Beyond Disruption and Invisibility: Evaluating Everyday AI Use in India
Key information
- Date
- Time
-
1:00 pm
- Venue
- SOAS, University of London
- Room
- Wolfson Lecture Theatre (Paul Webley Wing)
About this event
Though AI quietly powers much of India's daily digital life, it's rarely named - while national narratives celebrate transformation. This talk explores how users actually experience AI as a functional aid, not a revolution.
Though social media platforms mediate much of daily communication in India, embedded AI features are rarely labeled as AI (Behera & Gartia, 2024; Fahad et al., 2023), reinforcing its role as an infrastructural background. At the same time, the Prime Minister’s national discourse frames Generative AI (GenAI) as transformative (Wang & Downey, 2025). Yet sectoral evidence shows incremental augmentation rather than systemic overhaul: in education, capacity and uptake limits constrain deployment (Karan & Angadi, 2025); in healthcare, AI expands coverage and diagnostics without replacing existing systems (Bajpai & Wadhwa, 2021); while implementation across domains is conditioned by linguistic diversity, training-data bias, and digital inequalities (Khalid et al., 2025). Therefore, India is depicted as a platform-first environment where embedded AI is used every day but rarely named, and standalone GenAI is layered onto these routines as a visible assistant, even as national “transformation” narratives persist. Using 28 semi-structured interviews with employees at an office in South India, we use a grounded theory approach to identify thematic patterns. We found that participants recognized standalone GenAI more readily than embedded AI, but explicit naming mainly followed interface packaging rather than actual frequency of use. Our findings show that users tended to engage AI tools as functional aids rather than disruptive or invisible technologies.
About the Speaker
Dhiraj Murthy a Professor of Journalism and Media Studies (in the Moody College of Communication), Sociology (by courtesy), and School of Information (by courtesy). He earned his Ph.D. in Sociology from University of Cambridge
His research explores social media, digital research methods, race/ethnicity, qualitative/mixed methods, big data quantitative analysis, diversity and community inclusion, and virtual organizations. Dr. Murthy has edited 3 journal special issues and authored over 80 articles, book chapters, and papers. Murthy wrote the first scholarly book about Twitter (second edition published by Polity Press, 2018). He has been funded by the National Institutes of Health, National Institute of Minority Health & Health Disparities, National Science Foundation, and by Good Systems at the University of Texas at Austin.
Dr. Murthy founded and directs the Computational Media Lab at UT Austin, a large lab with over 20 graduate and undergraduate students (and several high school interns). He is co-editor of the high impact journal Big Data & Society (IF=8.731). Dr. Murthy has chaired and co-chaired international social media conferences and serves on the advisory board of MediaWell, an initiative by the Social Science Research Council (SSRC).
Photo credit: Habibur Rahman via unsplash
