The Knight First Amendment Institute will host a symposium in April 2023 to explore how online amplification works and to consider interventions that would mitigate some of the harms caused by amplification, or allow us to take fuller advantage of the benefits. The symposium, “Optimizing for What? Algorithmic Amplification and Society,” is a collaboration between the Knight Institute and the Institute’s Visiting Senior Research Scientist Arvind Narayanan and will take place at Columbia University and online.

We are excited to announce that the symposium will feature papers from an outstanding group of scholars, nonprofit leaders, and technology industry professionals, from a wide range of disciplinary backgrounds including computer science, psychology, law, philosophy, and other fields. 

A Field Experiment on the Impact of Algorithmic Curation on Content Consumption Behavior

  • Fabian Baumann, Postdoctoral Fellow, Max Planck Institute for Human Development
  • Philipp Lorenz-Spreen, Research Scientist, Max Planck Institute for Human Development

What's in an Algorithm? Empowering users through nutrition labels for recommender systems

  • Luca Belli, Independent Researcher
  • Marlena Wisniak, Senior Legal Consultant, European Center for Not-for-Profit Law

Algorithm-Mediated Social Learning in Online Social Networks

  • William J. Brady, Assistant Professor, Northwestern University
  • Joshua Conrad Jackson, Postdoctoral Researcher, Northwestern University
  • Björn Lindström, Senior Researcher and Principal Investigator, Karolinska Institute
  • M.J. Crockett, Associate Professor, Princeton University

Echo Chambers, Rabbit Holes, and Algorithmic Bias: How YouTube recommends content to real users

  • Megan Brown, Senior Research Engineer, NYU Center for Social Media and Politics
  • James Bisbee, Assistant Professor, Vanderbilt University
  • Angela Lai, Ph.D. Candidate, New York University
  • Richard Bonneau, Faculty Research Associate, NYU Center for Social Media and Politics
  • Jonathan Nagler, Professor of Politics and Co-Director, NYU Center for Social Media and Politics
  • Joshua A. Tucker, Professor of Politics and Co-Director, NYU Center for Social Media and Politics

Algorithmic Amplification for Collective Intelligence

  • Jason Burton, Assistant Professor, Copenhagen Business School; Alexander von Humboldt Research Fellow, Max Planck Institute for Human Development

A Public Service Media Perspective on the Algorithmic Amplification of Cultural Content

  • Fernando Diaz, Research Scientist, Google
  • Georgina Born, Professor, University College London

Teachable Agents for End-User Empowerment in Personalized Feed Curation

  • Kevin Feng, Ph.D. Student, University of Washington
  • David McDonald, Professor, University of Washington
  • Amy X. Zhang, Assistant Professor, University of Washington

How Friction-in-Design Moderates, Amplifies, and Dictates Speech and Conduct

  • Brett Frischmann, Professor, Villanova Law
  • Paul Ohm, Professor, Georgetown University Law Center

The Work of Art in the Age of Digital Commodification: An analysis of the emerging digital political economy of the performing arts

  • Sam Gill, CEO, Doris Duke Foundation
  • Annie Dorsen, Independent Artist

The Algorithmic Management of Polarization and Violence on Social Media

  • Ravi Iyer, Managing Director, Psychology of Technology Institute
  • Jonathan Stray, Senior Scientist, Center for Human-Compatible Artificial Intelligence
  • Helena Puig Larrauri, Strategy Lead & Co-Founder, Build Up

It’s the Algorithm: A large-scale comparative field study of news quality interventions

  • Benjamin Kaiser, Ph.D. Candidate, Center for Information Technology Policy, Princeton University
  • Stuart Begley-Miller, DuckDuckGo
  • Rob Johnstone, DuckDuckGo
  • Jonathan Mayer, Assistant Professor, Princeton University

What Makes Algorithmic Amplification Wrongful?

  • Benjamin Laufer, Ph.D. Candidate, Cornell Tech
  • Helen Nissenbaum, Professor, Cornell Tech

Communicative Justice and the Distribution of Attention

  • Seth Lazar, Professor, Australian National University

The Myth of “The Algorithm”: A system-level view of algorithmic amplification

  • Kristian Lum, Associate Research Professor, University of Chicago
  • Tomo Lazovich, Senior Research Scientist, Institute for Experiential AI at Northeastern University

Emotional and Political Effects of Twitter’s Ranking Algorithm

  • Smitha Milli, Postdoctoral Associate, Cornell Tech
  • Micah Carroll, Ph.D. Candidate, University of California, Berkeley
  • Sashrika Pandey, Undergraduate Researcher, University of California, Berkeley
  • Yike Wang, Undergraduate Researcher, University of California, Berkeley
  • Anca Dragan, Associate Professor, University of California, Berkeley

Bridging Systems: Open problems for countering destructive divisiveness in ranking, recommenders, and governance

  • Aviv Ovadya, Affiliate, Berkman Klein Center, Harvard University
  • Luke Thorburn, Ph.D. Candidate, King’s College London

Recommenders with Values: Developing recommendation engines in a public service organization

  • Alessandro Piscopo, Lead Data Scientist, BBC Product Group
  • Lianne Kerlin, Research Lead, BBC R&D
  • North Kuras, Senior UX Architect, BBC Product Group
  • James Fletcher, Responsible Data & AI Lead, BBC Product Group
  • Calum Wiggins, Executive Product Manager, BBC Product Group
  • Anna McGovern, Lead Automated Curation Specialist, BBC Product Group
  • Megan Stamper, Head of Data Science, BBC Product Group

Cycles of Symbol Production on Online Platforms

  • Inioluwa Deborah Raji, Ph.D. Candidate, University of California, Berkeley
  • Fernando Diaz, Research Scientist, Google
  • Irene Lo, Assistant Professor, Stanford University

The first day of the symposium, April 27, 2023, will consist of private workshop sessions at which authors of submitted papers will discuss and improve their papers. The second and third days, April 28-29, 2023, will be open to the public. The public event will feature a series of discussions and presentations on algorithmic amplification by contributing authors and others.

Sign up here to attend the public portion of the “Optimizing for What? Algorithmic Amplification and Society” symposium on April 28-29, 2023.