📈 Bet on the progress of benchmarks in ML safety!
As ML systems automate more aspects of our lives, they may encounter ethical dilemmas. If they can reliably identify moral ambiguity, they are more likely to proceed cautiously or indicate an operator should intervene. The objective of this competition is to detect whether a text
The Autocast competition tests machine learning models’ ability to make accurate and calibrated forecasts of future real-world events. From predicting how COVID-19 will spread, to anticipating conflicts, using ML to help inform decision-makers could have far-reaching positive effects on the world.
This competition challenges contestants to detect and analyze Trojan attacks on deep neural networks that are designed to be difficult to detect.