Artificial Intelligence (AI) systems, in contemporary digital society, have drastically evolved from statistical tools to principal instruments of knowledge production, validation and dissemination. Large language models (LLMs), automated search systems, and predictive algorithms increasingly dictate what society knows, how knowledge is validated, and who is recognized as an expert/authority. This shift demands a rigorous critique from the perspective of the sociology of knowledge to evaluate how power, inequality, and social structures are embedded within these automated epistemic tools. The panel invites contributions that explore this socio-epistemic duality of AI through conflicting dynamics: Societal Hospitality and Structural Hostility.

On the surface, consumer-facing AI presents a welcoming, democratic frontier. It offers immediate information access, bridges linguistic barriers, lowers technical entry requirements, and serves as an affordable intellectual assistant. This interface-level hospitality suggests an era of information democratization, flattening historical institutional gatekeeping. Beneath this user-friendly disguise lies an aggressive political economy of knowledge. This infrastructure relies on the extraction of human cognitive labor, the enclosure of the global intellectual commons, and the automated erasure of marginalized ways of knowing. The back end of AI systems enforces a rigid epistemology that encodes historical social biases, presenting them as neutral, objective, mathematical truths. This panel seeks to bring together scholars, theorists, and empirical researchers to map this friction. The panel aims to explore how AI acts simultaneously as an infrastructure of social integration and a vector of epistemic alienation.

The panel invites abstracts from scholars at all career stages, encouraging contributions from digital sociology, science and technology studies (STS), critical race studies, media studies, political economy and other interdisciplinary fields. The panel welcomes empirical, theoretical, and methodological papers that address questions including, but not limited to:

The Political Economy of Algorithmic Expertise
The Erasure of Tacit and Indigenous Knowledge
The Deskilling and Alienation of Cognitive Labor
Conversational AI as a Trojan Horse
Digital Colonialism and Epistemic Homogenization
Algorithmic Stratification and Epistemic Class Divides
Epistemic Resistance, Subversion, and Counter-Publics
The Techno-Religious Frame: AI as the Modern Oracle


Reference:

Benjamin, R. (2019). Race After Technology: Abolitionist Tools for the New Jim Code. Polity.

Collins, H. (2024). Why Artificial Intelligence Needs Sociology of Knowledge. Cambridge University Press.

Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press.

Fricker, M. (2007). Epistemic Injustice: Power and the Ethics of Knowing. Oxford University Press.

Liu, C. (2026). The Sociology of AI as an Emerging Field: Mapping Tensions and Boundaries. Sociology Compass.

Zuboff, S. (2019). The Age of Surveillance Capitalism. Public Affairs.



Submission Requirements:

Abstracts: 300–500 words, clearly stating the research problem, theoretical framework, methodology (if empirical), and core argument along with A/V requirements
Keywords: 3–5 keywords
Biography: A brief biography (100 words) of the author(s)
Please send queries, suggestions and scheduling requests to Dr. Amrita Basu Roy Chowdhury (Lady Brabourne College, India) at basuroyamrita1983@gmail.com and/or through the Ballast platform by 31 August 2026.

[Please note that all submissions will eventually have to be uploaded through Ballast.]