What is Interpretable? Using Machine Learning to Design Interpretable Decision-Support Systems

no code implementations • 27 Nov 2018 • Owen Lahav, Nicholas Mastronarde, Mihaela van der Schaar

Our results demonstrate that ML experts cannot accurately predict which system outputs will maximize clinicians' confidence in the underlying neural network model, and suggest additional findings that have broad implications to the future of research into ML interpretability and the use of ML in medicine.

BIG-bench Machine Learning Reinforcement Learning (RL)