Affective Automation: A Cross-Cultural Exploration of Emotion in Artificial Intelligence Development

This project explores the emotional and cultural dynamics of artificial intelligence (AI) development across four global sites—Canada, the UK, India, and the US—by examining how emotions shape decision-making, productivity, and well-being within distributed teams. Focusing on the workplace processes of a leading transnational AI firm, the research addresses critical industry challenges in managing intercultural collaboration and fostering inclusivity through the lens of emotion. Using a mixed-methods approach, including surveys, interviews, and participant observations, the study investigates how cultural differences in emotional expression and regulation impact team cohesion, feature prioritization, and ethical considerations. By bridging gaps in emotional labour theory and organizational psychology, the findings will offer actionable recommendations to enhance emotional support systems, workplace diversity, and innovation. Participating institutions, including academic and industry partners, will benefit from deeper insights into the emotional underpinnings of AI development, advancing both theoretical knowledge and practical applications. This project also aligns with Canada’s Pan-Canadian Artificial Intelligence Strategy by addressing talent diversification and strengthening innovation capacity, providing tools to build resilient, inclusive global teams capable of driving AI innovation forward.

Faculty Supervisor:

Megan Boler

Student:

Partner:

University of Oxford

Discipline:

Sociology

Sector:

Artificial Intelligence; Technology; Information and Communications Technology

University:

University of Toronto

Program: