Oh, and how that is related to current practice (because I lost my train of thought somewhere) is that 'modern' (=ML-based) experimental sentencing guideline sy

Oh, and how that is related to current practice (because I lost my train of thought somewhere) is that 'modern' (=ML-based) experimental sentencing guideline systems try to overcome this 'subjective bias' by injecting an 'objective subjective bias' by using ML methods. So basically by looking at many more circumstances and training the former 'points' system using ML, so in a way automatically deriving what used to be set by manually devised guidelines (as crude as they were) from past data - under the assumption that our past data is somewhat objective, and/or because we know it wasn't, additionally trying to correct for past biases. It's easy to see the problems with this approach and I don't have to rehash them here; and much of the interesting (academic) work here is in rebalancing and fixing the biases; but that is research, not something that is ready for actual use in democratic societies (not that that has stopped some places from using them anyway...). I'm not convinced it's even possible and any such system will invariably be very opaque. Imagine, if judges and prosecutors already find what was essentially a decision tree too inflexible and incomprehensible, how they would experience an ML model! Imagine being the person who has to explain how such a new model works to a classroom of lawyers! Strong men have wept for less. Anyway so the Dutch judicial system is now back to a system of spelled out sentencing guidelines in textual form, systematised by criminal law area, like there is one for cybercrimes, etc. With some tables that probably used to be encoded in a DBase file (that's how old the former software based tool was). But it seems that the fact that this information is now consumed from their original texts, gives the impression that there is more room for 'customization' - although there isn't actually that much more room, and in another 15 years we'll go full circle I suspect and get someone to code up the guidelines again... So these texts are still just algorithms but spelled out; and the former method was to have software to help with 'interpreting' those textual algorithms; yet nobody called them out for the things modern ML-based systems are called out. But still I think this is a very clear example of how the word 'algorithm' has become overloaded in its meaning - not just become broader, but has actually shifted in meaning depending on the context in which it's used.