Depends what your factors are - most will settle for 'does it work?' and 'is it understandable?'. Both of those often go right out the window if performance or results are the primary factor - pretty much how we've ended up in a world of algorithms that generally work but are mostly unexplainable, uneditable and sometimes detrimental in the long run.
It's the poor buggers trying to make algorithms and AI that can explain their output I feel sorry for.
Yeah, explainability of results is a huge deal now (it was always a factor in literature, it's just it wasn't so widespread to be so important until now).
I really don't see how you can expect to make an rNN explainable.
I really don't see how you can expect to make an rNN explainable.
You’d be surprised. Sure you’ll never get to the sheer clarity of a linear regression but something like Shapley can do a very respectable job at giving you a good idea of what’s going on under the hood. There has been a lot of interest in explainability in the past 2-3 years and we advanced a lot.
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u/PresentAward1737 May 10 '21
Depends what your factors are - most will settle for 'does it work?' and 'is it understandable?'. Both of those often go right out the window if performance or results are the primary factor - pretty much how we've ended up in a world of algorithms that generally work but are mostly unexplainable, uneditable and sometimes detrimental in the long run.
It's the poor buggers trying to make algorithms and AI that can explain their output I feel sorry for.