Algorithmic Mirror
Help Your Child See How Algorithms See Them
Oxford Internet Institute × Oxford Child-Centred AI Lab × MIT Media Lab · 2025
Introducing Algorithmic Mirror
Prototype: Algorithmic Mirror
Preprint: arXiv:2504.16615
The Synthetic Society Lab at Oxford Internet Institute, in collaboration with MIT Media Lab, Carnegie Mellon University, and the Oxford Child-centred AI Lab, has developed Algorithmic Mirror — an innovative visualisation tool that reveals how platforms like YouTube, TikTok, and Netflix interpret young people's viewing histories.
Your child will:
- See unique visualisations showing how algorithms categorise their interests over time
- Understand how their viewing habits data can be analysed by algorithms
- Learn practical strategies for managing their digital footprint
- Develop critical thinking skills about algorithmic systems
"With Algorithmic Mirror, I realize I'm watching quite a bit of content from genres that don't even remain in my memory. It's scary to realize that I'm watching things without awareness."
— from a participant in the last study
Temporal Evolution of Digital Footprint
Our participants from the last study realised that the categories and generative summaries were based on long-term data, and observed:
"recommendation algorithms remember you, like how you were interested."
Another participant critically questioned:
"When YouTube tries to understand what I like, my question is how would it [recommender system] try to track my interest over time and project new interests, or would it just like take me as I currently am and give me exactly what I like? [...] I can imagine it can try to predict how my personality would evolve in the next five years or so [...] it's a little scary."
Why does this matter?
Every video watched, every like, and every interaction creates data that platforms use to build sophisticated profiles of your child. These algorithmic profiles determine:
- Content Curation: What content appears in their feeds
- Time Spent: How much time they spend online
- Targeted Ads: Which advertisements target them
- Behaviour Prediction: How their interests and behaviours are predicted and influenced
The good news: when young people understand how algorithms interpret their data, they become more thoughtful digital citizens who can better protect their privacy and wellbeing online.
Team
- Yui Kondo (Research Associate, Oxford Internet Institute)
- Kevin Dunnell (PhD candidate, MIT Media Lab, USA)
- Isobel Voysey (Postdoctoral Researcher, University of Oxford)
- Qing Xiao (PhD Candidate, Carnegie Mellon University, USA)
- Dr. Jun Zhao (Senior Researcher, Oxford Child-Centred AI Lab, Department of Computer Science, University of Oxford)
- Dr. Luc Rocher (Associate Professor, Oxford Internet Institute, University of Oxford, UK)