Most of the methods used for this are basically large matrices with no human understandable way to represent them. Getting the values would only let you recalculate the results, not discover why the results were produced.
Most of the methods used for this are basically large matrices with no human understandable way to represent them. Getting the values would only let you recalculate the results, not discover why the results were produced.
ML is, afaik, considered too much of "curve fitter" to actually simulate or analyze anything novel instead of rehashing of past events, making it useless in cases like this.
It also allows you to calculate new results, which can be used to detect when the system is actually wrong, and to detect bias.
And actually, yes you can discover why the results were produced, because models leak a ton of data about the training set.
The simple and affordable solution is to ban the use of artificial stupidity in legal decision making.
IMO, if you're worried about a black box AI juror, we all ready have that--they are called (human) jurors.