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Dr Gemma Newlands

Departmental Research Lecturer in AI & Work

Dr Gemma Newlands

Departmental Research Lecturer in AI & Work


Dr. Gemma Newlands is a Departmental Research Lecturer in AI & Work. As an organisational sociologist, her research explores the impact of artificial intelligence on work and organisations, with particular focus on issues of surveillance and visibility. Her current research investigates the sustainability of AI production, situated at the intersection of supply-chain theory and critical data studies. Gemma also has ongoing research interests in the recognition and evaluation of work in the digital economy, exploring both the notions of occupational prestige and occupational social value.

Her research has been published in leading journals including Organization Studies, Sociology, Environment and Planning A: Economy and Space, Big Data & Society, New Media & Society, New Technology, Work and Employment and Research in the Sociology of Organizations.

Gemma received her PhD from the University of Amsterdam in 2023. Previously, Gemma was an Assistant Editor at Big Data & Society and has participated in multiple research projects funded by the Norwegian Research Council and the European Research Council.

Research Interests

Artificial Intelligence, Work and Labour, AI Production, Sustainability, Privacy and Surveillance, Social Theory

Positions at the OII

  • Departmental Research Lecturer in AI & Work, September 2022 -




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Current Courses

Internet and Society

Internet and Society is a comprehensive course designed to provide an overview of major themes, theories, and concepts related to the social implications of the Internet. Taking a multidisciplinary approach which combines several social science disciplines, this course will explore the social impact of the Internet's evolution, addressing both its opportunities and challenges.

Digital Interviewing and Qualitative Data Analysis

This course is designed to give students hands‐on practice gathering qualitative data and provide students with the knowledge and skills to analyse various types of qualitative data analysis collected from both online and offline settings.