorporated texts and apps to ensure the AI ethics project would adhere to district and department level requirements; they led equity-focused inquiry in a way that both protected vulnerable students and accounted for local cultures and politics; and they adjusted technical content and developed hands-on computer science experiences to better challenge and engage their students. We use Mishra and Kohler’s TPACK framework to highlight the ways teachers leveraged their own expertise in some areas, while relying on materials and support from our research team in others, to create stronger learning experiences.

This paper presents a new approach to engaging children in Nigeria to share their views of AI. This approach is centered on an inclusive writing contest for children in a secondary school in Abuja to write about AI to compete for prizes and share their writings with others. A preliminary analysis of the first 11 articles we received exhibits diverse gender and ethnic representation that conveys cultural values and perspectives distinct from those of the children in Western countries. This finding suggests future work to conduct an in-depth cross-cultural analysis of the articles and to replicate similar writing contests to engage children in other underrepresented countries.