Replica_

About the project

The Data Double made visible, toward an actionable representation of algorithmic identity.

Every digital action silently feeds an algorithmic profile that shapes real-world opportunities without awareness or consent. Replica is an ecosystem that makes the data double visible and actionable. A dashboard reconstructs the algorithmic identity inferred from browsing behavior, while Replica_ Mod 01, the first device in the system, is designed for digital workers and returns control through two physical interactions: injecting noise to become unclassifiable, or reinforcing chosen signals.

Research and Methodology
This thesis investigates the growing disconnect between a person’s real identity and the algorithmic “Data Double” generated through digital traces. The research combines an extensive literature review on digital footprints, data brokers, privacy, algorithmic profiling, and cognitive psychology with case study analysis and field research. The methodology includes surveys, semi-structured interviews with users and experts, behavioral mapping, persona development, and user journey analysis to understand privacy apathy, data literacy, and the mechanisms required to make algorithmic identity understandable and actionable.

Concept and Development
The project introduces Replica, a system that makes the invisible “Data Double” tangible by translating algorithmic profiling into an accessible representation. Rather than focusing solely on privacy settings or data deletion, Replica aims to expose how personal information is collected, interpreted, and transformed into predictive identities that influence real-world opportunities. The concept combines a browser extension, a dashboard, and a dedicated physical device to visualize discrepancies between the user’s actual identity and their algorithmic profile while enabling meaningful interaction and control over personal data.

User Experience and Application
Replica creates a human-centered experience that helps users understand how their digital footprint is constructed, where data originates, and how algorithmic inferences affect employment, housing, finance, and online reputation. Through intuitive visualizations, physical interaction, and actionable feedback, the system encourages users to move from passive acceptance of opaque profiling systems toward active stewardship of their digital identity.