Human–Computer Interaction (HCI) scholarship has begun to examine religion and spirituality; yet, devotion as a lived, material, and world-making practice remains largely overlooked. For millions across the Global South, devotional labor such as sculpting, tending to, or worshipping sacred figures forms a primary mode of engaging with the divine and shaping everyday social and technological imaginations. Drawing on a four-month ethnography with an idol-maker community in Kumartuli, Kolkata, India, this paper examines how artisans bring gods into being through materials, gestures, obligation, and collective care. Their practices reveal forms of knowledge, intentionality, and agency that complicate HCI’s predominantly secular and instrumental understandings of craft, creativity, and technology. Building on anthropological craft studies, postcolonial computing, and scholarship on religion and materiality, we show how sacred making foregrounds relational, embodied, and cosmological dimensions of practice. We argue that devotional craft constitutes an under-recognized site from which HCI can critically rethink its assumptions about materiality, mediation, knowledge, and the sacred.

In rapidly digitizing countries, like India, many people are adopting the Internet for the first time through smartphones. Such new users, with little prior exposure to digital systems, face applications and services that access personal and private data, often leaving no agency with the users to exercise a choice. This creates an imbalance between the power of data-driven platforms and the limited digital literacy of users, raising urgent privacy and security concerns. While prior research has studied experienced Internet populations, far less is known about how first-time users in the emerging markets think about and act on privacy risks. We present findings from interviews with 50 new Internet users in India, spanning diverse social and economic backgrounds. Our study shows that privacy is often managed by family members and local intermediaries, with users depending on them for key decisions. Participants held incomplete or inaccurate understandings of data collection, while prioritizing visible threats like fraud and device theft. The findings reveal a mismatch between formal privacy controls and the realities of everyday practice. We outline design and policy directions to support consent and security in ways that reflect the experiences of new Internet users.

Design within digital platforms is rarely neutral.Rather, it is saturated with normative assumptions about sensory experiences and what constitutes "good" interaction.This paper engages What-sApp: a ubiquitous platform in India, as a site to interrogate how dominant design paradigms privilege sighted ways of knowing, sensing, and navigating the world.Drawing from critical disability studies, we examine how access for blind users is too often conceptualized as a matter of retrofitting: treated as a technical deficit to be repaired, rather than as a structural question of epistemic exclusion and sensory erasure.Through Roland Barthes' notion of myth, we argue that WhatsApp's interface naturalizes visual interaction as universal, rendering other modes: auditory, haptic, contextual, as secondary or supplemental.Through an interpretative phenomenological analysis (IPA) with blind WhatsApp users in India, we trace how the promise of access is frequently undermined by infrastructural precarity, shared device use, and screen-reader incompatibilities.Yet, rather than cast blind users as passive recipients of exclusion, we foreground their situated practices of navigation, interruption, resistance, and adaptation.This study resists calls for more efficient assistive add-ons and instead demands a reorientation of design thinking itself.To engage seriously with the politics of access, we must move beyond the visual logic of modularity and toward an ethic of multimodal, relational design, one attuned to the material, social, and sensory conditions of everyday life.In doing so, we contribute to a growing body of work that reclaims access not as accommodation [2,6,12], but as a transformative critique of what platforms take for granted, and who they leave behind.

This paper examines how ride-hailing drivers in Hyderabad, India, respond to the constraints of algorithmic management. Through interviews with 14 cab drivers we explore how workers navigate opaque systems, shifting incentives, and limited recourse. Drivers adopt informal tactics, such as offline rides , to regain autonomy. Many coordinate through WhatsApp groups or join grassroots cooperatives, which offer welfare support and collective bargaining. Some also engage in informal reintermediation by hiring others or managing small fleets. We contribute to CSCW by showing how global platform models are reshaped by local practices and informal infrastructures. Our findings highlight the need for transparent platform design, worker-led organising, and supportive policy in the Global South.

