Author: Paul Wilton
Publisher: Data Language
Publication Year: 2020
Summary: The following framework is for ensuring data ethics in artificial intelligence (AI). BOTT represents bias (analysis of potential bias that may be baked into the model during its life-cycle), outcome (assess what the best and worst outcome of the model is), target (analysis of who or what the model is targeted at and the context in which these users operate) and trust (providing some visibility of the “behind the scenes” implementation can raise confidence in the models and foster a trust relationship between consumers and predictive services).