arXiv subjects

Sharifa Sultana

Publications and source records attributed to Sharifa Sultana.

29 records · Page 2Linked to original sources

arXiv2026

"OpenBloom": A Question-Based LLM Tool to Support Stigma Reduction in Reproductive Well-Being

Reproductive well-being education remains widely stigmatized across diverse cultural contexts, constraining how individuals access and interpret reproductive health knowledge. We designed and evaluated OpenBloom, a stigma-sensitive, AI-mediated system that uses LLMs to transform reproductive health articles into reflective, question-based learning prompts. We employed OpenBloom as a design probe, aiming to explore the emerging challenges of reproductive well-being stigma through LLMs. Through surveys, semi-structured interviews, and focus group discussions, we examine how sociocultural stigma shapes participants' engagements with AI-generated questions and the opportunities of inquiry-based reproductive health education. Our findings identify key design considerations for stigma-sensitive LLM, including empathetic framing, inclusive language, values-based reflection, and explicit representation of marginalized identities. However, while current LLM outputs largely meet expectations for cultural sensitivity and non-offensiveness, they default to superficial rephrasing and factual recall rather than critical reflection. This guides well-being HCI design in sensitive health domains toward culturally grounded, participatory workflows.

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arXiv2026

Perception of Deepfakes among Bangladeshi Women

As deepfake technology becomes more accessible, concerns about its misuse and societal impact are escalating, particularly in regions like the Global South where digital literacy and regulatory measures are often limited. While previous research has explored deepfakes in contexts such as detection and media manipulation, there is a noticeable gap in understanding how individuals in these regions perceive and interact with deepfake media. This study addresses this gap by investigating how Bangladeshi women perceive deepfakes and the socio-cultural factors influencing their awareness, concerns, and responses to this technology. Drawing on 15 semi-structured interviews, we uncover how cultural values, gendered norms, trust in institutions, and the prevalence of digital harassment shape their perceptions and coping mechanisms. Through this research, we aim to advance existing scholarship in HCI by offering insights into the design of culturally sensitive interventions, educational initiatives, and policy frameworks to address the challenges posed by deepfakes in the Global South.

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arXiv2026

Bangladesh AI Readiness: Perspectives from the Academia, Industry, and Government

Artificial Intelligence (AI) readiness in the Global South extends beyond infrastructure to include curriculum design, workforce development, and cross-sector collaboration. Bangladesh, ranked 82nd in the 2023 Oxford Insights AI Readiness Index, exhibits significant deficits in technology capacity and research ecosystems, despite strong governmental visions. While HCI and ICTD research have explored digital inclusion and responsible AI, little empirical work examines how educational, industrial, and policy domains intersect to shape readiness. We present a multi-method qualitative study of AI readiness in Bangladesh, combining institutional analyses, 59 stakeholder interviews, and curriculum benchmarking against global exemplars. Findings reveal outdated curricula, limited faculty upskilling, inadequate computing resources, entrenched gender disparities, and the near-total absence of AI ethics instruction. We contribute empirical mapping of current practices, identification of structural and cultural barriers, and actionable pathways for embedding human-centered, inclusive, and responsible AI practices into national agendas, advancing equitable innovation in emerging AI ecosystems.

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arXiv2026

Re-educating Educated Ones: A Case Study on Chakma Language Revitalization in Chittagong Hill Tracts

Indigenous languages face significant cultural oppression from official state languages, particularly in the Global South. We investigate the Bangladeshi Chakma language revitalization movement, a community grappling with language liquidity and amalgamation into the dominant Bengali language. Our six-month-long qualitative study involving interviews and focus group discussions with Chakma language learning stakeholders uncovered existing community socio-economic challenges and resilience strategies. We noted the need for culturally grounded digital tools and resources. We propose an ICT-mediated community-centric framework for Indigenous language revitalization in the Global South, emphasizing the integration of historical identity elements, stakeholder-defined requirements, and effective digital engagement strategies to empower communities in preserving their linguistic and cultural heritage.

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arXiv2026

Job Anxiety in Post-Secondary Computer Science Students Caused by Artificial Intelligence

The emerging widespread usage of AI has led to industry adoption to improve efficiency and increase earnings. However, a major consequence of this is AI displacing employees from their jobs, leading to feelings of job insecurity and uncertainty. This is especially true for computer science students preparing to enter the workforce. To investigate this, we performed semi-structured interviews with (n = 25) students across computer science undergraduate and graduate programs at the University of Toronto to determine the extent of job replacement anxiety. Through thematic analysis, it was determined that computer science students indeed face stress and anxiety from AI displacement of jobs, leading to different strategies of managing pressure. Subfields such as software engineering and web development are strongly believed to be vulnerable to displacement, while specialized subfields like quantum computing and AI research are deemed more secure. Many students feel compelled to upskill by using more AI technologies, taking AI courses, and specializing in AI through graduate school. Some students also reskill by pursuing other fields of study seen as less vulnerable to AI displacement. Finally, international students experience additional job replacement anxiety because of pressure to secure permanent residence. Implications of these findings include feelings of low security in computer science careers, oversaturation of computer science students pursuing AI, and potential dissuasion of future university students from pursuing computer science.

