LIVE-ISH: TUNE-OUT TO-TUNE IN     https://www.twitch.tv/live_ish     LIVE-ISH: LIVESTYLES OF THE ON-CAMERA & UN-FAMOUS     https://www.twitch.tv/live_ish    LIVE-ISH: TUNE-OUT TO TUNE-IN     https://www.twitch.tv/live_ish     LIVE-ISH: LIVESTYLES OF THE ON-CAMERA & UN-FAMOUS     https://www.twitch.tv/live_ish    
   




























EPISODE 2:
AR-TV (ARRGH!-TV)




































AR-TV is a streaming publication of design research that explores how the stories we consume today are authored by not just humans but algorithmically tuned cameras.

As a part of SNAP INC Research’s 2020 CREATIVE CHALLENGE, in collaboration with BBC Research and MICROSOFT Research, ARTCENTER’S Immersion Lab examined the future of storytelling with augmented reality through the lens of the camera, computer vision, and machine learning.

AR-TV proposes ways to identify, author, and share new stories in collaboration with autonomous machines. If a story is a series of events that are suddenly given priority, importance, and structure, who or what decides this? How can computer vision reveal events and details that once went unnoticed? How can machine vision and learning models detect features, infer patterns, and predict scenes, now be co-authors? How might these new machine envisioned stories change how we understand and relate to one another?

ARTCENTER COLLEGE OF DESIGN Transdisciplinary Studio HOST DEPARTMENT Interaction Design FACULTY AND DESIGN RESEARCHER Jenny Rodenhouse THESIS RESEARCHER Miranda Jin ARTIST & DESIGNERS Davis Brown, Dillon Chi, Brandon Comer, Wenyu Du, Qihang Fan, Anna Kang, Casey Knapp, John Ma, Susie Moon, Jeanne Park, Ian Sterling, Nicole Wang TEACHING ASSISTANT Leo Yang WEB & AR BUMPER DESIGN Jenny Rodenhouse 



THANK YOU to our mentors RAJAN VAISH, ANDRES MONROY-HERNANDEZ, SNAP INC RESEARCH, BBC RESEARCH, and MICROSOFT RESEARCH