Despite rapid mobile and Internet penetration in India, e-commerce adoption remains slow among emergent users. In this paper, we conduct a mixed-method study involving a two-phase user study and an analysis of app reviews posted on app stores. The findings reveal that emergent users often replicate offline shopping behaviours in digital contexts, struggle with product search and filtering, and prefer cash-on-delivery due to distrust in online payments. Many users misinterpret rating systems and lack confidence in post-purchase processes, further deterring adoption. Our research underscores the need for intuitive design, clearer communication of platform features, and trust-building mechanisms to enhance user engagement with e-commerce. We propose design recommendations to make e-commerce platforms more accessible, addressing the specific needs of this user group.

Patriarchal practices and other socio-cultural norms in rural North India often prevent women from participating in digital platforms. In this paper we present a voice-based participatory community media platform that runs over simple voice-based phone calls. The platform is meant for women users and is led by women and has been used by 12,222 women users over the course of 20 months. We conduct a qualitative study and present several innovations, such as creating a safe space for women, which have contributed to more participation of women on the platform. We present a framework which can serve as a guidance for researchers and practitioners who want to set up digital platforms for women users.

Most online information sources are text-based and in Western Languages like English. However, many new and first time users of the Internet are in contexts with low English proficiency and are unable to access vital information online. Several researchers have focused on building conversational information systems over voice for this demographic, and also highlighted the importance of building trust towards the information source. In this work we develop four versions of a voice based chat-bot on the Google Assistant platform in which we vary the gender, friendliness and personalisation of the bot. We find that the users rank the female version of the bot with more personalisations over the others; however when rating the bots individually, the ratings depend on the ability of the bot to understand the users’ spoken query and respond accurately.

Policymakers often make decisions based on GDP, unemployment rate, industrial output, etc. The primary methods to obtain or estimate such information are resource-intensive. In order to make timely and well-informed decisions, it is imperative to come up with proxies for these parameters, which can be sampled quickly and efficiently, especially during disruptive events like the COVID-19 pandemic. We explore the use of remotely sensed data for this task. The data has become cheaper to collect than surveys and can be available in real-time. In this work, we present Regional GDP-NightLight (ReGNL), a neural network trained to predict GDP given the nightlights data and geographical coordinates. Taking the case of 50 US states, we find that ReGNL is disruption-agnostic and can predict the GDP for both normal years (2019) and years with a disruptive event (2020). ReGNL outperforms time-series ARIMA methods for prediction, even during the pandemic.

Video conferencing platforms have been appropriated during the COVID-19 pandemic for different purposes, including classroom teaching. However, the platforms are not designed for many of these objectives. When users, like educationists, select a platform, it is unclear which platform will perform better given the same network and hardware resources to meet the required Quality of Experience (QoE). Similarly, when developers design a new video conferencing platform, they do not have clear guidelines for making design choices given the QoE requirements.

The COVID-19 induced lockdowns forced people to shift several activities, including education, online. However, in the context of online schooling, the Digital Divides have magnified and perpetuated existing inequities in the education system and in society. Through a qualitative study with 48 participants across four stakeholder groups we find that students in under-funded government schools in India largely have not been able to access online classes because of a lack of devices, poor quality of Internet access, unreliable data networks and expensive data plans. We also document attempts by teachers and non-profit workers to use mass media broadcast technologies to work around the issue of digital access, highlighting the importance of a human infrastructure to build resilience during a disruptive event. Socioeconomic factors have also forced several students to drop out of schools and into taking up jobs to support their families. We document the importance of enabling environments and economic safety nets at home for online education to succeed. We present some focus points for researchers and policy makers working in the space of digital divide and education to build more resilient systems through Digital Welfarism.

Proliferation of “Fake News” and misinformation is resulting in widespread negative social fallout. Scalable Fake News classification techniques for resource poor languages like Hindi are in early stages because of a lack of datasets and lack of robust NLP libraries for these languages. In this exploratory study we curate a dataset of around 13,000 data points of true news articles, and, articles on fake news authored by media organisations which flag fake news. We then use seven ML classification models on this dataset and present the preliminary results. Our results show that concerted efforts need to be made by the research community towards dataset curation and improving the NLP models for resource poor languages in order to make scalable classification systems.

