Using AI to improve representation in media
Entertainment media, particularly film and television, significantly influences viewers' perceptions and social narratives. It shapes how we view the world, our roles in society, our values, our career aspirations, and even who we see as cultural heroes. This video explores MUSE, Media Understanding for Social Exploration, a project that applies Google AI to studying representation in media.
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You’ll hear from:
Madeline Di Nonno, President & CEO, Geena Davis Institute
Komal Singh, Sr. Product Manager, Google Research
Krishna Somandepalli, Sr. Software Engineer, Google Research
The Challenge of Media Representation
Given how influential entertainment media can be, the Geena Davis Institute on Gender in Media has partnered with Google Research to leverage AI to analyze various modalities within media—Visuals, Sound Design, and Language—to understand perceived age, gender, skin tones, and the natural language of actors and the characters they portray, to enhance our understanding of representation.
What is Project MUSE?
In collaboration with The Geena Davis Institute on Gender in Media, The University of Southern California, and the International Advertising Association India Chapter, Google Research conducted an extensive longitudinal study on representation in the most popular scripted TV series in America and India over the past five years. This study utilized advanced insights and analysis, cutting-edge machine learning technology, and expert advisement to understand media portrayal and its impact on viewers.
What is the Scully Effect?
The Scully Effect is a phenomenon where the fictional FBI agent Dana Scully from the TV show The X-Files inspires women to pursue careers in STEM (science, technology, engineering, and math). According to a 2018 report by the Geena Davis Institute on Gender in Media, 63% of women in STEM who grew up watching The X-Files stated that Scully, portrayed by Gillian Anderson, was a role model who boosted their confidence to succeed in a male-dominated field.
Benefits for Society
With Google Research’s machine learning innovations, MUSE can infer human-centric signals at scale, including perceived gender expression, age, and skin tone. This advanced technology allows us to process large volumes of data efficiently, significantly reducing time and costs compared to manual methods.
The speed of automation enabled us to extend the study across five languages—Hindi, Bengali, Tamil, Telugu, and Kannada—over a five-year period, providing valuable insights into historical trends across these Indian languages.
This video is perfect for anyone interested in:
Artificial intelligence applications
Building in better representation for media
Technological solutions for Diversity, Equity, and Inclusion
Products Mentioned: Google AI