Context & Problem

Biometric data and biosignals are increasingly embedded in everyday technologies, from fitness trackers to authentication systems. While these systems promise convenience, health insights, and personal optimisation, the processes of data collection, storage, and reuse remain largely invisible to users. Consent is often reduced to legal agreements and perceived as mandatory rather than optional. Users feel powerless and poorly informed about how their data is used, leading to a growing gap between data sharing and data awareness.

This project is situated at the intersection of Interaction design, data privacy, and critical play, exploring how playful, physical interaction can be used to help people critically reflect on the collection, use, and ownership of biometric data, and their own role within data-driven systems.

Research question:

How can critical play in the form of an activist game raise awareness of the issue of data privacy and encourage critical reflection on one’s own behaviour with personal data?

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Design Process

This project followed a human-centred design process structured around the phases Empathise, Define, Ideate, Prototype, and Playtest, moving from research and analysis toward experimentation and implementation.

Research Phase 1 – Biosignals, Self-Tracking & Awareness

The project began with an exploration of how biosignals and biometric data could be represented in more physical and experiential ways, rather than through abstract numbers and graphs. The goal was to foster mindfulness and embodied awareness, while also questioning how sharing personal body data in real time impacts perceptions of privacy and control.
Research methods included desktop research, a survey, and a self-tracking experiment. Results showed that most participants regularly use fitness or health-tracking devices and value them for performance improvement, health monitoring, and self-understanding. However, concerns emerged around over-reliance on data, misinterpretation, and unease about data storage, monetisation, and long-term use. While many participants were willing to share data for medical benefits, this willingness was highly context-dependent and often accompanied by discomfort about who ultimately profits from the data.

Research Phase 2 – Data Privacy & Surveillance

The second research phase focused more explicitly on personal data, biometric identifiers, and data protection, extending into themes of surveillance capitalism and data as a commodity. Unstructured interviews revealed a wide spectrum of attitudes, from highly privacy-conscious individuals to those largely unconcerned.
Across all interviews, participants generally understood what private data is but had limited knowledge of biometric data classifications and GDPR specifics. Many expressed feelings of powerlessness, frustration with opaque consent systems, and a lack of meaningful choice. Data consent was often seen as unavoidable for participation in modern social and digital life, reinforcing a sense that once data is collected, it cannot truly be reclaimed or deleted.

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From Research to Concept

Insights from research were mapped and synthesised, categorising biometric data into physical and behavioural identifiers and identifying key application areas such as security, healthcare, fitness, entertainment, and art. Initial experiments with biosensors informed technical feasibility, but practical constraints (including COVID-19) led to a shift away from wearable devices and real-world data towards exemplary represented biosignal data.

This phase introduced the central metaphor of the “black box” as a way to communicate the hidden processes of data collection and exploitation.

• Users provide data → data disappears into a system
• Internal processes are hidden
• Value is extracted, but control is unclear

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Solution

Using the framework of critical play, the concept evolved into an activist tabletop game, where players must make decisions that mirror real-life data-sharing behaviour in order to progress.
Personal data , in form of game tokens, is represented as a physical resource and functions as game currency. Players must trade this data in order to gain advantages, improvements, or convenience. The collected data disappears into a central “black box,” which stands for opaque data infrastructures and loss of control over data by users. The goal is to gain access to, or ownership of all collected data.

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Game components

Motivation categories: Categorised in access control, security, health/fitness, convenience, socialising and entertainment

Digitalisation meter: Meter going from “Anonymous” to “Digital doppelgänger”, separated in three scales, one for each type of data

Data token: Colour coded and categoriesed into biometric data, biosignals and general personal data

Game board & Black Box: Game board with up and down connections and marked fields for event cards. Black Box in which all the data tokens need to be “payed”

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Game Play

Goal of the game

Players must decide when, why, and how much personal data to share in order to gain benefits—while avoiding the loss of control over their digital identity.
The game ends when one player has fully maxed all motivation categories.
The winner is the player who owns the most data at the end.

Design Intention

• There is no "correct" way to play
• Reflection emerges through decision-making and discussion
• The mechanics simulate real-world trade-offs between benefit, convenience, and privacy
• The game prioritises awareness over competition

Turn Structure

Each turn consists of three phases:

1. Draw
The player draws one Action card

2. Play or Discard
The player chooses to play or discard one action card from their hand

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