This is the first in a series of posts about the way we think about programming, the influence these ideas have on how we write code and what languages we choose, and why I like the functional programming paradigm in general and Haskell in particular.

Consumer notification: I've worked as a programmer for decades, but for many of those years I wrote bad code in Perl, and I've had no formal training in software design or computer science. These posts should be taken as part sketchy meditation on the philosophy of programming, part mea culpa. I don't want to add another "burn down software and start again" rant to the literature.

An unfair case

This first post is a digression into an unfairly extreme case of how IT people misunderstand law, and a confession. Here is the the extreme case, taken from the manifesto of Ethereum, a project which is planned as a replacement for both Bitcoin, and, speaking of burning things down and starting again, the civil law:

The authors of laws and the writers of contracts face a special kind of challenge. Ideally, there should never be any confusion about the meaning of the agreement. But laws are written with words, and words are famously imprecise.

So these are big problems with traditional law. Agreements are ambiguous. And enforcement is hard.

Ethereum solves both these problems. It does this with the marriage of two special ingredients: a digital currency, and a complete programming language. Let’s look at both.

This is an extreme example of what Evgeny Morozov calls "solutionism": the belief that apparently intractable problems will melt away given a correct technological framework. That's not why I'm quoting it here, though, and this is where the confession comes in. I studied law for my undergraduate degree. I never qualified as a solicitor, and only spent a little over a year in a legal workplace before I realised that the profession didn't suit my temperament. So I'm not equipped to give any kind of advice. However, as someone who studied law after they had already learned the elements of programming, I can recognise the way IT geeks misunderstand the law from a mile away. I know this misunderstanding intimately, having suffered from it. It can be summed up in a sentence:

Legal rules are sufficiently like a computer progam that the one can be analysed and reformed using techniques from the other.

This is one of those seductive ideas that's superficially plausible but wrong. It's wrong in a way which makes it very bad for analysing law or politics, and in one way or another, most of the attempts by IT people to grapple with these fields, whether these are scornful dismissals or quixotic pledges of reform, can be reduced to it.

The Ethereum blogger thinks that they've found the worst problem with law: that it's written in what IT people refer to as "natural language" (ie, language), and "words are famously imprecise". The solution to this problem is a legal system in which laws are expressed not in ambiguous, clumsy language, but in the clean precision of code.

It's my contention that this is not only a bad way to think about both language and the law, but is also a bad way to think about computers and software.


There's a metaphor which is used to introduce kids to computers: I can't remember where I first encountered it, possibly in one of the many books I bought from Dick Smith which were full of printouts of BASIC programs to be typed into a TRS-80 (if you didn't understand the last clause of that sentence it roughly translates to "I am old as balls"). The metaphor is that the computer is a willing but idiotic servant: it will do everything you tell it to, but only exactly what you tell it to, even if your instructions are wrong. This is not a bad way to introduce a ten-year-old to programming, particularly if they've got the impression from pop culture that computers are smarter than people.

The metaphor is baked into much of the terminology of the trade:

  • command
  • instruction
  • program
  • programming language
  • imperative programming
  • execution

I'm not saying that developers genuinely believe that they're telling a little homunculus inside the computer what to do: I'm saying that the way they explain and write and think about their code is unconsciously built around the metaphor of telling a little homunculus what to do.

It's this metaphor which the IT style of reasoning about law is appealing to: programs are sets of precise, unambiguous instructions, so if we can somehow embody laws in code, we can build a legal system which is free from ambiguous language (and, perhaps, lawyers).

No-one home

The metaphor hides a crucial aspect of human language: it is always addressed to a person. By this I don't just mean that human listeners bring to bear a huge, submerged mass of assumptions and tacit knowledge which allow them to comprehend language. I mean that all human language is part of a dialogue between persons who are capable of action and who are members of a community. The imaginary homunculus to whom a program is addressed is something like an ideal slave: the programmer (the master) provides a set of instructions to cover every eventuality, and the computer follows them.

Contracts, and laws in general, like all examples of human language, are not like this. The essence of a contract is that of mutual promise, usually a promise to pay in consideration of a promise to provide either goods, services or labour: the contract per se is a formal recognition of an agreement between persons, and it would make no difference if the contract were expressed as a computer programme, rather than as a template filled out by a bored junior solicitor, in a case where the parties unintentionally misunderstood one another, or where one was seeking to actively deceive the other. It's important to be diligent in checking a contract for errors, omissions or ambiguities, but removing these alone wouldn't obviate the need for a law of contract.

Hard cases and corner cases

Another way of looking at the quality which social and legal systems possess, and their radical difference from the systems governed by programming languages, is expressed in the maxim "hard cases make bad law". (The existence and importance of maxims in law, of precepts which cannot be reduced to simple rules, but instead embody a kind of general principle, also proves my point.) "Hard cases make bad law" is a sort of counterargument to the idea that the the exception proves the rule: it expresses the idea that the vast majority of cases are unexceptional, and that the particular circumstances of a celebrated or notorious case are not necessarily the best way to understand the principles behind a law.

One of the distinctive ways in which IT people go wrong when they try to understand legal ideas is to immediately go for hard cases: anyone who has spent ten minutes talking about intellectual property law with a nerd should recognise our tendency to immediately identify and exaggerate the most absurd consequences of copyright that we can think of. This is a misapplication of an honourable and useful trait: the ability to identify "corner cases" - situations, or inputs, which will tend to produce bugs, either because the programmer hasn't anticipated them, or through pure cussedness. The job of a quality assurance engineer is to find corner cases, and is admirably summed up in this tweet:

In law, and in the much broader field of social relations which take place in areas which are governed by law, many corner cases can be resolved using common sense - which is not an unproblematic idea at all, but which is useful for expressing the idea that these social relations are not taking place between automata, but between human beings who are capable of understanding one another and are part of some sort of community of practice.

Hard cases may make bad law, but corner cases make good software: they are also very difficult to exhaustively deal with using imperative programming, which is the formal name of the programming paradigm which I've been caricaturing under the name of "homunculus". Imperative programming not only implies a willing and brainless slave, but also an omniscient master, in the form of the programmer. While testing and quality assurance can go a long way to remedying this, the real solution is to get rid of the homunculus altogether, by shifting to a paradigm which is better at capturing exactly what we are trying to do when we program computers.

Keep reading: Part 2 - State