Resolution

By "all" Atari games we mean the more than 50 games listed on the EFF AI Progress Measurement page.

(This should be interpreted as: "there exists one system which can play all games (though possibly including retraining)", and not "for each game there exists one system which can play it".)

Resolution date will be set to the earliest of the following dates:

• Publication date of a credible paper, blog-post, video or similar demonstrating an AI achieving the feat in question

• A credible paper, blog-post, video or similar, referencing a date earlier than its publication date, by which the feat was achieved (similar to how DeepMind kept AlphaGo's victory over European champion Fan Hui secret from October 2015 to January 2016, in order to coincide with the publication of the corresponding Nature paper)

• A date such that an expert council of several senior AI researchers agree (by majority vote) that it is >=95% likely that the feat could have been carried out by that date. This means not just the date when the computational resources and algorithmic insights were available, but the date were they could have been fully deployed to solve the problem. For example, think the end and not the beginning of the AlphaGo project. [1] [2]

[1] The point of this counterfactual resolution condition is as follows. Not all trajectories to advanced AI pass by a single agent playing all Atari games. There might be a point at which it is clear that the feat in the question is achievable, even though no one has actually bothered to implement the experiment.

This is similar to how the release of the AlphaZero agent (playing chess, Go and shogi) should give us >=95% confidence that it is possible to play Othello at superhuman level without domain-specific knowledge, even though no one (to the author's knowledge) ran that experiment.

[2] More details regarding the council composition will be announced on Metaculus in the coming months.