Blind people use visual assistance technologies (VAT) to access visual information, yet VAT can expose blind people to privacy risks.Prior HCI research has studied and built AI-enabled obfuscation techniques to detect and remove private content.However, blind people cannot easily spot errors in obfuscation tools.Our paper explores how assessment descriptors, brief visual attributes of objects, may enable blind people to find errors.By conducting interviews and focus groups with blind participants, we found that certain assessment descriptors (color, dimensions, distance) are inadequate to support blind people.Instead, participants discussed assessment descriptors that better reflect their sensemaking process, such as describing multiple objects in a particular space.Expanding the scope of accessible verification beyond assessment descriptors, participants called for greater transparency on how AI-enabled privacy techniques are developed and emphasized the need to co-create training materials on using AI-enabled privacy techniques.Building from our findings and disability studies scholarship, our paper examines how sighted bias could produce assessment descriptors that neglect the needs of blind people and analyzes how participants' preferred assessment descriptors contrast with existing standards of visual description.Lastly, we offer design directions to push for greater transparency in VAT and obfuscation tools.

A growing body of research investigates how to make captioning experiences more accessible and enjoyable to disabled people. However, prior work has focused largely on English captioning, neglecting the majority of people who are multilingual (i.e., understand or express themselves in more than one language). To address this gap, we conducted semi-structured interviews and diary logs with 13 participants who used multilingual captions for accessibility. Our findings highlight the linguistic and cultural dimensions of captioning, detailing how language features (scripts and orthography) and the inclusion/negation of cultural context shape the accessibility of captions. Despite lack of quality and availability, participants emphasized the importance of multilingual captioning to learn a new language, build community, and preserve cultural heritage. Moving toward a future where all ways of communicating are celebrated, we present ways to orient captioning research to a language justice agenda that decenters English and engages with varied levels of fluency.

Blind people use artificial intelligence-enabled visual assistance technologies (AI VAT) to gain visual access in their everyday lives, but these technologies are embedded with errors that may be difficult to verify non-visually. Previous studies have primarily explored sighted users’ understanding of AI output and created vision-dependent explainable AI (XAI) features. We extend this body of literature by conducting an in-depth qualitative study with 26 blind people to understand their verification experiences and preferences. We begin by describing errors blind people encounter, highlighting how AI VAT fails to support complex document layouts, diverse languages, and cultural artifacts. We then illuminate how blind people make sense of AI through experimenting with AI VAT, employing non-visual skills, strategically including sighted people, and cross-referencing with other devices. Participants provided detailed opportunities for designing accessible XAI, such as affordances to support contestation. Informed by disability studies framework of misfitting and fitting, we unpacked harmful assumptions with AI VAT, underscoring the importance of celebrating disabled ways of knowing. Lastly, we offer practical takeaways for Responsible AI practice to push the field of accessible XAI forward.

Existing visual assistive technologies are built for simple and common use cases, and have few avenues for blind people to customize their functionalities. Drawing from prior work on DIY assistive technology, this paper investigates end-user programming as a means for users to create and customize visual access programs to meet their unique needs. We introduce ProgramAlly, a system for creating custom filters for visual information, e.g., ‘find NUMBER on BUS’, leveraging three end-user programming approaches: block programming, natural language, and programming by example. To implement ProgramAlly, we designed a representation of visual filtering tasks based on scenarios encountered by blind people, and integrated a set of on-device and cloud models for generating and running these programs. In user studies with 12 blind adults, we found that participants preferred different programming modalities depending on the task, and envisioned using visual access programs to address unique accessibility challenges that are otherwise difficult with existing applications. Through ProgramAlly, we present an exploration of how blind end-users can create visual access programs to customize and control their experiences.

The privacy dimensions of accessibility technologies are often understudied and overlooked. Very little prior research has investigated the privacy concerns of disabled people, and much less has studied the barriers of privacy-preserving techniques. In order to address this gap and bridge between two separate communities (accessibility and privacy), our one-day workshop explores how researchers might design and build technologies that are both accessible and privacy-preserving.

