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Professor Ekaterina Hertog

Associate Professor in AI and Society

Professor
Ekaterina Hertog

Associate Professor in AI and Society

About

Ekaterina’s research interests lie at the intersection of digital sociology and family sociology. She leads the ESRC-funded DomesticAI project that scopes new technologies’ potential to free up time now locked into unpaid domestic labour and measures how willing people are to introduce these technologies into their private lives. First research findings are available as pre-prints here: The future(s) of unpaid work: How susceptible do experts from different backgrounds think the domestic sphere is to automation

and

The future of unpaid work: Estimating the effects of automation on time spent on housework and care work in Japan and the UK

Hertog’s earlier study of never-married single mothers in Japan that provides an in-depth analysis of Japanese women’s decision-making on childbearing issues and the related value systems was published as a book by Stanford University Press titled Tough Choices: Bearing an Illegitimate Child in Contemporary Japan. Her other research includes analyses of gender differences in time use in East Asia and an investigation of digital dating records from one of Japan’s largest matchmakers to scrutinise partner search processes, identifying the social factors that drive individual success and failure on the Japanese marriage market. She has published in journals such as Journal of Marriage and Family, Demographic Research, and PLOS One.

Research Interests

AI, Future of Unpaid Work, Living with Technology, Family Sociology, Time Use, Gender Practices in Households, Contemporary Japanese Society

Areas of Interest for Doctoral Supervision

Gender and Technology, Domestic Automation, Digitalisation of private lives, gender equality, attitudes to technology, trust, Europe, Japan

Positions at the OII

  • Associate Professor in AI and Society, March 2022 -

Research

Related Sites

Recordings

Teaching

Current Courses

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.