Event
Optimizing for What? Algorithmic Amplification and Society
A two-day symposium exploring algorithmic amplification and distortion as well as potential interventions
Columbia University
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 the Institute’s Visiting Senior Research Scientist Arvind Narayanan. It will take place in-person at Columbia University and online.
In-person guests should be prepared to show proof of vaccination upon entry.
Schedule
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Alfred Lerner Hall, Roone Arledge Cinema, or Online
2920 Broadway, New York, NY 10027
Welcome
- Jameel Jaffer, Knight First Amendment Institute at Columbia University
Keynote and conversation
- Alondra Nelson, Institute for Advanced Study
- Jameel Jaffer, Knight First Amendment Institute at Columbia University
Panel 1: Level setting
This panel will set the stage by discussing how platforms and platform algorithms work, laying out the issues at stake, reviewing recent developments, and looking at the legal questions relevant to possible reform options.
Panelists
- Tarleton Gillespie, Microsoft Research New England
- Daphne Keller, Stanford University
- Tomo Lazovich, Northeastern University
Moderator
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Arvind Narayanan, Princeton University and the Knight First Amendment Institute at Columbia University
Break
Panel 2: Audits
The panel will consider how algorithmic recommendations affect what real users see on social media, with deep dives into Twitter and YouTube. Panelists will discuss how platform design affects content creators and talk about research methods and ways to enable more audit research.
Panelists
- Fabian Baumann, Max Planck Institute for Human Development
- William J. Brady, Northwestern University
- Smitha Milli, Cornell Tech
- Inioluwa Deborah Raji, University of California, Berkeley
Moderator
- Laura Edelson, New York University
Lunch
Panel 3: Normative questions
How do algorithmic platforms distribute attention and shape social relations? How have they influenced the arts? The public square? What makes algorithmic amplification wrongful? What are the moral and political responsibilities of platforms?
Panelists
- Annie Dorsen, Independent Artist
- Benjamin Laufer, Cornell Tech
- Seth Lazar, Australian National University
Moderator
- Katy Glenn Bass, Knight First Amendment Institute at Columbia University
Break
Panel 4: Reform part 1
Panelists will discuss various ideas for reforming, including nutrition labels, friction, algorithmic interventions, and decentralized alternatives, with a deep dive into one particular area: how to dampen conflict feedback loops.
Panelists
- Luca Belli, Sator Labs and University of California, Berkeley
- Brett Frischmann, Villanova University
- Ravi Iyer, Psychology of Technology Institute
- Yoel Roth, University of California, Berkeley
Moderator
- Camille François, Columbia University
Visualizing virality
Presenters
- Samia Menon, Columbia University
- Sahil Patel, Columbia University
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Faculty House, Presidential Room 2, or Online
64 Morningside Dr, New York, NY 10027
Panel 5: Empirical look at user behavior
Algorithms learn from users’ behavior, and users rely on algorithm-mediated social learning. What is the nature of the resulting feedback loop? How can platforms empower users to make better informed decisions about potential disinformation? Conversely, what design interfaces can allow users to actively teach platforms their preferences?
Panelists
- Jason Burton, Copenhagen Business School and Max Planck Institute for Human Development
- Kevin Feng, University of Washington
- Benjamin Kaiser, Princeton University
- Angela Lai, New York University
Moderator
- Mor Naaman, Cornell Tech
Break
Panel 6: Reform part 2
How can platforms go beyond engagement optimization? For example, how can they design recommender systems to bridge political divides? What can we learn from public service media on how to design recommendation engines that reflect cultural values and responsibly curate cultural content?
Panelists
- Georgina Born, University College London
- Aviv Ovadya, Harvard University
- Alessandro Piscopo, BBC Product Group
Moderator
- Joe B. Bak Coleman, Columbia University
Lunch
Speakers
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Alondra Nelson
Institute for Advanced Study
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Joe B. Bak-Coleman
Columbia University
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Katy Glenn Bass
Research Director, Knight Institute
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Fabian Baumann
Max Planck Institute for Human Development
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Luca Belli
University of California, Berkeley
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Georgina Born
University College London
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William J. Brady
Northwestern University
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Jason W. Burton
Copenhagen Business School and the Max Planck Institute for Human Development
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Annie Dorsen
Independent Artist
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Laura Edelson
New York University
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Kevin Feng
University of Washington
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Camille François
Columbia University
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Brett Frischmann
Villanova University
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Tarleton Gillespie
Microsoft Research New England
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Ravi Iyer
Psychology of Technology Institute
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Jameel Jaffer
Executive Director, Knight Institute
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Benjamin Kaiser
Princeton University
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Daphne Keller
Stanford University
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Angela Lai
New York University
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Benjamin Laufer
Cornell Tech
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Seth Lazar
Senior AI Advisor 2024-2025; Australian National University
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Kristian Lum
University of Chicago
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Samia Menon
Columbia University
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Smitha Milli
Cornell Tech
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Mor Naaman
Cornell Tech
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Arvind Narayanan
Knight Institute Visiting Senior Research Scientist 2022-2023; Princeton University
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Aviv Ovadya
Harvard University
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Sahil Patel
Columbia University
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Alessandro Piscopo
BBC Product Group
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Inioluwa Deborah Raji
University of California, Berkeley; Mozilla
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Yoel Roth
University of California, Berkeley