While data and user records are a resource for human intellect, they may simultaneously contribute to the machine learning innovation process. Defining when a user is using online technology and when a user is a contributor to machine learning during online interactions is challenging and requires a better understanding of computational design, UX design, and data-surveillance in the context of human agency.

My research is investigating what the benefits of computational design are and how this insight can offer audiences and users more transparency on data-surveillance by creating prototypes that inform abstract and often invisible procedures. Applying a practice-based methodology lets me explore through iteration and prototyping what role computational design plays in a telematic experience. Revealing my findings will contribute to a better understanding of the human relationship with computational design, online technology, and the dialogue on automated processes as part of the creative practice of designers and media artists.