4 ms·

I'm pretty sure these kinds of regulations have existed in the US for a while too. According to [1], having an algorithm be interpretable (which NNs aren't) is

I'm pretty sure these kinds of regulations have existed in the US for a while too. According to [1], having an algorithm be interpretable (which NNs aren't) is a legal requirement in any financial decisions subject to anti-discrimination laws. In this case, it doesn't necessarily mean there will be a HUGE CLASH. We will either turn to more interpretable AI, or continue developing more and more interpretability techniques for deep learning, which has been an area of very active research in the recent years. [1] https://www.cs.princeton.edu/picasso/mats/Book_Schapire.pdf https://www.cs.princeton.edu/picasso/mats/Book_Schapire.pdf page 664

Zak 10y ago
I'm not sure if anti-discrimination laws require that the outcome be explainable as long as none of the inputs involve legally protected classes.
- dragonwriter 10y ago
  > I'm not sure if anti-discrimination laws require that the outcome be explainable as long as none of the inputs involve legally protected classes. Yes, in general anti-discrimination law in the US, a disparate impact along a protected axis usually means that a decision must be justified on some neutral grounds. If there is no disparate impact attached to -- not just no express input related to -- some protected axis of discrimination, then, no, the outcome doesn't need to be explained.