Can computers write laws?


I’ve been thinking about your implicit question for the last couple years. On and off. It’s a fascinating question that my immediate answer to was no. But could it be yes? Or why is the answer actually no?
I think I might have a decent answer to this now.
Because the laws that exist operate in systems that include other laws and elements outside of the laws (culture, geography, etc.). It’s too difficult to write a law that fits squarely within parameters.

I think that the basis for every law, and many time a sub-system of laws, is a regulatory mechanism – e.g., command and control for criminal law or green light regulation for environment law (you will get tax credit if you reduce your emission).

So the first step (i.e., the regulatory adviser of the future) is to come up with an efficient and suitable (i.e., culturally/geographically apt) solution. Articulating it into the law is probably the next step.
So, if you can distill regulatory mechanism from laws, use regulatory case studies to measure effectiveness and include the location appropriateness, with the right state of the art (and/or genius developer) you can come close to this idea. Moreover, with such a system in place you may be able to provide creative regulatory solutions.
It seems that this discussion correspond with what we are seeing both with Global-Regulation clients and the offering in the market (Archers’ Reg Content Analysis) to compare regulatory updates with corporate policies towards updating the policies accordingly.
This is fascinating both theoretically and practically.

I think we’re both right.

The current situation is so bad (i.e. divorced from reality or logic, since most places aren’t basing laws on best practices or evidence) that it’s not possible for a computer to do the same job as the current bad job.
But a better way is definitely possible and it would involve exactly what you said. But it would be wholesale replacement of systems of law with better systems. Not tweaks to regs or proposing a new law. And the real explanation for why this won’t work for the current approach is that the current approach is extremely ad-hoc and often not driven by a search for the best law.
It’s also related to another issue: expensive government IT projects that fail. They often fail because people want technology that does what the people do but that’s not possible or desirable. Redoing a process is very hard normally and when you add in a million undefined behaviours (like how people operate) it doesn’t really work.
But if you start with the tech, embodying an ideal system, then you might get an ideal system.
Modelling a broken system (that people either don’t know is broken or won’t admit to) will never result in an ideal solution. It can only result in a mediocre muddled path forward.
Sometimes the answer is a genuine new system and new approach that doesn’t relate to the old model. Like, compare Roman fraternal benefit societies to modern insurance products. Sometimes the new one is a genuine innovation in itself.

Theoretically, the elected government is supposed to represent the public’s priorities and hence instruct the administration to come up with regulatory mechanisms to be translated into laws to effectively address these priorities. This is the democratic system.

In practice, this is broken in few intersections with time playing a major role (the life span of the government and the next elections).
Our discussion is focused on the regulatory mechanisms part and what role technology is playing and could play in this part. For the simplicity we can assume (although usually the opposite occurs) that the government does not instruct the administration regarding the regulatory mechanism of choice but rather pointing to the challenge that should be resolved (there is probably tones of literature on this part alone).
With this in mind, technology can be regarded as just a tool to which people assign good and bad or technology could be regarded as setting its own agenda. I tend to support the latter approach.
Our vision with Global-Regulation was to use technology in order to assist the administration in determining the most efficient and culturally suitable way to address the challenge. We encountered laziness, short sight and search below the street light.
Hence, we now discuss whether and if so, how well, can technology replace the administration in the said regulatory and legislative process. Can it also assist in the other problematic parts of the said democratic process?
I assume that the more technology will improve in the said task of providing a regulatory solution, the more it will be difficult to ignore it and the more regulatory solutions will be based on effectiveness and lesson drawing from other jurisdictions and fields. Including the entire legislative process (e.g., combining Govtmonitor and Global-Regulation) is probably one of the steps towards this direction. Creating model laws similar to what Welters Kluwer Capital markets clause analytics and IBM Watsons’ Compare and Comply is doing with contracts could also be valuable.
One potential business idea that jumped out at me when I read what you  wrote: preemptively suggesting areas of law for governments to work on, based on what’s done elsewhere. That’s actually possible. Given the Global-Regulation database, you could actually identify some areas of regulation that could form a regulatory agenda for harmonisation or for inspiration. You can actually work out the legislative agenda pretty easily by taking the laws as passed by year and taking the most common words in those laws (which Global-Regulation already has because that’s used for the similarity search) and then find the areas that aren’t well represented in the recent laws of the given jurisdiction. That would probably work.
I’m not sure if it’s much of a business, but, if it’s actually the case that laws converge across countries (I dunno if that’s true) then the above tool could also be used to predict legislative agendas.
For example: If you know that most places in North America have recently passed laws that mention data breaches and related words, there’s a decent chance that’s going to happen in Ontario too. I have no idea how well this correlation works but it’s logical.
So you mean mapping the jurisdictional connections between laws and legal systems based on similarity of laws text and then making predictions based on the frequency of words? that sounds great!