Human-centered mechanism design with Democratic AI
π Description
1 Human-centered mechanism design with Democratic AI Authors: Raphael Koster1?, Jan Balaguer1?, Andrea Tacchetti1, Ari Weinstein1, Tina Zhu1, Oliver Hauser2, Duncan Williams1, Lucy Campbell-Gillingham1, Phoebe Thacker1, Matthew Botvinick1,3 and Christopher Summerfield1,4 Affiliations: 1 Deepmind, London, UK 2 Department of Economics and Institute for Data Science and Artificial Intelligence, University of Exeter, Exeter, UK 3 Gatsby Computational Neuroscience Unit, University College London, London, UK 4 Department of Experimental Psychology, University of Oxford, Oxford, UK *Corresponding author. Email: [email address redacted] ? These authors contributed equally to this work 2 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 hu...
π Game Impacts
Not verified in gameWhich variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.
| Variable | Direction | Condition |
|---|---|---|
| Research | proposed: up | Always |
| Papers | proposed: up | Always |
| Vibey Doom | proposed: up | Always |
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