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Shaping Human Creativity at a Massive Scale | Stanford HAI

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news

Shaping Human Creativity at a Massive Scale

Date
June 26, 2020
Topics
Arts, Humanities
Machine Learning
Unsplash/Paul Gaudriault

HAI fellow Pamela Chen studies how creators harness AI to go viral on social platforms and why we need to question the process.

Gone are the days of lugging around a camera to every major family event or vacation. Today our smartphones operate as high-resolution cameras within arms’ reach.

But digital photography leads to digital-age issues. Our pictures can be manipulated. Our social sharing decides what images are shown to us, when, and how.

Pamela Chen is a JS Knight journalism and HAI fellow at Stanford University who studies how digital creators are harnessing AI to go viral. Before joining Stanford, she worked as a professional photographer and editor for National Geographic and ran Instagram’s ad account as one of the platform’s first hundred employees.

Chen was with Instagram when the company introduced machine learning in the form of content ranking algorithms around 2015 – more commonly know as the recommender systems.

“One of the things that I became increasingly aware of is that it affected the consumption experience, but it also deeply affected the creator experience,” she says. As the company shifted from showing images chronologically to predicting users’ interests, creators felt the “algorithm” was now in charge. That perception of the algorithm became a powerful influence on what artists posted.

In this Future of Everything podcast with HAI associate director Russ Altman, Chen discusses this artist dilemma and the changing perceptions of artist success, how platforms have the potential to shape human creativity at a massive scale, and how they also solve an important problem – helping us sort through massive amounts of information. She also shares her work studying memes and the incentive structures that help digital content go viral.

“These systems are very new and they are still being designed and redesigned,” she says. “It’s not too late to ask the right questions about why we’re doing this and what we’re optimizing for. These are powerful, predictive systems that are shaping human creativity, our behaviors, and our perception of what is real, so it really matters that we get this right.”

Watch the full conversation, below. 

 

This conversation is part of the Future of Everything podcast.

Stanford HAI's mission is to advance AI research, education, policy and practice to improve the human condition. Learn more. 

Unsplash/Paul Gaudriault
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Authors
  • headshot
    Shana Lynch
  • Russ Altman
    Russ Altman
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