We are no longer accepting submissions. We'll get in touch with winners and make a post about winning proposals sometime in the next month.

ARC recently released a technical report on eliciting latent knowledge (ELK), the focus of our current research. Roughly speaking, the goal of ELK is to incentivize ML models to honestly answer “straightforward” questions where the right answer is unambiguous and known by the model.

ELK is currently unsolved in the worst case—for every training strategy we’ve thought of so far, we can describe a case where an ML model trained with that strategy would give unambiguously bad answers to straightforward questions despite knowing better. Situations like this may or may not come up in practice, but nonetheless we are interested in finding a strategy for ELK for which we can’t think of any counterexample.

We think many people could potentially contribute to solving ELK—there’s a large space of possible training strategies and we’ve only explored a small fraction of them so far. Moreover, we think that trying to solve ELK in the worst case is a good way to “get into ARC’s headspace” and more deeply understand the research we do.

We are offering prizes of $5,000 to $50,000 for proposed strategies for ELK. We’re planning to evaluate submissions received before February 15.

For full details of the ELK problem and several examples of possible strategies, see the writeup. The rest of this post will focus on how the contest works.

Contest details

To win a prize, you need to specify a training strategy for ELK that handles all of the counterexamples that we’ve described so far, summarized in the section below—i.e. where the breaker would need to specify something new about the test case to cause the strategy to break down. You don’t need to fully solve the problem in the worst case to win a prize, you just need to come up with a strategy that requires a new counterexample.

We’ll give a $5,000 prize to any proposal that we think clears this bar. We’ll give a $50,000 prize to a proposal which we haven’t considered and seems sufficiently promising to us or requires a new idea to break. We’ll give intermediate prizes for ideas that we think are promising but we’ve already considered, as well as for proposals that come with novel counterexamples, clarify some other aspect of the problem, or are interesting in other ways. A major purpose of th...

Luca De Leo

Luca De Leo

Luca De Leo

Luca De Leo