Several months ago I was taken by the idea that in the future (and maybe depending on how you think about it, already in the present) laws should be written as computer algorithms. While the idea that “code is law” and that technology regulates is by no means original, what I thought perhaps provocative is the positive case for the (re-)implementation of the fundamental laws of the city or state in software code.
The argument went roughly like this:
- Effective law must control a complex society
- Effective control requires social and political prediciton.
- Unassisted humans are not good at social and political prediction. For this conclusion I drew heavily on Philip Tetlock’s work in Expert Political Judgment.
- Therefore laws, in order to keep pace with the complexity of society, should be implemented as technical systems capable of bringing data and machine learning to bear on social control.
Science fiction is full of both dystopias and utopias in which society is literally controlled by a giant, intelligent machine. Avoiding either extreme, I just want to make the modest point that there may be scalability problems with law and regulation based on discourse in natural language. To some extent the failure of the state to provide sophisticated, personalized regulation in society has created myriad opportunities for businesses to fill these roles. Now there’s anxiety about the relationship between these businesses and the state as they compete for social regulation. To the extent that businesses are less legitimate rulers of society than the state, it seems a practical, technical necessity that the state adopt the same efficient technologies for regulation that businesses have. To do otherwise is to become obsolete.
There are lots of reasons to object to this position. I’m interested in hearing yours and hope you will comment on this and future blog posts or otherwise contact me with your considered thoughts on the matter. To me the strongest objection is that the whole point of the law is that it is based on precedent, and so any claim about the future trajectory of the law has to be based on past thinking about the law. Since I am not a lawyer and I know precious little about the law, you shouldn’t listen to my argument because I don’t know what I’m talking about. Q.E.D.
My counterargument to this is that there’s lots of academics who opine about things they don’t have particular expertise in. One way to get away with this is by deferring to somebody else who has credibility in field of interest. This is just one of several reasons why I’ve been reading “The Path of the Law“, a classic essay about pragmatist legal theory written by Supreme Court Justice Oliver Wendell Holmes Jr. in 1897.
One of the key points of this essay is that it is a mistake to consider the study of law the study of morality per se. Rather, the study of law is the attempt to predict the decisions that courts will make in the future, based on the decisions courts will make in the past. What courts actually decide is based in part of legal precedent but also on the unconsciously inclinations of judges and juries. In ambiguous cases, different legal framings of the same facts will be in competition, and the judgment will give weight to one interpretation or another. Perhaps the judge will attempt to reconcile these differences into a single, logically consistent code.
I’d like to take up the arguments of this essay again in later blog posts, but for now I want to focus on the concept of legal study as prediction. I think this demands focus because while Holmes, like most American pragmatists, had a thorough and nuanced understanding of what prediction is, our mathematical understanding of prediction has come a long way since 1897. Indeed, it is a direct consequence of these formalizations and implementations of predictive systems that we today see so much tacit social regulation performed by algorithms. We know now that effective prediction depends on access to data and the computational power to process it according to well-known algorithms. These algorithms can optimize themselves to such a degree that their specific operations are seemingly beyond the comprehension of the people affected by them. Some lawyers have argued that this complexity should not be allowed to exist.
What I am pointing to is a fundamental tension between the requirement that practitioners of the law be able to predict legal outcomes, and the fact that the logic of the most powerful predictive engines today is written in software code not words. This is because of physical properties of computation and prediction that are not likely to ever change. And since a powerful predictive engine can just as easily use its power to be strategically unpredictable, this presents an existential challenge to the law. It may simply be impossible for lawyers acting as human lawyers have for hundreds of years to effectively predict and therefor regulate powerful computational systems.
One could argue that this means that such powerful computational systems should simply be outlawed. Indeed this is the thrust of certain lawyers. But if we believe that these systems are not going to go away, perhaps because they won’t allow us to regulate them out of existence, then our only viable alternative to suffering under their lawless control is to develop a competing system of computational legalism with the legitimacy of the state.