Answers are grounded in this paper and cite their sources.
Explores the importance of model transparency in trust and decision-making regarding machine learning applications.
Despite widespread adoption, machine learning models remain mostly black boxes. Understanding the reasons behind predictions is, however, quite important in assessing trust, which is fundamental if one plans to take action based on a prediction, or when choosing whether to deploy a new model. Such understanding also provides insights into the model, which can be used to transform an untrustworthy model or prediction into a trustworthy one.
No takes yet. Share an insight, caveat, or question.
Ribeiro et al. (2016) studied this question.
Synapse has enriched 8 closely related papers on similar clinical questions. Consider them for comparative context: