Language operates as a mechanism of both marginalization and resistance, especially for minority communities navigating insensitive and harmful speech online. As content moderation increasingly depends on large language models (LLMs), concerns arise about whether these systems can recognize culturally insensitive speech–language that disregards or marginalizes the cultural and religious perspectives of historically underrepresented communities, often through implicit erasure, misrepresentation, or normative framing, rather than overt hostility. Focusing on Bangladesh’s Hindu and Chakma communities – the country’s largest religious and Indigenous ethnic minorities, respectively – this paper investigates the epistemic limits of LLM-based moderation systems and explores methods for incorporating minority perspectives. We co-created a culturally grounded corpus of insensitive speech with community members and integrated their narratives into moderation pipelines using retrieval augmented generation (RAG). Our tool, Mod-Guide, improves LLM sensitivity to minority viewpoints by leveraging contextual cues derived from lived experience. Through mixed-method evaluations involving both minority and majority participants, we demonstrate that RAG-enhanced moderation responses are more contextually accurate and perceived differently across ethnic lines. This work advances research in human-computer interaction, AI ethics, and social computing by foregrounding restorative justice and hermeneutical inclusion in the design of content moderation systems.

Sustainable Development Goals are currently universal objectives in all domains of engineering. Nevertheless, design for this global mission is exceedingly intricate and nearly surpasses the limits of human capability. Industrial and academic communities have devoted considerable of effort to developing new technologies, such as artificial intelligence (AI), as new design tools. Generative AI is the latest advancement among these tools, which can empower human designers with its capability to process massive amount of data from diverse sources and recast it in a comprehensible form. Despite the heated discussion on the relationship between creative innovation and frontier technologies, little attention has been paid to empowering young designers with the new skills of the AI era. Therefore, this study conducted a two-week design workshop to explore the interaction between generative AI tools and novice designers, especially in shaping their AI self-efficacy and design thinking process of novice designers.

University libraries are increasingly incorporating technological advances to increase productivity and participation among users. Today, using university libraries in a smart way is very important for our modern and innovative minds. In such contexts, presents the design-based research strategy for the creation of a guide robot which has been customized to suit the specific library needs of universities. Through detailed surveys with students and librarians, we set out to establish core design features and functional requirements that allow the robot to be as efficient as possible in carrying out the tasks of assisting users locate materials, answering questions, and developing user-library relations. This stage of iterative design development focuses on the statistical data collected throughout the processes, indicating that the design finalized at this level is ideal for users. The purpose of the study was to create interactive participation, access to real-time data in the robot framework, and improve user experience, library workflows, and usability. The results of this research are important for improving the human-robot interaction, which can be extended in the education environment, providing a customized and flexible approach for other academic or public service institutions. This research aims to contribute to the growing discourse on robotics in education by proposing a practical, data-driven solution to improve the functionality and responsiveness of modern university libraries.

While content moderation in online platforms marginalizes users in the Global South at large, users of certain identities are further marginalized. Such users often come from Indigenous ethnic minority groups or identify as women. Through a qualitative study based on 18 semi-structured interviews, this paper explores how such users' experiences with hate speech online in Bangladesh are shaped by their intersectional identities. Through a civics-oriented approach, we examined the spectrum of their legal status, membership, rights, and participation as users of online platforms. Drawing analogies with the concept of citizenship, we develop the concept of usership that offers a user-centered metaphor in studying moderation and platform governance.

For thousands of years in the history of our human society, people are inevitably segregated by long-distances. No matter whatever the reasons are, due to working, studying, visiting, traveling, or even the self-isolations as a result enforced by pandemic diseases, we are always separated with our closest friends, families and/or loved ones all the times in our life. There are no effective ways to bond us all together while we are away from each other. REmotion is an ergonomic, sleek, and human-centered non-invasive neurohaptic interface that turns human emotion brain signals into physical touch stimulations and synthetic images. It allows "speech-free", "typing-free" remote communications with your friends by direct brain-to-brain telepathy. While wearing our earbud-like simple brain-computer interface and the robotic haptic suit/armband, the developed BCI biosensing algorithms can interpret EEG signals, and the deep Generative Adversarial Network (GAN) will translate the "feelings of missing someone" into perceivable images and haptic sensations conveyed remotely to your friends. This method provides on-the-fly telepathy and peaceful feelings when people are segregated from their families, close friends, or loved ones. The only thing they have to do is by just thinking "I miss you", without additional fumbling of speaking on the cellphones, using hands to open the Apps or typing text messages in order to communicate with each other.

This paper presents the design, control and expressive capabilities of RoboQuin-a novel humanoid social robot. Although social robots have become more human-friendly, their capacity for naturalistic human behavior remains relatively limited. We implement an interdisciplinary design method to create a realistic and natural humanoid robot, with accurate body proportions and smooth motion coordination, and the ability to perform nonverbal communication. With this design, we aim to explore the impact of robot body design and dynamic robot postures on human perception towards robots.