Pragmatic AI Explanations
Shi Feng · Chenhao Tan
Abstract
We use the Rational Speech Act framework to examine AI explanations as a pragmatic inference process. This reveals fatal flaws in how we currently train and deploy AI explainers. To evolve from level-0 explanations to level-1, we present two proposals for data collection and training: learning from L1 feedback, and learning from S1 supervision.
Chat is not available.
Successful Page Load