Optimizing for What? Algorithmic Amplification and Society
Emilie Flamme

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 NarayananIt will take place in-person at Columbia University and online.

In-person guests should be prepared to show proof of vaccination upon entry. 

Algorithmic Amplification and Society blog posts

Understanding Social Media Recommendation Algorithms

Understanding Social Media Recommendation Algorithms: A discussion guide

Visualizing Virality


  • Alfred Lerner Hall, Roone Arledge Cinema, or Online

    2920 Broadway, New York, NY 10027


    • 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.


    • Tarleton Gillespie, Microsoft Research New England
    • Daphne Keller, Stanford University
    • Tomo Lazovich, Northeastern University


    • Arvind Narayanan, Princeton University and the Knight First Amendment Institute at Columbia University


    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.


    • Fabian Baumann, Max Planck Institute for Human Development
    • William J. Brady, Northwestern University
    • Smitha Milli, Cornell Tech
    • Inioluwa Deborah Raji, University of California, Berkeley  


    • Laura Edelson, New York University


    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?  


    • Annie Dorsen, Independent Artist
    • Benjamin Laufer, Cornell Tech
    • Seth Lazar, Australian National University 


    • Katy Glenn Bass, Knight First Amendment Institute at Columbia University


    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.


    • 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


    • Camille François, Columbia University

    Visualizing virality


    • Samia Menon, Columbia University
    • Sahil Patel, Columbia University

  • 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?


    • 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


    • Mor Naaman, Cornell Tech


    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?


    • Georgina Born, University College London
    • Aviv Ovadya, Harvard University
    • Alessandro Piscopo, BBC Product Group


    • Joe B. Bak Coleman, Columbia University



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