i agree and disagree with you- a trainer may not understand how or what the connections a neural network will make but any product goes through EXTENSIVE QA bef

i agree and disagree with you- a trainer may not understand how or what the connections a neural network will make but any product goes through EXTENSIVE QA before being launched. thus, a trainer will see all of the different outcomes any nn will make inside of a product, they see the gamut of differences. a user may not see that. additionally, i don't think you give UX designers enough credit. i worked alongside engineers, and met frequently with trainers to talk about what kind of results our prototypes were generating. it was up to me to help articulate what the results meant and how those connections were made. for example- how do you make a long tail result looking different than a short tail one without making it look like a google search? how do you articulate those differences to users so it just doesn't look like a shitty searching algorithm? that is a design problem- articulating those differences visually- not an engineering problem. this is what the article is advocating for.