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Comment by tclark225 | Hacker News Reader

I definitely agree with this, but how could you specifically change the laws in this case such that they are still, by some measure, "fair" and "just"? Most people would probably agree that there is no reason to adhere to the letter of driving laws all the time. Speeding on an empty highway to get somewhere more quickly is mostly harmless. Running a red light in a dangerous neighborhood might be safer than waiting. To the point of the "real" laws, such violations are probably most often prosecuted when they result in danger to the driver or others. You could certainly generalize these examples from driving to a variety of other laws.

I guess the question is, you can beat the drum about this, but to what tune? What's the answer? How could a self-driving car decide when it is okay to break traffic rules without a certain level of human discretion? How could the laws be re-written such that the effect is the same?

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What if we step outside of the law in organizing our societies? Law being an abstraction, any usefulness it has must be realized in its substrate: human relationships. When law fails, it is because the abstraction has leaked. We can find remedy by working with the fundamental thing and restoring the abstraction.

In NYC, there is an unspoken more that people who wish to stand on subway escalators should stay on the right so that people who wish to walk up escalators can use the left side. This is not a law; it is not derived from authority; it is not enforced with coercion. The worst you'll get, probably, is a snide 'excuse me'.

Authority is a degenerate form of respect. Law is a degenerate form of consensus. Arbitration is a degenerate form of mediation. Holding ideas accountable to human beings is superior to holding human beings accountable to ideas. At the end of the day, we are only accountable to each other, not the law.

"definitely agree with this, but how could you specifically change the laws in this case such that they are still, by some measure, "fair" and "just"?"

This is a really deep question, which is part of why I dropped the entire discussion on the topic in my initial post so I wouldn't get too sidetracked.

One problem we have is that if we can encode laws into computer programs, which is to say, basically math, we also become subject to the problems that creates. For instance, raise your hand if you enjoy min-maxing in an RPG or MMO or something. Now, keep your hands raised and add a big evil grin for me if you'd love the opportunity to minmax real laws with such impunity.

In theory, even human enforcement is a computational system which could in theory be attacked the same way, but in its own weird way, its own enormous complexity and frankly at times random enforcement prevents the really terrible gaming of the law by preventing an attacking entity from fully accurately simulating the system for the purposes of attacking it.

(I said something that may trigger some knee-jerk reactions in some people about "gaming" the system. But however bad you think it is in the real world... and I would agree that it is bad in many places... it has nothing on the gaming you can do on something specified with programmatic precision and with no human in the loop to prevent truly stupid states from emerging. This isn't making your way to the top over the years by bribery and flattery, this is waking up one day and discovering that one person has literally all the money now.)

You'll want to encode enforcement rules in the laws themselves. Fundamentally, our laws really aren't constraints on what you can do, but guidelines for what you can enforce. You need to take it a step further and write down what you will enforce.

How do you guarantee the enforcement of the rules of enforcement? The fundamental problem is a vicious circle. The abstraction of law leaks.

Every abstraction leaks. That's why they are abstractions and not 'actuals.'

What you do is try it, and when it fails, you manage the failure and modify your system.

Different people have different idea what the actuality of law is. Most people (as Baudrillard would argue) don't ever work with the actuality. Others, mainly the powerful, are quite happy enough to fix failures of the law with copious amounts of force. The abstraction tends to leak bullets. It is very important to emphasize that the law is less than sacred, even an annoyance, to undermine those who will enforce it with the wrong actuality.

I fail to see your point.

Attempting to maintain the abstraction of law by fixing it when it leaks has the hazard of bad actors sneaking undesirable elements into our social structures, like violently maintained hierarchy. Adopting a mindset that law is fundamentally flawed and its language is essentially incoherent helps mitigate this possibility.

An example of such incidence is when people trust the police to the point that they prejudge conflicts involving the police on the basis that they represent the law, and the law is good, therefore the police are good. This is still happening.

But execution and legislation are two separate branches, why are you creating a tightly coupled relationship between them? Writing down explicit paths of enforcement sounds almost guaranteed to be incomplete, and would result in having a high degree of agency being removed from enforcement, because they would now have to follow literal conditions no matter what. Conditions which will almost certainly account for an insufficient number of variables than the ones that will be encountered in reality.

>But execution and legislation are two separate branches,

And cars don't drive themselves. So I guess that solves our problem.

You can read my post below (https://news.ycombinator.com/item?id=10154344) to see how I'd start addressing your other concerns. Basically, if an enforcement officer recognizes some new variables, they can write them down in the law and then enforce it.

Computer programs are just human-dictated logic, so we can program the same decision-making processes into computers. A logical way to do this would be to train mapping computers the same way we do now, by allowing them to learn from human drivers. Just like how Google hires drivers with cameras to take pictures of streets, we can start with semi-autonomous cars which compare their programmed decisions with the decisions of the drivers and analyze differences. Afterward, they could ask the driver questions about why their behavior was different from what was expected in a programmatic way. Trends could be analyzed, and suggestions for altering the driving logic could be incorporated by programmers.

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