You’ve just rejected an idea because your interpretation of it takes a severe path where use of randomness is incompatible with documenting an algorithm. Flowchart the process “flip a coin” to demonstrate why this world-ending interpretation isn’t so.
Come on, where did systemd come into the picture? Don't be obtuse.
No one is saying that the algorithm should be three if statements that the jury can understand in 30 seconds.
As an example, I'd say that doing maximum bipartite matching using factors like proximity, rating, etc, for drivers/gigs is a reasonable thing that you can explain to the jury. It's not that they have to understand the proof for the algorithm itself.
The most if not only important thing is that you should be be able to convince the jury that you're not including criteria in the matching process that is actively or accidentally malicious towards the gig workers.
The problem with high dimensional LP solvers, optimisation problems, PID controllers, or other systems with a feedback loop is that it's very tempting to include revenue (or a confounding factor thereof) into your objective. This can, as you might imagine, lead to something that harms the workers.
On the other hand, worker satisfaction is much much harder to quantify and is not included in the objectives at all usually. Number of active work-hours and simple things like that are not typically a good signal because of the fundamental nature of most gig work in this context -- they are doing it out of necessity, and taking a risk losing out on employee protections.
> where did systemd come into the picture? Don't be obtuse.
>>> if the algorithm cannot be explained in easily understandable language (as determined by a jury), then it's illegal.
It came here and because just the other day there was a big thread on systemsd where plenty of people were complaining about how difficult it was[0]. I'm really not convinced that the average person could understand systemd.
The thing is that the simpler you explain it, the less informed the jury is. So the question is if you can find an explanation that is sufficient to make informed decisions. The reality of this is that this then becomes more dependent on who's a smooth talker. Who can convince the jury that they understand and understand in the way they want to. There's a big bias in the balance of power here. Details are hard to explain and if anything relies on something subtle, well you're fucked. So all you need to do to abuse employees is make the algorithm sufficiently complex and get a smooth talking lawyer.
> The problem with high dimensional LP solvers, optimisation problems, PID controllers, or other systems with a feedback loop is that it's very tempting to include revenue
Some of these are fully interpretable, others are not. But most people have a really hard time understanding high dimensions. Where a straight line isn't "straight" (geodesic) or how the average can be a meaningless value, or how a unit ball inscribed in a unit cube can extend out of the unit cube. Problem with high dimensions is that it is really hard to explain without math because you no longer can rely on any visualization reference.
> So all you need to do to abuse employees is make the algorithm sufficiently complex and get a smooth talking lawyer.
Yeah that is true. I was speaking more to the importance of interpretability in these things, and how the lack of it leads to bad incentives very quickly.
> Problem with high dimensions is that it is really hard to explain without math because you no longer can rely on any visualization reference.
Yep, and the co-dependencies also tend to become very hard to reason about.