Workplaces around the globe are beginning to rapidly adopt hybrid meetings to conduct, plan, and organize their work. While previous literature explores the benefits and drawbacks of hybrid meetings, the experiences of professionals with disabilities are largely missing. With an orientation towards an accessible future of work, we interviewed 21 professionals with disabilities to unpack the accessibility barriers, opportunities, and conflicts of hybrid meetings. We highlight the creative ways professionals with disabilities developed workarounds and repairs to these accessibility tensions. Our paper expands the understanding of accessibility in hybrid meetings by identifying how the visibility of access labor may be affected by being in the room together with other colleagues or joining remotely. We also observed how hybrid configurations can require navigating accessibility conflicts specific to the location site of each participant. Building from our analysis, we offer practical suggestions and design directions to make hybrid meetings accessible.

Existing assistive technologies (AT) often fail to support the unique needs of blind and visually impaired (BVI) people. Thus, BVI people have become domain experts in customizing and ‘hacking’ AT, creatively suiting their needs. We aim to understand this behavior in depth, and how BVI people envision creating future DIY personalized AT. We conducted a multi-part qualitative study with 12 blind participants: an interview on unique uses of AT, a two-week diary study to log use cases, and a scenario-based design session to imagine creating future technologies. We found that participants work to design new AT both implicitly through creative use cases, and explicitly through regular ideation and development. Participants envisioned creating a variety of new technologies, and we summarize expected benefits and concerns of using a DIY technology approach. From our results, we present design considerations for future DIY technology systems to support existing customization and ‘hacking’ behaviors.

Clustering researchers in communities is an important task to support a range of techniques for analyzing and making sense of the research environment and helps re-searchers find people in the same field of interest to collaborate. In computer science, ontology is commonly used to capture knowledge about a particular area using relevant concepts and relations. This study investigates the use of overlapping community detection algorithms on a multilayered Arabic scholarly network to detect communities of researchers who share their research interests. Two researchers can share an interest if they co-authored a publication or share some keywords in their publications. The set of keywords is expanded via semantic search within a cross-domain ontology, e.g. DBpedia, allowing more researchers with indirect relationships to be connected. A 2-layer scholarly network was constructed by retrieving the scholarly data of faculty members from three colleges at Umm AlQura University (UQU) with rich Arabic publications. Four versions of this network were tested: unweighted, weighted, semantically expanded, and reduced semantically expanded. It was found that weights have an insignificant role in community detection within this study. In addition, a semantically expanded network does have better clustering potentials but only if was performed selectively. Otherwise, the expanded network might suffer from generic and non-discriminative keywords, making the community detection task more challenging. To our knowledge, this is the first investigation into detecting communities within an Arabic scholarly network.

Blind and low vision people use visual description services (VDS) to gain visual interpretation and build access in a world that privileges sight. Despite their many benefits, VDS have many harmful privacy and security implications. As a result, researchers are suggesting, exploring, and building obfuscation systems that detect and obscure private or sensitive materials. However, as obfuscation depends largely on sight to interpret outcomes, it is unknown whether Blind and low vision people would find such approaches useful. Our work aims to center the perspectives and opinions of Blind and low vision people on the potential of obfuscation to address privacy concerns in VDS. By reporting on interviews with 20 Blind and low vision people who use VDS, our findings reveal that popular research trends in obfuscation fail to capture the needs of Blind and low vision people. While obfuscation might be helpful in gaining more control, tensions around obfuscation misrecognition and confirmation are prominent. We turn to the framework of interdependence to unpack and understand obfuscation in VDS, enabling us to complicate privacy concerns, uncover the labor of Blind and low vision people, and emphasize the importance of safeguards. We provide design directions to move the trajectory of obfuscation research forward.

Social media platforms aspire to create online experiences where users can participate safely and equitably. However, women around the world experience widespread online harassment, including insults, stalking, aggression, threats, and non-consensual sharing of sexual photos. This article describes women's perceptions of harm associated with online harassment and preferred platform responses to that harm. We conducted a survey in 14 geographic regions around the world (N = 3,993), focusing on regions whose perspectives have been insufficiently elevated in social media governance decisions (e.g. Mongolia, Cameroon). Results show that, on average, women perceive greater harm associated with online harassment than men, especially for non-consensual image sharing. Women also prefer most platform responses compared to men, especially removing content and banning users; however, women are less favorable towards payment as a response. Addressing global gender-based violence online requires understanding how women experience online harms and how they wish for it to be addressed. This is especially important given that the people who build and govern technology are not typically those who are most likely to experience online harms.