Research Seminar: Prof Finola Kerrigan
Seminar Title: Algorithmic identity- understanding consumer vulnerability
Abstract: The digital has transformed identity formation, requiring new frameworks to understand how online selves are constructed and perceived. Algorithms play a pivotal role in shaping these identities, offering personalization and convenience while raising concerns about privacy, authenticity, and fairness (Wei & Geiger, 2025). This paper draws on a multi-year study exploring how individuals interpret their algorithmic identity through online profiling.
Digital identities are built from social media profiles, behavioral data, and interactions, which are tracked to deliver personalized content and advertising (Kerrigan & Hart, 2016). Cheney-Lippold (2011) introduced the concept of “algorithmic identity,” where algorithms infer identity categories from data, enabling measurable classifications such as gender or class. Airoldi and Rokka (2022) describe “algorithmic consumer culture,” contrasting optimistic views of digital freedom with critical perspectives warning of exploitation through profiling and surveillance (Zuboff, 2019; Darmody & Zwick, 2020). Puntoni et al. (2020) note that accurate algorithmic classification can make consumers feel understood, while errors lead to feelings of misunderstanding. Our research examines consumer vulnerability from a temporal perspective and proposes a typology to guide ethical algorithmic profiling.
Two studies inform our findings. First, twenty heavy social media users documented targeted ads and posts over two weeks, storing screenshots on Pinterest and discussing their experiences in interviews. Results show that while algorithms engage with aspirational selves, they fail to capture humor, unconventional language, and individuality. Despite claims of personalization, aggregation dominates, reinforcing heteronormative assumptions based on fixed identity markers like age and gender. A second study recruited sixteen participants who did not conform to social norms of age or gender. Interviews revealed persistent stereotyping despite personalization efforts. Five themes emerged: social media as a mirror, passive acceptance of algorithmic identity, risks of sharing, heteronormative assumptions, and coping strategies.
While prior research highlights harm from misclassification, our findings demonstrate that accurate profiling can also have negative effects. These insights underscore the need for greater sensitivity and filtering in algorithmic marketing to minimize harm. We conclude with guidelines to support ethical practices.
Bio: Finola Kerrigan is Professor of Marketing at Birmingham Business School, where she has recently finished a term as Deputy Dean, and 8 months as Interim Dean. She has previously held leadership roles such as the Director of the Fashion Business Research Centre at University of the Arts London, Research Environment Lead at Birmingham Business School and Head of the Department of Marketing, Birmingham Business School. She has published her research in a range of international journals such as the Academy of Management Journal, Journal of Consumer Research, Journal of Business Ethics, and International Journal of Research in Marketing. She is the co-editor in chief of Marketing Theory. Drawing on a range of qualitative and creative research methods, Finola has researched subjects on branding, digital identity, ethics and the incorporation of new technologies into marketing practice and how this impacts consumers. With a specific focus on researching the cultural and creative industries, Finola centres the arts both in terms of arts-based methods and as a context for her research. As well as her academic research, which has been funded by the ESRC, EPSCR, British Academy and a range of charitable organisations, Finola has completed several industry research projects in collaboration with public bodies and commercial companies and is a trustee of Jasmine Vardimon Company.
Note: Tea, coffee, and sandwiches will be provided in front of Café Jolt (Lower Ground Floor) at 12 pm.
Photographs will be taken during this seminar and may be shared on social media. If you do not wish to appear, please notify tbs.research@tcd.ie.