Project Description

Data Portraits represent both a precursor to Inner-Selfies and a forward-looking extension of Brain Terrains.

Now being developed as a standalone, web-based platform, the project aims to combine:

• Conversational AI

• Personal data reflection

• Generative visual composition

Participants will be invited into a dialogic process—surfacing data through conversation and co-composing evolving portraits of identity. The emphasis is not on representation, but on meaning-making: how data becomes legible, relational, and human.

Conceived as a modular system, Data Portraits is positioned for deployment across cultural, medical, and research environments, and as a foundation for future installations, residencies, and collaborations.

The Conceptual Shift

Data Portraits extends Brain Terrains toward a generative, dialogic system. While earlier works explored the visual resonance between bodily and planetary data, this project asks how identity might be co-composed through interaction, reflection, and conversation.

The shift is from static representation to process. Rather than producing a finished portrait, the platform invites participants into an unfolding exchange—using conversational AI to surface data, prompt reflection, and shape evolving visual forms. The portrait becomes less an image of the self and more a record of inquiry.

Why It Matters (and What’s Next)

As a work in development, Data Portraits points toward new possibilities for engaging with personal data in ethical, human-centered ways. It proposes an alternative to extractive or performative data practices by emphasizing reflection, agency, and meaning-making.

Conceived as a modular, web-based platform, the project is positioned for future deployment across cultural institutions, medical and neuroscience contexts, and research environments. It establishes a foundation for installations, residencies, and collaborations that treat data not as an endpoint, but as a starting point for dialogue.