The design of participatory media platforms can have many variations in terms of whether or not anonymous communication is allowed, what moderation policies are in use, the conversation model that is supported, etc. We use six case-studies of voice-based ICT4D participatory media platforms running in India to outline a typology of design axes that can be used to characterize these platforms. Such typologies can be useful for ICT4D practitioners to conceptualize suitable designs for their platforms in different contexts, and to reconfigure the platforms in case design changes are required. We also use this typology to discuss the design constraints and flexibilities allowed by Internet based social media platforms.

Social and behaviour change communication interventions are believed to gain from using mobile technology owing to the reach and rapid scaling promise of technology. In this paper we describe our experiences from the layering of an IVR based content platform for behaviour change in maternal and child nutrition practices in the state of Bihar in rural central India. We specifically show that being able to leverage technology effectively can be quite complex and needs a careful implementation design. We demonstrate that technology adoption takes time and has to be encouraged through offline mechanisms. We also demonstrate that diversification of content on the IVR platform can facilitate greater usage of the platform. We outline the technology assisted concurrent monitoring methods developed by us, and how the data analysis helps identify gaps to take timely corrective action. Finally, we discuss the pros and cons of different pathways to reach women users in rural areas. The insights derived from our work can serve as guidelines for designing technology-based behaviour change campaigns.

Social welfare schemes and public infrastructure services often face implementation and last mile delivery challenges. Governments in India have set up phone helplines for beneficiaries to report irregularities but we find that it remains challenging for beneficiaries to realise positive outcomes through these helplines; without a personal follow-up with the concerned local government officials by experienced members from the civil society, the redressals done are often inadequate. To combine the scalability of centralised helplines with the effectiveness of decentralised mediation by civil society groups, we set up an IVR (Interactive Voice Response) system where beneficiaries can record their grievances, which are then delegated to a network of civil society volunteers who do the required local follow-ups for resolution of these grievances. Through this pilot, we analysed over 200 cases of redressal and document how volunteer networks operate and can plug accountability gaps in government services. We advocate for formalisation of this civil-society mediated and technology assisted model into the design of public welfare schemes to enable citizens to engage with government departments in productive ways.

Citizen feedback on the implementation of social welfare schemes can help fine tune their design, understand problems, and assess the benefits and impact from these schemes. Such feedback loops however are singularly missing in most schemes in India, and are conveyed only indirectly via civil society and social audit organisations that try to serve as a bridge between citizens and the government. We leverage the deep penetration of mobile phones in India to design a suite of IVR (Interactive Voice Response) tools that can help capture community perceptions, improve awareness of the people, and verify official records directly by the beneficiaries themselves. In the context of a rural employment guarantee scheme, we evaluate these tools in a few villages in the state of Haryana and demonstrate that there is good scope for using IVR tools to serve as a citizen engagement channel for welfare schemes. Our contribution lies in outlining several use-cases for technology interventions, and uncovering nuances that should be addressed if such systems are integrated into the implementation of social welfare schemes.

Activist groups have taken up information dissemination and feedback collection as a means of rights advocacy in India. However, it is not easy given the difficulty in procuring and disseminating information at a large scale. Beneficiaries are often not able to help themselves as information systems are administration facing, because of poor literacy and the inability to access the Internet. Further, beneficiaries are not well informed of their rights and entitlements under different government schemes to know how and when to file grievances. We aim to solve these problems by designing and testing prototypes for information dissemination and feedback collection in various contexts. In our current prototype we describe an automated tool that sifts through the data on an MIS and conveys personalised information to the beneficiaries through voice calls. This is a work in progress, and our first exercise on providing MIS-extracted information to people through phone calls led to 70% of the beneficiaries who noticed a discrepancy in the data to agree to file a grievance on their behalf. We are continuing to scale the work, make it more automated, and run qualitative interviews with all stakeholders to understand causality linkages with transparency led grievance filing, assisted by appropriate ICTs, to increase accountability.