Policy Brief
This report explores the potential of bridging and discusses some of the most common objections, addressing questions around legitimacy and practicality.
Algorithmic ranking and recommendation systems determine what kinds of behaviors are rewarded by digital platforms like Facebook, YouTube, and TikTok by choosing what content to show to users. Because these platforms dominate our attention economy, and because attention can be transformed into money and power, platform recommendations therefore provide a reward structure for society at large.
Platforms currently reward divisive behavior with attention due to the interactions between engagement-based ranking and human psychology. This helps determine the kinds of politicians, journalists, entertainers, and others who can succeed in their respective social arenas, resulting in significant impacts on the quality of our decision-making, our capacity to cooperate, the likelihood of violent conflict, and the robustness of democracy.
We can potentially mitigate this ‘centrifugal’ force toward division by deploying ranking systems that do the opposite—that provide a countervailing ‘centripetal’ or bridging force.
Bridging-based ranking rewards behavior that bridges divides. For example, imagine if Facebook rewarded content that led to positive interactions across diverse audiences, including around divisive topics. How might that change what people, posts, pages, and groups are successful?
This report explores the potential of bridging and discusses some of the most common objections, addressing questions around legitimacy and practicality. It contrasts bridging with some of the most discussed approaches for reforming ranking: reverse-chronological feeds, ‘middleware’, and ‘choose your own ranking system’. (Unfortunately, without introducing bridging, all of these proposed reforms still reward those who seek to divide.) Finally, this report explores early examples where bridging systems are already being tried with some success.
Summary of Next Steps
We can and should rapidly build capacity to develop, evaluate, and deploy bridging-based ranking systems.
Bridging-based ranking alone is not a silver bullet—we need other reforms to address the many challenges of platform-enabled connectivity. But bridging would help address one of the most significant risks—that of being pushed past a “division threshold” beyond which democracy can no longer function.
Paper
Allen Lab for Democracy Renovation authors offer the first comprehensive analysis of how Massachusetts municipalities are using technology to support civic engagement, government decision-making, and public service delivery.
Feature
As we celebrate America’s 250th, the Allen Lab for Democracy Renovation is reflecting on how we arrived at this moment and where we are headed.
Commentary
Allen Lab member Charlie Covit reflects on the After Neoliberalism conference and examines the intersection of artificial intelligence and the future of work, arguing that AI forces a democratic reckoning with the meaning of labor itself and that an economy which generates abundance while stripping citizens of purpose and dignity undermines the very foundation of democratic life.
Paper
Allen Lab for Democracy Renovation authors offer the first comprehensive analysis of how Massachusetts municipalities are using technology to support civic engagement, government decision-making, and public service delivery.
Commentary
Allen Lab member Charlie Covit reflects on the After Neoliberalism conference and examines the intersection of artificial intelligence and the future of work, arguing that AI forces a democratic reckoning with the meaning of labor itself and that an economy which generates abundance while stripping citizens of purpose and dignity undermines the very foundation of democratic life.
Media Release
New study published in AI and Ethics introduces a new ethical-moral intelligence framework for AI and finds that leading AI models mimic human moral concern while making decisions that reveal a hidden value hierarchy.
