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It’s easy to take for granted how much social media pervades our lives. Depending on the survey, upwards of 75-80 percent of Americans are using it daily—not to mention billions of people around the world. And over the past decade, we’ve seen a major backlash over the various failings of Big Tech. Much of the ire of policymakers has been focused on content moderation choices—what content gets left up or taken down. But arguably there hasn’t been much focus on the underlying design of social media platforms.
What are the default settings? How are the interfaces set up? How do the recommendation algorithms work? And what about transparency? What should the companies disclose to the public and to researchers? Are they hiding the ball?
In recent years, policymakers have started to take these issues head on. In the U.S. more than 75 bills have been introduced at the state and federal level since 2023—these bills target the design and operation of algorithms, and more than a dozen have been passed into law. Last year, New York and California passed laws attempting to keep children away from “addictive feeds.” Other states in 2025 have introduced similar bills. And there’s a lawsuit from 42 attorney generals against Meta over its design choices. While Congress hasn’t done much, if anything, to regulate social media, states are clearly filling that void—or at least trying to.
So what would make social media better, or better for you? Recently, a group of academic researchers organized by the Knight Georgetown Institute put out a paper called Better Feeds: Algorithms that Put People First They outline a series of recommendations that they argue would lead to better outcomes. Evan is joined by Alissa Cooper, co-author of the paper and Executive Director of the Knight-Georgetown Institute. She previously spent over a decade at Cisco Systems, including in engineering roles. Her work at KGI has focused on how platforms can design algorithms that prioritize long-term user value rather than short-term engagement metrics.
5
33 ratings
It’s easy to take for granted how much social media pervades our lives. Depending on the survey, upwards of 75-80 percent of Americans are using it daily—not to mention billions of people around the world. And over the past decade, we’ve seen a major backlash over the various failings of Big Tech. Much of the ire of policymakers has been focused on content moderation choices—what content gets left up or taken down. But arguably there hasn’t been much focus on the underlying design of social media platforms.
What are the default settings? How are the interfaces set up? How do the recommendation algorithms work? And what about transparency? What should the companies disclose to the public and to researchers? Are they hiding the ball?
In recent years, policymakers have started to take these issues head on. In the U.S. more than 75 bills have been introduced at the state and federal level since 2023—these bills target the design and operation of algorithms, and more than a dozen have been passed into law. Last year, New York and California passed laws attempting to keep children away from “addictive feeds.” Other states in 2025 have introduced similar bills. And there’s a lawsuit from 42 attorney generals against Meta over its design choices. While Congress hasn’t done much, if anything, to regulate social media, states are clearly filling that void—or at least trying to.
So what would make social media better, or better for you? Recently, a group of academic researchers organized by the Knight Georgetown Institute put out a paper called Better Feeds: Algorithms that Put People First They outline a series of recommendations that they argue would lead to better outcomes. Evan is joined by Alissa Cooper, co-author of the paper and Executive Director of the Knight-Georgetown Institute. She previously spent over a decade at Cisco Systems, including in engineering roles. Her work at KGI has focused on how platforms can design algorithms that prioritize long-term user value rather than short-term engagement metrics.
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