Seeing with Machines: A Reflexive Ethnography of AI Systems in Everyday Life

Abstract

Students conduct a reflexive ethnography of their everyday AI interactions, keeping field notes and analyzing how AI shapes perception, behavior, and identity. Instead of being passive users, it challenges students to reveal the invisible processes shaping their digital lives and fosters awareness of data collection, algorithmic decision-making, and...

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Details

Subject Area(s):

Ethnography, Science and Technology

Resource Type(s):

Assignment

Class Level(s):

Any Level, Graduate

Class Size(s):

Medium

Usage Notes

This assignment is best introduced during the first third of a course on digital sociology, sociology of AI, or science and technology studies. It is designed to help students move from abstract discussions of algorithmic power to embodied, reflexive analysis of their own experiences as data subjects. The assignment can be used online and in the...

Learning Goals and Assessments

Learning Goal(s):

1. Use ethnographic methods to examine everyday interactions with AI systems.
2. Identify how algorithmic processes shape user behavior, perception, and social
   identity.
3. Apply sociological theory (e.g., social construction, classification, bias,
   reflexivity) to analyze AI technologies.
4. Foster ethical awareness of data collection and surveillance in algorithmic systems.
5. Develop reflexive writing that connects personal experience with structural critique.

Goal Assessment(s):

1. Students demonstrate their learning through a 5-page ethnographic analysis that includes field observations, application of sociological theory, and a critical reflection on AI's social impact. Engagement is assessed through the integration of course readings, depth of reflection, and the ability to connect personal experience with broader social...