Intelligent legal technology in Finnish courts by 2025?

In Finland, the select committee on judicial reform presented its report to the Minister of Justice today. (Press release in Finnish, Swedish.) The report, responding to the political pressure of making reducing judicial expenditures by 2025 while at the same time making trials more expedient (Finland has quite a track record from the ECHR in this respect), contains a fair share of controversially controversial recommendations and proposals, including the total elimination of lay judges and possibly even the two-track system of general and administrative courts throughout the system, but then there is also this:

In some types of cases the preparation processcould be more strongly computer-supported. For example, when the elements of certain crimes are met, the system could automatically offer relevant phrasings as motivations, which could ease up the burden of processing simple high-volume cases, such as drunk driving. This could reduce routine work while at the same time safeguarding the high quality of the decisions.

(Finnish original: Osassa asioita voidaan valmistelua tukea tietojärjestelmän avulla nykyistä voimakkaammin. Esimerkiksi tiettyjen tunnusmerkistöjen täyttyessä tietojärjestelmä voisi automaattisesti tarjota asiaan liittyviä fraasiperusteluja, mikä voisi keventää suuren volyymin yksinkertaisten juttujen, kuten rattijuopumukset, käsittelyä. Näin voitaisiin vähentää rutiiniluontoista työtä ja samalla kuitenkin varmistaa päätösten korkea laatu. (p. 18))

The general sad state of court ICT in Finland was also highlighted by the Minister in her reply and also raised earlier independently in a short interview with her in Hufvudstadsbladet a week or two ago. The Finnish intelligent legal technology lobby (ahem) is officially pleased.

(If this is your first encounter with the words “intelligent legal technology”, you may want to take a look at this article of mine from the latest IPRinfo magazine.)

What is Artificial Intelligence?

Prompted by the discussion at a presentation I gave yesterday on intelligent legal technology (titlend Älykäs oikeusteknologia, ie. in Finnish, for once) I guess I feel the need to export a part of the neural network that subsequently emerged in the form of a blog post. I was asked to define artificial intelligence, and since I refused to provide a definition, I was asked again. And again. So even if providing such a definition is quite irrelevant as I don’t research legal AI in general (in which case the delineation between AI and non-AI might be of interest) but rather some specific questions (modelling vagueness and uncertainty in law) which without a question are AI & law questions, here, for explanatory rather than definitive use, with no warranties for fitness for any particular purpose, yadda yadda yadda, are my two cents:

Artificial Intelligence is the cross-disciplinary enterprise of trying to do things with a computer which when done by people are said to require intelligence and which computers cannot (yet) do. (The careful reader may notice a certain degree of isomorphism with a popular definition within the extended cognition framework...)

(And comparison shoppers, here is Wikipedia’s current version: “Artificial intelligence (AI) is the intelligence of machines and robots and the branch of computer science that aims to create it.”)

So: Consistently with the bottom-up approach to AI I like to advocate in general, I don’t think allusions to the Turing test or the Singularity or whatever are all that interesting, as far as actual progress is concerned, the cognitive arts advance through innovations which are very small increments from the perspective of AI as a whole but can be quite dramatic for the topical discipline in question.

I do think that the trying (or aim[ing] to create) is an important part of what makes AI AI. Doing arithmetics also requires intelligence but has never been a part of AI since computers could do (and indeed were built to do) it properly from the beginning. And so on the way from notrespondingstilltrying to commercial viability, AI projects start being called computational whatever or whatever technology (hence legal technology). Of course the boundaries are vague and the whole boxological excercise of little use in anything other than turf-wars in academia.

And the fact that the definition refers to human intelligence just serves to illustrate the futility and question-beggitude of definitions for one simple reason: The psychological understanding of human intelligence just adds even more layers of complexity. For example, IQ tests cannot possibly measure human intelligence per se and in general. What they measure instead is a specific indicator known as the g factor (or general intelligence), which has been shown to correlate (reasonably) well with the more specific intelligent abilities.

Even if working on definitions can occasionally serve an useful purpose, personally I think in most cases the more expedient alternative is to follow Justice Potter Stewart in Jacobellis v. Ohio: “I know it when I see it.” For historical reasons, jurisprudence in Finland still has a particular affinity for concepts and definitions not really seen elsewhere to the same degree. I’m planning to address this issue in extenso at some point with the title Begriffsjurisprudenz 2.0. (Spoiler alert: may also offend ontologists.)

Peter Thiel on Singularity and legal technology

Betabeat (just one of many tech blogs I follow regularly) had yesterday a interesting post on Peter Thiel’s (Stanford Law graduate, PayPal co-founder &c &c) presentation at the Legal Technology and Informatics course held at Stanford law for the first time this past autumn. Blake Winters has kindly written and published an essay on the presentation, on which these brief comments are based.

Personally I think all this talk about the Singularity is mostly just a distraction (and of course fodder for dystopic science fiction). Actually functioning general-purpose artificial intelligence is not simply just a matter of bytes and CPU cycles or even fully replicating the neural network of a human brain at some instant (because so much of human intelligence depends on neurogenesis and the formation and pruning of connections, processes which only a couple of decades ago were still thought to end by adulthood), and anyway it is so far in the horizon that it is impossible to use as a target. There is still a lot of work to be done in trying to make sense about the actual functioning of human cognition. (The discussion about free will and whether Libet’s experiments show that it doesn’t exist is a good example.) Even if the Singularity does arrive at some point, the interaction of humans and computers at that time will not be something we can easily imagine. (Just compare whatever you are using to read this with a completely character-based interface (your only choice thirty years ago). And I still fondly remember the sound of a good mechanical teleprinter...)

