Actions Panel
Optimizing for What? Algorithmic Amplification and Society
A two-day symposium exploring algorithmic amplification and distortion as well as potential interventions
When and where
Date and time
April 28 · 9:30am - April 29 · 12:30pm EDT
Location
Columbia University 2920 Broadway New York, NY 10027
About this event
- 1 day 3 hours
- Mobile eTicket
On April 28-29, 2023, the Knight Institute will host a symposium 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 Arvind Narayanan. It will take place in-person at Columbia University and online.
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Featured papers:
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
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 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
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
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About the organizer
The Knight First Amendment Institute defends the freedoms of speech and the press in the digital age through strategic litigation, research, and public education. Its aim is to promote a system of free expression that is open and inclusive, that broadens and elevates public discourse, and that fosters creativity, accountability, and effective self-government.