University of British Columbia

AI-generated Anonymity in VR Journalism

University of British Columbia is one of the 2017 winners of the Journalism 360 Challenge. See all the winners.


  • Owen Taylor
  • Steve DiPaola

Project Description

This project will explore the use of computational abstraction in video-based virtual reality journalism for the purpose of anonymizing subjects. Using an AI video filter tool developed by project co-applicant Steve DiPaola, we will test whether emotional resonance, or empathy, can be maintained when a character is algorithmically distorted to the point at which their identity is hidden.

Our goal is to address a central challenge in VR journalism — that standard tools of anonymization such as blurring or blacking out faces and silhouettes breaks the emotional connection that is the central premise of the form. Using animated abstraction could allow for a viewer to remain emotionally connected to a character or subject, while still granting the confidentiality needed for investigative journalism.

This project has three components. First, we will adapt our current 2D AI filter for use in 360 3D video environments. Second, we will run a series of experiments to determine whether the empathetic connection created in immersive video translates to abstracted animations. This will involve three tests: (1) a study to determine which magnitude and types of abstraction best convey an emotional connection of an interview; (2) determine at what point of abstraction emotional connection is lost; and (3) develop a tool to allow interview subjects to fine tune their own level of abstraction. Third, we will produce a short piece of journalism portraying various characters with different levels of anonymization. We will produce this work of journalism on a topic of the growing opioid epidemic in Vancouver, a subject that is both ideally suited to the immersive form of VR, but also rife with challenges of confidentiality.

We will partner with a national media outlet to publish this work.