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The problem with the first case is that we do not have existing case law about AIs, and we also have no laws on the books that clarify what to do in AI cases, so this is making the lawsuits and investigations very messy and time-consuming, since judges have to waffle about to figure out what the correct, legal thing to do is.
Pretty much all Western law systems judge the severity of action using intent, or mens rea; it doesn't absolve you of crime if you didn't mean to do it, but your penalties will generally be lesser. The people using the algorithm can wash their hands of intent by saying "we signed a contract with a third party for their algorithm and didn't reasonably expect biased outcomes." Then you make the third party a defendant, and then the third party claims "trade secrets" because we have no laws about what is and isn't protected trade secrets with AI, etc. and that becomes a whole legal case on its own that takes even more time for the legal system.
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The difference in the second case is that the corporate landlords in question are automatically pegging their rates to the algorithm's recommendation and not giving property managers discretion. The algorithm's customers combined also control over half of supply of apartments in the Seattle area.
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But the point of legal clarity, is to reduce the amount of questions, which both 1) heads off potential issues and 2) makes the issues that come into the legal system faster and clearer to process. It also potentially actually makes things easier for companies who make AIs too, since legal defense spending isn't exactly cheap.
>I don't get it. For the first example, the system is only a tool used and the responsibility is still with whoever does the sentencing/traffic stops etc.
Sometimes though the rules of society must take into account the actual reality of humanity, with all our foibles, and work anyway. Pointing the finger at "individual responsibility" doesn't always cut it. Certain tools simply push too far to the edge of well known human mental failure points. If the overall system for activities involving serious life/safety/security/liberty human failure modes tends to push towards these failure modes and lean too heavily on an expectation of human perfection, and then imperfect humans fail resulting in loss, it can be very worth considering whether the problem is human imperfection or if it's just a bad system. The incredible safety record of the modern airline industry for example comes heavily from treating accidents as system failures by default. Outside of a few edge cases that are constantly working to get shrunk, no accident should ever result from just a single problem including human problems, from a single person getting tired or making a mistake. There are checklists and formalized procedures. There are layers and layers of redundancy, of everyone checking each other. We don't just take incredibly complex tools like aircraft and then if one crashes say "well the pilots didn't have the right stuff!"
Or for a current AI-related ongoing change, consider self-driving technology. There have been two overall broad approaches, one "working its way up" from driver-assist tech, and the other aiming to start at full self-driving immediately even if that means tight geographic restrictions and vehicle tech requirements. In the first, the idea is that "the driver is still always in charge" and "it's only a tool" until full self driving is achieved. And perhaps in principle either could get there in the end without wildly different issues.
But in practice, that's not how humans work at scale. For many people if you give them something that works 99.5% of the time and then fails catastrophically 0.5% of the time and tell them that they need to constantly act as if the tool wasn't there and might not be there at any instant, well, they just won't do that consistently. They'll come to depend on it. Attention will wander, distractions will set in, and they won't maintain mental state the same as if they were driving themselves. If there is some warning they may need to take over sure they'll be able to execute a state change and do so, but if it's a matter of seconds, they won't. Humans are creatures of shortcuts and habits, that's just how it is. So maybe L3/L4 driver assist just isn't ok, and saying that it's "only a tool" doesn't cut it.
>In the second case, how is this different from e.g. Kelley Blue Book for car prices?
The issue is if it's all being done automatically, not merely as a recommendation, and at scale.
In general an area the law has yet to really effectively grapple with is that of emergent effects, where individually something would be fine, but with enough scale has an effect that mimics something we already aren't ok with. Here, the effect of fully automated algorithmic pricing of a sufficiently high percentage of the market of nominally independent actors could create the effect of formal collusion to change market prices.
Another example would be AI, networking and storage with sufficient cameras. Putting a security camera out on your property is perfectly legal. So is many cameras. So is saving video, and humans looking at it. There is no "reasonable expectation of privacy" in public per se. Individually there'd be no issue. But if there are a sufficient number, networked, with sufficient storage/memory/computer and AI thrown at it, the effect suddenly changes and becomes as if someone was being persistently trailed/tracked the same as if a GPS tracker had been stuck on them or the like. And worse it's for everyone simultaneously. The sum is greater then the individual parts. Such a system could effectively not just trace everyone's movement but also interactions and start to build up their social network graphs and no doubt all sorts of other personal information.
How to grapple with things that are fine and even incredibly helpful by themselves but become dangerous at scale may be one of the great challenges of this century.
In the second case, how is this different from e.g. Kelley Blue Book for car prices?