(upbeat music)
(computer keys clicking) - Yes, Scully was a badass. She was levelheaded, she
used logic, she used science, and she certainly could save herself. - Dana Scully from "The X-Files"
was breaking stereotypes, and I thought of her to be my hero. And then later on, I was
exposed to this study called "The Scully Effect,"
which basically revealed that 63% of women working
in STEM identified Scully as a role model while
they were growing up. I am a byproduct of the Scully effect. And I think that's the power
that characters in media hold. (upbeat music continues) (upbeat music continues) (computer keys clicking) - For 20 years the institute has looked at onscreen representation, and what we've always done is
we've taken the data directly to the leading content
creators, studio by studio, network by network, company by company. When people are presented with the data, it really has moved them to make change. - In the past few years, Google Research has
developed Project MUSE, which stands for Media Understanding
for Social Exploration. It is basically a project that is aimed at using AI to study
representation in media. (machine clicking) - Media is composed of
what we call modalities: the visuals, the sound
design, and the language. What AI does is try to
automatically understand how people are being portrayed along these various dimensions. - [Komal] So it can be
computer vision systems that can infer the perceived
age, perceived gender, perceived skin tone, to natural
language processing models. - These are all perception attributes, and we need scales that are inclusive. For example, we often have
scales like light or dark, which is not enough variety of
skin tones that people have. So the Monk Skin Tone Scale
was developed in collaboration with Dr. Ellis Monk This 10-point scale captured
diverse types of skin tones, which helps us understand
the media content better. - So we were really excited to
partner with Google Research on the American TV study
looking longitudinally over 12 years. - The scale of the study was huge because it was looking at
top 10 broadcast TV shows of every year. The data we looked at
was about 480 episodes. That accounted to about 440 hours of data. We were able to process
this in under 24 hours. - And that's something
that would not be possible with using human annotators, which has been the traditional
way of doing such studies. - So what we found is, even though there's been
progress over 12 years, male characters still had much
more screen and speaking time than female characters. (machine clicking) - After we conducted the
American TV show study, we partnered with the
Geena Davis Institute and with the University of
Southern California again to study representation
in Indian television because of the usage
of multiple languages, the skin tone diversity,
the cultural nuance. - Part of this work relies on a lot of technological advances
made by Google Research. For example, the Universal
Speech Models allow us to automatically transcribe speech, not just in English, but
different Indian languages we used in the India study. And Monk Skin Tone Scale
helped us measure skin tone on a much granular scale. - It was really interesting to see that a country where there's
so much skin tone diversity, even now, more than 80%
of screen time is given to characters with lighter skin tone. - Google Research has always been a great and supportive partner, and the insights that they've
been able to help us garner really pushes the research much further. (upbeat music) - What technologies are
good at doing right now is understanding these
individual modalities well. And once we start understanding
these modalities together, we can then start understanding the stories being told computationally, ask questions like: When
does this person show agency? - I grew up in India, where I was very
impressionable by the media that I consumed. A lot of these roles
were not played by people who looked like me. And then, to be at a place
in my professional life to be able to do something about it was really a full-circle moment for me. (upbeat music continues)
(air whooshing) (upbeat music continues)
Senior Product Manager @ Google AI Research | Author | Board Member | Public Speaker | Kind Human
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