To date, AI has been most successful when trying to solve very difficult but still quite concrete problems with computational methods. My rule of thumb is that when AI starts being useful, it stops being called AI. (Hence I also prefer to talk about (intelligent) legal technology rather than legal AI.) There are many branches of computer science and other computational sciences which started out basic AI research, with language technology as just one good example.

But more importantly, as for the shorter timeframe, I totally agree with Thiel. Computers are much better than people at some tasks and legal technology has great potential for radically transforming the marketplace for legal services (for the better) in the near future. The work we do at Onomatics will hopefully a good example from the more technologically advanced end of the scale, but our domain (trademark law) is just a very small corner of the entire legal system.

All this just reminds me that I should finally get around to writing two blog posts I’ve been thinking about for quite a while, one titled “Why do computers make better lawyers than people” and the other – of course – “Why do people make better lawyers than computers”. Real Soon Now!

Further reading:

• Peter Thiel on The Future of Legal Technology - Notes Essay (by Blake Masters)
• Notes from Peter Thiel’s CS183 Startup class at Stanford (by Blake Masters)
• Syllabus for the Stanford Legal Technology and Informatics course
• Course reader for the same

What is Legal Technology?

In my opinion, AI & law desperately needs a makeover. One simple but effective way for the field to reinvent itself is rebranding, and the best label for this I can think of is Legal Technology (oikeusteknologia, rättsteknologi, ret(t)steknologi, õigustehnoloogia, R/rechtstechnologie, technologie juridique, tecnologia giuridica, юридическая технология &c).

As someone who has followed and worked in language technology for about two decades now, I see AI & law as being now in the same state as language technology was in the early 1990s. I have presented some lessons learned on how to approach real-world problems at the detail level in my robo-judge paper, so I won't go into them here. Instead, my proposal here looks into language technology as a field that has succesfully reinvented itself a couple of times already. Early on, it was only known as natural language processing (NLP) as a subfield of AI and a form of basic research rarely with any concrete application in mind. (A notable exception to this is machine translation, which also happens to be older than the term AI itself. More on that in a separate post as well as an article written jointly by me and Anniina Real Soon Now.) Then came computational linguistics, which was centered on using computational models and techniques as a tool for linguistic research. (This is where I think AI & law is now.) Of these, in particular corpus linguistics has become mainstream in virtually all subfields of linguistics, but other computational methods are now widely used outside computational linguistics proper as well. Through the 1990s computational linguistics also started to find its way into commercial applications in domains such as language checking, information retrieval, text-to-speech and vice versa, dialogue systems, and machine translation. As these real-world applications started to generate increasingly important research questions in their own right, language technology was born.

"Legal technology" as a term is not my invention. For example, in the US there has been a bicoastal biannual conference called LegalTech® since 2006. As far as I know, most of the technologies presented there are are not all that interesting from an AI & law perspective, with topics such as case management and billing platforms, synchronizing your BlackBerry with your Outlook and stuff like that, and whatever new cruft Westlaw and LexisNexis have come up with each year.

More to the point are for example the LawTechCamps arranged by Daniel Martin Katz (of Computational Legal Studies) and others in June 2011 and next week in Toronto and in the end of June in London. There is also a growing number of start-up companies in the field at least in the US, as listed just the other day on the eLawyering blog. Most of the start-ups listed seem to be working on applications having to do with contracts (possibly a sign of flock mentality from the venture capital side?). Contracts are also the target of the only out legal tech start-up I know of here in Finland, Sopima. With a large number of companies on the same domain fighting over the same market from somewhat different perspectives, it is clear that only some of these companies will be able to succeed (at least as far as the US companies are concerned, Europe is a different kettle of fish because of the different legal culture(s) and the prevalence of non-English languages). The best products have to address a real-world problem and solve it well and efficiently. Usability is another key success factor, and it still seems to be generally neglected in legal IT. Just because a certain design is a possible way to do something does not mean it is the best way (indeed it rarely is, though at least it usually is not quite this bad; required reading: Donald Norman's The Design of Everyday Things, MIT Press 1989). In particular, just replicating ancient practices from the age of pen and paper (and secretaries) and possibly adding some bells and whistles is a true and tried pattern, unfortunately. And the result is an application that takes a week-long course just to get started with it. All the same, the technically best solution does not necessarily win the game. In the end, it all boils down to the viability of the business model and the ability to make it into a reality. (Here's a convenient rule of thumb: marketing costs money, selling makes money. Close early, close often.)

So how can the AI & law community contribute to the impending legal technology boom? One approach is to take an existing, reasonably well-developed Good Old-Fashioned AI & law technology, and to find a real-life legal problem which it could possibly solve. (I'm afraid I can't come up with an example.) The other approach is to take an existing problem (= market need) in the legal community, a problem of the kind that should be solvable by computing, and looking around all over the place in computer science in search of that solution. (Here e-discovery is a prime example, though it does not travel well, and performance-wise it is quite disappointing by the language technology metrics I'm used to but at least it is still equally reliable yet faster and cheaper than people doing the same job.) Since language is in a key role in law, language technology is one obvious place to look at but it should definitely not be the only one for any legal tech company. I'm sure the next 20 years will be a lot more interesting (and profitable) for the field than the past 20.