Reflection AI: teaching with AI: Facial Subjects and the politics of the face

This essay explores the pedagogical use of images generated by artificial intelligence (AI) to investigate the politics of facial representation. Through a media archaeological and visual culture lens, the essay outlines a classroom assignment, Facial Subjects , in which students generate photographic portraits using generative AI to critically examine how identity categories such as race, gender and class are constructed, mediated and encoded by machine learning (ML) systems. By comparing AI-generated portraits to archival and real-word photographic portraits, students engage in visual critique while developing media literacy in the analysis of images. The essay argues that teaching with AI-generated images provides new resources for critical media pedagogy and that comparing those images with archival and real-world portraits equips students with conceptual tools for thinking about questions of aesthetics, normativity, and bias central to film and media studies today. Through this exercise, teaching with AI becomes a method of inquiring into the ideological underpinnings of contemporary image systems while fostering experimental and critical approaches to media pedagogy.

Authors

Institutions

Publication Details

Journal
Frontiers in Communication
Published
2026-02-13
DOI
https://doi.org/10.3389/fcomm.2025.1629478
Primary Topic
Participatory Visual Research Methods
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reflection AI: teaching with AI: Facial Subjects and the politics of the face

Lisa Åkervall
Frontiers in Communication
Participatory Visual Research Methods
article

Reflection AI: teaching with AI: Facial Subjects and the politics of the face

Lisa Åkervall
article en

Abstract

This essay explores the pedagogical use of images generated by artificial intelligence (AI) to investigate the politics of facial representation. Through a media archaeological and visual culture lens, the essay outlines a classroom assignment, Facial Subjects , in which students generate photographic portraits using generative AI to critically examine how identity categories such as race, gender and class are constructed, mediated and encoded by machine learning (ML) systems. By comparing AI-generated portraits to archival and real-word photographic portraits, students engage in visual critique while developing media literacy in the analysis of images. The essay argues that teaching with AI-generated images provides new resources for critical media pedagogy and that comparing those images with archival and real-world portraits equips students with conceptual tools for thinking about questions of aesthetics, normativity, and bias central to film and media studies today. Through this exercise, teaching with AI becomes a method of inquiring into the ideological underpinnings of contemporary image systems while fostering experimental and critical approaches to media pedagogy.

Frontiers in CommunicationVol. 10
University of Gothenburg (SE)
Quality Education
Openalex Percentile: Top 61%
Participatory Visual Research Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.