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An autonomous debating system

Author

Listed:
  • Noam Slonim

    (IBM Research AI)

  • Yonatan Bilu

    (IBM Research AI)

  • Carlos Alzate

    (IBM Research AI)

  • Roy Bar-Haim

    (IBM Research AI)

  • Ben Bogin

    (IBM Research AI)

  • Francesca Bonin

    (IBM Research AI)

  • Leshem Choshen

    (IBM Research AI)

  • Edo Cohen-Karlik

    (IBM Research AI)

  • Lena Dankin

    (IBM Research AI)

  • Lilach Edelstein

    (IBM Research AI)

  • Liat Ein-Dor

    (IBM Research AI)

  • Roni Friedman-Melamed

    (IBM Research AI)

  • Assaf Gavron

    (IBM Research AI)

  • Ariel Gera

    (IBM Research AI)

  • Martin Gleize

    (IBM Research AI)

  • Shai Gretz

    (IBM Research AI)

  • Dan Gutfreund

    (IBM Research AI)

  • Alon Halfon

    (IBM Research AI)

  • Daniel Hershcovich

    (IBM Research AI)

  • Ron Hoory

    (IBM Research AI)

  • Yufang Hou

    (IBM Research AI)

  • Shay Hummel

    (IBM Research AI)

  • Michal Jacovi

    (IBM Research AI)

  • Charles Jochim

    (IBM Research AI)

  • Yoav Kantor

    (IBM Research AI)

  • Yoav Katz

    (IBM Research AI)

  • David Konopnicki

    (IBM Research AI)

  • Zvi Kons

    (IBM Research AI)

  • Lili Kotlerman

    (IBM Research AI)

  • Dalia Krieger

    (IBM Research AI)

  • Dan Lahav

    (IBM Research AI)

  • Tamar Lavee

    (IBM Research AI)

  • Ran Levy

    (IBM Research AI)

  • Naftali Liberman

    (IBM Research AI)

  • Yosi Mass

    (IBM Research AI)

  • Amir Menczel

    (IBM Research AI)

  • Shachar Mirkin

    (IBM Research AI)

  • Guy Moshkowich

    (IBM Research AI)

  • Shila Ofek-Koifman

    (IBM Research AI)

  • Matan Orbach

    (IBM Research AI)

  • Ella Rabinovich

    (IBM Research AI)

  • Ruty Rinott

    (IBM Research AI)

  • Slava Shechtman

    (IBM Research AI)

  • Dafna Sheinwald

    (IBM Research AI)

  • Eyal Shnarch

    (IBM Research AI)

  • Ilya Shnayderman

    (IBM Research AI)

  • Aya Soffer

    (IBM Research AI)

  • Artem Spector

    (IBM Research AI)

  • Benjamin Sznajder

    (IBM Research AI)

  • Assaf Toledo

    (IBM Research AI)

  • Orith Toledo-Ronen

    (IBM Research AI)

  • Elad Venezian

    (IBM Research AI)

  • Ranit Aharonov

    (IBM Research AI)

Abstract

Artificial intelligence (AI) is defined as the ability of machines to perform tasks that are usually associated with intelligent beings. Argument and debate are fundamental capabilities of human intelligence, essential for a wide range of human activities, and common to all human societies. The development of computational argumentation technologies is therefore an important emerging discipline in AI research1. Here we present Project Debater, an autonomous debating system that can engage in a competitive debate with humans. We provide a complete description of the system’s architecture, a thorough and systematic evaluation of its operation across a wide range of debate topics, and a detailed account of the system’s performance in its public debut against three expert human debaters. We also highlight the fundamental differences between debating with humans as opposed to challenging humans in game competitions, the latter being the focus of classical ‘grand challenges’ pursued by the AI research community over the past few decades. We suggest that such challenges lie in the ‘comfort zone’ of AI, whereas debating with humans lies in a different territory, in which humans still prevail, and for which novel paradigms are required to make substantial progress.

Suggested Citation

  • Noam Slonim & Yonatan Bilu & Carlos Alzate & Roy Bar-Haim & Ben Bogin & Francesca Bonin & Leshem Choshen & Edo Cohen-Karlik & Lena Dankin & Lilach Edelstein & Liat Ein-Dor & Roni Friedman-Melamed & As, 2021. "An autonomous debating system," Nature, Nature, vol. 591(7850), pages 379-384, March.
  • Handle: RePEc:nat:nature:v:591:y:2021:i:7850:d:10.1038_s41586-021-03215-w
    DOI: 10.1038/s41586-021-03215-w
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    Cited by:

    1. Alexandros Vassiliades & Nick Bassiliades & Theodore Patkos & Dimitris Vrakas, 2022. "An Open-Ended Web Knowledge Retrieval Framework for the Household Domain With Explanation and Learning Through Argumentation," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 18(1), pages 1-34, January.

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