Literature DB >> 35789321

Human-centred mechanism design with Democratic AI.

Raphael Koster1, Jan Balaguer1, Andrea Tacchetti1, Ari Weinstein1, Tina Zhu1, Oliver Hauser2, Duncan Williams1, Lucy Campbell-Gillingham1, Phoebe Thacker1, Matthew Botvinick1,3, Christopher Summerfield4,5.   

Abstract

Building artificial intelligence (AI) that aligns with human values is an unsolved problem. Here we developed a human-in-the-loop research pipeline called Democratic AI, in which reinforcement learning is used to design a social mechanism that humans prefer by majority. A large group of humans played an online investment game that involved deciding whether to keep a monetary endowment or to share it with others for collective benefit. Shared revenue was returned to players under two different redistribution mechanisms, one designed by the AI and the other by humans. The AI discovered a mechanism that redressed initial wealth imbalance, sanctioned free riders and successfully won the majority vote. By optimizing for human preferences, Democratic AI offers a proof of concept for value-aligned policy innovation.
© 2022. The Author(s).

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Year:  2022        PMID: 35789321      PMCID: PMC9584820          DOI: 10.1038/s41562-022-01383-x

Source DB:  PubMed          Journal:  Nat Hum Behav        ISSN: 2397-3374


  9 in total

1.  The competitive advantage of sanctioning institutions.

Authors:  Ozgür Gürerk; Bernd Irlenbusch; Bettina Rockenbach
Journal:  Science       Date:  2006-04-07       Impact factor: 47.728

2.  How AI can be a force for good.

Authors:  Mariarosaria Taddeo; Luciano Floridi
Journal:  Science       Date:  2018-08-24       Impact factor: 47.728

Review 3.  Normative foundations of human cooperation.

Authors:  Ernst Fehr; Ivo Schurtenberger
Journal:  Nat Hum Behav       Date:  2018-07

Review 4.  The description-experience gap in risky choice.

Authors:  Ralph Hertwig; Ido Erev
Journal:  Trends Cogn Sci       Date:  2009-10-14       Impact factor: 20.229

5.  A clinically applicable approach to continuous prediction of future acute kidney injury.

Authors:  Trevor Back; Christopher Nielson; Joseph R Ledsam; Shakir Mohamed; Nenad Tomašev; Xavier Glorot; Jack W Rae; Michal Zielinski; Harry Askham; Andre Saraiva; Anne Mottram; Clemens Meyer; Suman Ravuri; Ivan Protsyuk; Alistair Connell; Cían O Hughes; Alan Karthikesalingam; Julien Cornebise; Hugh Montgomery; Geraint Rees; Chris Laing; Clifton R Baker; Kelly Peterson; Ruth Reeves; Demis Hassabis; Dominic King; Mustafa Suleyman
Journal:  Nature       Date:  2019-07-31       Impact factor: 49.962

6.  Humans rely more on algorithms than social influence as a task becomes more difficult.

Authors:  Eric Bogert; Aaron Schecter; Richard T Watson
Journal:  Sci Rep       Date:  2021-04-13       Impact factor: 4.379

7.  A shallow defence of a technocracy of artificial intelligence: Examining the political harms of algorithmic governance in the domain of government.

Authors:  Henrik Skaug Sætra
Journal:  Technol Soc       Date:  2020-06-08

8.  Adversarial vulnerabilities of human decision-making.

Authors:  Amir Dezfouli; Richard Nock; Peter Dayan
Journal:  Proc Natl Acad Sci U S A       Date:  2020-11-04       Impact factor: 11.205

9.  Highly accurate protein structure prediction with AlphaFold.

Authors:  John Jumper; Richard Evans; Alexander Pritzel; Tim Green; Michael Figurnov; Olaf Ronneberger; Kathryn Tunyasuvunakool; Russ Bates; Augustin Žídek; Anna Potapenko; Alex Bridgland; Clemens Meyer; Simon A A Kohl; Andrew J Ballard; Andrew Cowie; Bernardino Romera-Paredes; Stanislav Nikolov; Rishub Jain; Demis Hassabis; Jonas Adler; Trevor Back; Stig Petersen; David Reiman; Ellen Clancy; Michal Zielinski; Martin Steinegger; Michalina Pacholska; Tamas Berghammer; Sebastian Bodenstein; David Silver; Oriol Vinyals; Andrew W Senior; Koray Kavukcuoglu; Pushmeet Kohli
Journal:  Nature       Date:  2021-07-15       Impact factor: 49.962

  9 in total
  1 in total

1.  Designing all-pay auctions using deep learning and multi-agent simulation.

Authors:  Ian Gemp; Thomas Anthony; Janos Kramar; Tom Eccles; Andrea Tacchetti; Yoram Bachrach
Journal:  Sci Rep       Date:  2022-10-08       Impact factor: 4.996

  1 in total

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