Previously: what is law part 12
Perhaps the biggest form of push-back I get from fellow IT people with respect to the world of law relates to the appealing-but-incorrect notion that in the text of the law, there lies a data model and a set of procedural rules for operating on that data model, hidden inside the language.
The only thing stopping us computerizing the law, according to this line of reasoning, is that we just need to get past all the historical baggage of foggy language and extract out the procedural rules (if-this-then-that) and the data model (definition of a motor controlled vehicle, definition of 'theft', etc.). All we need to do is leverage all our computer science knowledge with respect to programming languages and data modelling, combine it with some NLP (natural language processing) so that we can map the legacy linguistic form of law into our shiny new digital model of law.
In previous parts in this series I have presented a variety of technical arguments as to why this is not correct in my opinion. Here I would like to add some more but this time from a more sociological perspective.
The whole point of law, at the end of the day, is to allow society to regulate its own behavior, for the greater good of that society. Humans are not made from diamonds cut at right angles. Neither are the societal structures we make for ourselves, the cities we build, the political systems we create etc. The world and the societal structures we have created on top of it are messy, complex and ineffable. Should we be surprised that the world of law which attempts to model this, is itself, messy, complex and ineffable?
We could all live in cities where all the houses are the same and all the roads are the same and everything is at right angles and fully logical. We could speak perfectly structured languages where all sentences obey a simple set of structural rules. We could all eat the same stuff. Wear the same clothes. Believe in the same stuff...but we do not. We choose not to. We like messy and complex. It suits us. It reflects us.
In any form of digital model, we are seeking the ability to model the important stuff. We need to simplify - that is the purpose of a model after all - but we need to preserve the essence of the thing modeled. In my opinion, a lot of the messy stuff in law is there because law tries to model a messy world. Without the messy stuff, I don't see how a digital model of law can preserve the essence of what law actually is. The only outcome I can imagine from such an endeavor (in the classic formulation of data model + human readable rules) is a model that fails to model the real world.
In my opinion, this is exactly what happened in the Eighties when people got excited about how Expert Systems could be applied to law. In a nutshell, it was discovered that the modelling activity lost so much of the essence of law, that the resultant digital systems were quite limited in practice.
Today, as interest in Artificial Intelligence grows again, I see evidence that the lessons learned back in the Eighties are not being taken into account. Today we have XML and Cloud Computing and better NLP algorithms and these, so the story goes, will fix the problems we had in the Eighties.
I do not believe this is the case. What we do have today, that did not exist in the Eighties, is much much better algorithms for training machines - not programming them to act intelligently - training them to act intelligently. When I studied AI in the Eighties, we spent about a week on Neural Networks and the rest of the year on expert systems i.e. rules-based approaches. Today's AI courses are the other way around!
Rightly so, in my opinion because there has not been any great breakthrough in the expert systems/business rules space since the Eighties. We tried all the rules-based approaches in the Eighties. A lot of great computer science minds worked on it. It came up short in the real world of law.
When you combine the significant advances in Neural Network approaches with all the compute advantages of cloud and the ready availability of lots and lots of digital data, things get interesting again. This is where we are today. And it is very interesting indeed.
I numbered this blog post "12a", for a reason that is hopefully both humorous and relevant. I know of both legal texts and legal business processes that avoid the number 13. I know of a legal text with so many sub-paragraphs that the number 666 was needed, and 665a was used instead. This kind of thing drives rules-based computing mad but is exactly the kind of human footprint that is literally all over the world of law.
The human touch can be seen in all its splendor in the area of legal fictions. Everything from life insurance claims to resigning from office uses forms of logic that are very foreign to the world of classic computing concepts of rules and data models.
Yet there the are... in all their messy, complex, splendidly human glory. Spend a few moments with the Chiltern Hundreds. It is worth your time . Spend some time thinking about how we humans can both navigate ambiguity when we have to, or when it suits us, and - when it suits us - create new ambiguity. Then read about contra proferentem.
Now we can refuse to believe the messy ambiguity and complexity is intrinsic and spend our time trying to remove it with computers - as we did in the Eighties. Or we can take a deep breath, dive in and embrace it.
I recommend the latter. Next up: What is Law? - Part 14.