HAI Weekly Seminar with Pamela Chen
In this talk, Pamela Chen, 2020 Human-Centered AI and JSK Journalism Fellow at Stanford, shares her experiences leading an editorial team at Instagram as the company scaled content discovery to serve more than 1 billion monthly active users. Spoiler alert: it doesn’t go as planned.
As content platforms began to rely on machine learning to personalize recommendations, they inadvertently enabled a new human creator class who specialized in going viral via the machine. The ranking algorithms got better at predicting the content we respond to, and these viral meme creators got better at achieving the response the algorithms were designed to predict. This emerging feedback loop, combined with the hard learnings of scaling content discovery, has led to new questions.
Who are the players behind “the power of memes” to both expand the global cultural zeitgeist and enable targeted disinformation campaigns at astounding scale? And how can better understanding the ecosystem change the way we approach the design of human-centered AI in content curation systems today?
Related Events
Tom Mitchell | The History of Machine Learning
How did we get to today’s technology which now supports a trillion dollar AI industry? What were the key scientific breakthroughs? What were the surprises and dead-ends along the way...
How did we get to today’s technology which now supports a trillion dollar AI industry? What were the key scientific breakthroughs? What were the surprises and dead-ends along the way...
Dan Iancu & Antonio Skillicorn | Interpretable Machine Learning and Mixed Datasets for Predicting Child Labor in Ghana’s Cocoa Sector
Child labor remains prevalent in Ghana’s cocoa sector and is associated with adverse educational and health outcomes for children.
Child labor remains prevalent in Ghana’s cocoa sector and is associated with adverse educational and health outcomes for children.