Abstract

From an study of food delivery workers, we examine the precarity and consolidation of working conditions driven by the platform economy in the context of Urban India. The study considers the apparent threats in ‘gigging’, informalisation of labour and the obvious need to reconceptualise worker well-being, risks, stress and the eventuality of workplace and worker alignment in food delivery labour.

Abstract

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Abstract

The evolving landscape of gig labor, particularly within food delivery platforms, has been influenced by a shift towards algorithmic management, emphasizing performance metrics as a daily burden to be carried through delivery work. Through a study of Indian food delivery agents, our paper suggests an emerging gamification culture between delivery platforms and workers. Agents gradually yet consistently adapt to stringent algorithmic management to overcome everyday work's precarity. Despite the challenges of performance pressure on food delivery labor, we capture the daily rhythms and routines of delivery work punctuated by flashes of agenting, revealing small capacities to make choices and influence work outcomes. By employing a qualitative research framework, we uncover the mechanisms through which delivery platforms manipulate labor, simultaneously exploring delivery agents' tactics to extract agency and exploit the platforms' rules. We develop the notion of 'agency’ to disentangle the idea of `gamification by agents’ as a socio-technical derivative governing food delivery agents in urban India. The findings highlight the potential of platform work empowering, albeit with limits, delivery agents with agency and decision-making authority.

Abstract

Anti-discrimination represents a critical area of study for researchers, policymakers, and designers of technical systems. Drawing on AI fairness and inclusion studies research, we analyse algorithmic bias and their propensity to reproduce bias [Selbst et al., 2019] on two types of platforms- a gaming environment and a dating platform. On the gaming platform we conduct research on toxicity to comprehend its manifestations, diverse interpretations of toxicity, the conditions fostering toxic gaming, specifically affecting gendered identities. We also investigate if toxic behaviours are normalised within gaming domains, adversely impacting gendered perceptions and experiences. For the second platform, we offer results from an experiment on the Bumble dating platform to identify and address the presence of discrimination in the matching algorithms the platform pushes to its users in the form of profiles for potential dates in the real world. Forms of Interactions of user discovery pose a significant risk of sexual violence and other forms of harm for diverse communities of gender on dating platforms. By reporting experiences of non-binary individuals using dating platforms we contribute to a largely unexplored research field. This study not only highlights the discrepancies and potential biases in dating algorithms but also serves as a catalyst to foster more inclusive design principles, thereby acknowledging the diverse needs across genders and communities.

Abstract

AI is about learning algorithms and huge amounts of data and are drivers of economic growth -- what does this mean for the field of development studies? Can we re-orient to twin AI studies and development theory and practice to generate how development challenges are identified and researched? To do this a good grasp is needed of AI internal mechanisms and outcomes in addressing development issues -- this argument will be developed through a case study of the ADAS [Advanced Driver Assistance System] deployment in India. Over and above discussing the ADAS we bring an anthropological lens to understand the social context that surrounds the system. Focusing on bus drivers, we offer findings from a qualitative and ethnographic study of drivers in a collaborative effort to achieve road safety by deploying AI-driven technology and empowering stakeholders in the transport industry in India especially, bus drivers as critical actors in the city transport network.

Abstract

We study bias and discrimination in the context of Bumble, an online dating platform in India. Drawing on research in AI fairness and inclusion studies we analyze algorithmic bias and their propensity to reproduce bias. We conducted an experiment to identify and address the presence of bias in the matching algorithms Bumble pushes to its users in the form of profiles for potential dates in the real world. Dating apps like Bumble utilize algorithms that learn from user data to make recommendations. Even if the algorithm does not have intentions or consciousness, it is a system created and maintained by humans. We attribute moral agency of such systems to be compositely derived from algorithmic mediations, the design and utilization of these platforms. Developers, designers, and operators of dating platforms thus have a moral obligation to mitigate biases in the algorithms to create inclusive platforms that affirm diverse social identities.

Abstract

The COVID-19 pandemic required efficient allocation of public resources and transforming existing ways of societal functions. To manage any crisis, governments and public health researchers ex-ploit the information available to them in order to make informed decisions, also defined as situational awareness. Gathering situational awareness using so-cial media, has been functional to manage epidemics. Previous research focused on using discussions during periods of epidemic crises on social media platforms like Twitter, Reddit, or Facebook and developing NLP techniques to filter out important/relevant discussions from a huge corpus of messages and posts. Social media usage varies with internet penetration and other socio-economic factors, which might induce disparity in an-alyzing discussions across different geographies. How-ever, print media is a ubiquitous information source, irrespective of geography. Further, topics discussed in news articles are already ‘newsworthy’, while on social media ‘newsworthiness' is a product of techno-social processes. Developing this fundamental difference, we study Twitter data during the second wave in India focused on six high-population cities with varied macro-economic factors. Through a mixture of qualitative and quantitative methods, we further analyze two Indian newspapers during the same period

Abstract

Resilience in Acute Contexts

Abstract

witter played a dominant role during the 2014 general elections in India, ushering a right-wing party into power. Political leaders employed Twitter to augment their public image and push right-wing campaign agendas to millions of followers. A prominent and strategic use of Twitter was credited to Prime Ministerial candidate Narendra Modi, portrayed as a visionary leader supporting economic development, social empowerment and good governance. Within this narrative, women's empowerment debates underwent multiple transformations. Through this article, we aim to establish the nature of discussions lying at the intersections of feminist thinking and internet technology. We study the discursive trajectory of women's empowerment against the backdrop of a right-wing political (Hindutva) ideology playing out on Twitter. Utilising the qualitative methods of Thematic Analysis and Feminist Relational Discourse …

Abstract

Now you can pursue world class courses on Indian soil… we are grooming a new generation of global Indians.… Join now and be the best.(A ‘computer institute’brochure in small town India) India’s large under-twenty-five adult population has stoked huge demand for technical, IT job-ready education. India is home to the largest undertwenty-five demographic profile in the world, 604,394,787 people and 49.91 per cent of the total population (Census, 2011), requiring a