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arXiv2025

Ghostcrafting AI: Under the Rug of Platform Labor

Platform laborers play an indispensable yet hidden role in building and sustaining AI systems. Drawing on an eight-month ethnography of Bangladesh's platform labor industry and inspired by Gray and Suri, we conceptualize Ghostcrafting AI to describe how workers materially enable AI while remaining invisible or erased from recognition. Workers pursue platform labor as a path to prestige and mobility but sustain themselves through resourceful, situated learning - renting cyber-cafe computers, copying gig templates, following tutorials in unfamiliar languages, and relying on peer networks. At the same time, they face exploitative wages, unreliable payments, biased algorithms, and governance structures that make their labor precarious and invisible. To cope, they develop tactical repertoires such as identity masking, bypassing platform fees, and pirated tools. These practices reveal both AI's dependency on ghostcrafted labor and the urgent need for design, policy, and governance interventions that ensure fairness, recognition, and sustainability in platform futures.

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arXiv2025

From Literature to ReWA: Discussing Reproductive Well-being in HCI

Reproductive well-being is shaped by intersecting cultural, religious, gendered, and political contexts, yet current technologies often reflect narrow, Western-centric assumptions. In this literature review, we synthesize findings from 147 peer-reviewed papers published between 2015 and 2025 across HCI, CSCW and social computing, ICTD, digital and public health, and AI for well-being scholarship to map the evolving reproductive well-being landscape. We identify three thematic waves that focused on early access and education, cultural sensitivity and privacy, and AI integration with policy-aware design, and highlight how technologies support or constrain diverse reproductive experiences. Our analysis reveals critical gaps in inclusivity, with persistent exclusions of men and non-binary users, migrants, and users in the Global South. Additionally, we surfaced the significant absence of literature on the role of stakeholders (e.g., husband and family members, household maids and cleaning helping hands, midwife, etc.) in the reproductive well-being space. Drawing on the findings from the literature, we propose the ReWA framework to support reproductive well-being for all agendas through six design orientations associated with: location, culture, and history; polyvocality and agency; rationality, temporality, distributive roles, and methodology.

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arXiv2025

DAIEM: Decolonizing Algorithm's Role as a Team-member in Informal E-market

In Bangladesh's rapidly expanding informal e-market, small-scale sellers use social media platforms like Facebook to run businesses outside formal infrastructures. These sellers rely heavily on platform algorithms, not just for visibility, but as active collaborators in business operations. Drawing on 37 in-depth interviews with sellers, buyers, and stakeholders, this paper examines how people in informal e-markets perceive and interact with the algorithm as a "team member" that performs sales, marketing, and customer engagement tasks. We found that while sellers and local tech entrepreneurs are interested in developing services to support this industry, buyers and investors place greater trust in human interactions. This reveals a postcolonial tension involving cultural values, local tech education and training, and a mismatch between the global and Bangladeshi e-market growth. We expand this discussion using perspectives from HCI, political design, and AI design. We also support the decoloniality movement in informal e-markets by proposing the DAIEM framework, which includes six components: autonomy and agency; resistance; locality, culture, and history; rationality; materiality; and advocacy. DAIEM serves as both a guideline for algorithm design and an analytical tool.

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arXiv2025

`Socheton': A Culturally Appropriate AI Tool to Support Reproductive Well-being

Reproductive well-being education in the Global South is often challenged as many communities perceive many of its contents as misinformation, misconceptions, and language-inappropriate. Our ten-month-long ethnographic study (n=41) investigated the impact of sociocultural landscape, cultural beliefs, and healthcare infrastructure on Bangladeshi people's access to quality reproductive healthcare and set four design goals: combating misinformation, including culturally appropriate language, professionals' accountable moderation, and promoting users' democratic participation. Building on the model of `\textit{Distributive Justice,}' we designed and evaluated \textit{`Socheton,'} a culturally appropriate AI-mediated tool for reproductive well-being that includes healthcare professionals, AI-language teachers, and community members to moderate and run the activity-based platform. Our user study (n=28) revealed that only combating misinformation and language inappropriateness may still leave the community with a conservative mob culture and patronize reproductive care-seeking. This guides well-being HCI design toward being culturally appropriate in the context of reproductive justice with sensitive marginalized communities.

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arXiv2025

Digital Labor: Challenges, Ethical Insights, and Implications

Digital workers on crowdsourcing platforms (e.g., Amazon Mechanical Turk, Appen, Clickworker, Prolific) play a crucial role in training and improving AI systems, yet they often face low pay, unfair conditions, and a lack of recognition for their contributions. To map these issues in the existing literature of computer science, AI, and related scholarship, we selected over 300 research papers on digital labor published between 2015 and 2024, narrowing them down to 143 on digital gig-labor for a detailed analysis. This analysis provides a broad overview of the key challenges, concerns, and trends in the field. Our synthesis reveals how the persistent patterns of representation and voices of gig workers in digital labor are structured and governed. We offer new insights for researchers, platform designers, and policymakers, helping them better understand the experiences of digital workers and pointing to key areas where interventions and future investigations are promptly needed. By mapping the findings from the past ten years' growth of the domain and possible implications, this paper contributes to a more coherent and critical understanding of digital labor in contemporary and future AI ecosystems.

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arXiv2025

Talking About the Assumption in the Room

The reference to assumptions in how practitioners use or interact with machine learning (ML) systems is ubiquitous in HCI and responsible ML discourse. However, what remains unclear from prior works is the conceptualization of assumptions and how practitioners identify and handle assumptions throughout their workflows. This leads to confusion about what assumptions are and what needs to be done with them. We use the concept of an argument from Informal Logic, a branch of Philosophy, to offer a new perspective to understand and explicate the confusions surrounding assumptions. Through semi-structured interviews with 22 ML practitioners, we find what contributes most to these confusions is how independently assumptions are constructed, how reactively and reflectively they are handled, and how nebulously they are recorded. Our study brings the peripheral discussion of assumptions in ML to the center and presents recommendations for practitioners to better think about and work with assumptions.

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