MIT and IBM Develop New Tool To Help Choose the Right Method for Evaluating AI Models — Selecting the right method |
MIT and IBM researchers have created ‘saliency cards’ to aid in the selection of appropriate saliency methods for machine learning models. These cards detail a method’s functionalities and performance characteristics, facilitating users in making informed choices, ultimately improving understanding of their models’ behavior.
and IBM Research created a tool to help users choose the best saliency method for their particular task. They developed saliency cards, which provide standardized documentation of how a method operates, including its strengths and weaknesses and explanations to help users interpret it correctly. “Saliency cards are designed to give a quick, glanceable summary of a saliency method and also break it down into the most critical, human-centric attributes. They are really designed for everyone, from machine-learning researchers to lay users who are trying to understand which method to use and choose one for the first time,” says Boggust.
“It will tell you that any black pixels in your image aren’t important, even if they are, because they are identical to that meaningless baseline. This could be a big deal if you are looking at X-rays since black could be meaningful to clinicians,” says Boggust.
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