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People with disabilities experience high levels of social discrimination worldwide. But, these harms are more pronounced in the Global South due to the intense stigma around disability and its intersections with structural embeddings of patriarchy. The massive growth of social media in the Global South provides people with disabilities a unique opportunity to advocate for disability rights and challenge regressive ableist norms. Yet, little is known about the challenges they face in doing their advocacy work on social media. Through interviews with 20 disability advocates in India with diverse gender identities and abilities, we found that disability advocates routinely face ableist hate and harassment, patronizing and invalidating comments, and lack of visibility and support, which forces them to self-censor as a form of self-protection, leading to low advocacy outcomes. We draw on these findings to illuminate the role of social media in the invisibilization of people with disabilities in the online sphere.
Non-Consensual Image-Disclosure Abuse (NCIDA) represents a subset of technology-facilitated sexual abuse where imagery and video with romantic or sexual connotations are used to control, extort, and otherwise harm victims. Despite considerable research on NCIDA, little is known about them in non-Western contexts. We investigate NCIDA in Pakistan, through interviews with victims, their relatives, and investigative officers; and observations of NCIDA cases being processed at a law enforcement agency. We find, first, that what constitutes NCIDA is much broader in Pakistan's patriarchal society, and that its effects can be more severe than in Western contexts. On every dimension -- types of content, perpetrators, impact on victims, and desired response by victims -- our findings suggest an expansion of the concepts associated with NCIDA. We conclude by making technical and policy-level recommendations, both to address the specific context of Pakistan, and to enable a more global conception of NCIDA.
The pandemic has contributed to the increased digital content development for remote experiences. Notably, museums have begun creating virtual exhibitions using 360-videos, providing a sense of presence and high level of immersion. However, 360-video content often uses a linear timeline interface that requires viewers to follow the path decided by the video creators. This format limits viewers’ ability to actively engage with and explore the virtual space independently. Therefore, we designed a map-based video interface, Viewer2Explorer, that enables the user to perceive and explore virtual spaces autonomously. We then conducted a study to compare the overall experience between the existing linear timeline and map interfaces. Viewer2Explorer enhanced users' spatial controllability and enabled active exploration in virtual museum exhibition spaces. Additionally, based on our map interface, we discuss a new type of immersion and assisted autonomy that can be experienced through a 360-video interface and provide design insights for future content.
AI technologies are increasingly deployed to support community health workers (CHWs) in high-stakes healthcare settings, from malnutrition diagnosis to diabetic retinopathy. Yet, little is known about how such technologies are understood by CHWs with low digital literacy and what can be done to make AI more understandable for them. This paper examines the potential of explorable explanations in improving AI understanding for CHWs in rural India. Explorable explanations integrate visual heuristics and written explanations to promote active learning. We conducted semi-structured interviews with CHWs who interacted with a design probe in which AI predictions of child malnutrition were accompanied by explorable explanations. Our findings show that explorable explanations shift CHWs' AI-related folk theories, help develop a more nuanced understanding of AI, augment CHWs' learning and occupational capabilities, and enhance their ability to contest AI decisions. We also uncover the effects of CHWs' sociopolitical environments on AI understanding and argue for a more holistic conception of AI explainability that goes beyond cognition and literacy.