If network analysis in particular and data science in general can be so useful, why do they figure so rarely in legal research? Van Dijck: “Lawyers are often bad at maths and want to avoid numbers at all costs. They’re also not empirically trained, so they won’t immediately turn to a method from data science. But so far almost everyone who’s seen what we’re doing is enthusiastic and sees the potential for his or her research.”

The lawyers looking beyond the law

It is no coincidence that Van Dijck and Schaper themselves have broader-than-usual backgrounds. Although he chose to pursue law, at school Van Dijck was good at maths, and he still has a technical itch that needs scratching. Schaper, having studied Business Economics at UM in addition to Tax Law, is familiar with quantitative research methods. Both saw that there was a different and better way of doing things, and together they decided to set up the Maastricht Law and Tech Lab (‘the Lab’). “We want to be a platform that focuses explicitly on technology for law alongside law for technology”, Van Dijck says.

Technology for law is in its infancy

Schaper: “We’ve reached a stage in which we can apply specific computational techniques like network analysis to legal questions, but the translation of general algorithms to the field of law, and exactly how they can be applied there, is not yet clear. There’s still very little evidence as to which algorithm you can use to answer which legal question. Medical science has made much more progress; in bioinformatics they’ve developed all kinds of applications for their own field. We’re lagging behind in that regard.” 

The goal: transparent, open-source algorithms

Software already exists that lawyers can use, but it is not user-friendly and comes in the form of commercial products that users need to pay for. Van Dijck: “As a consequence, you don’t know exactly how the algorithms work. We want to make them transparent. We work according to the FAIR principles (findable, accessible, interoperable, reusable) and aim to make things open source as far as possible, so that others can see, check and use them.” Schaper: “We’re trying to build a data infrastructure for legal research where the data are stored in such a way that you can apply algorithms to them that produce reliable results.” Van Dijck: “There are three phases: first create a data infrastructure, then develop AI or apply it in order to answer empirical legal questions. The first step in particular is essentially donkey work, but nonetheless important, because if you throw rubbish at AI, you get rubbish back.”

The prototype has already led to an important find  

They are currently working on a network analysis tool that several bachelor’s and master’s students have already used for their theses. Schaper: “We try for example to show the links between verdicts in graphical form, so you can see at a glance how one verdict relates to another, whether there are few or many connections, and whether the verdicts can be grouped in some way. If you go to rechtspraak.nl [the database of Dutch case law] and search for a particular decision or keyword, you get a whole list of verdicts that you have to read to see how they relate to one another, whereas the computer can easily make those connections for you and present them visually. That’s the product we’re now trying to deliver.”

Successfully, so far, because although there is room for improvement from a technical perspective, one of their students already made a discovery using the prototype that had been overlooked in the literature. The resulting article will soon be submitted to an academic journal. Van Dijck: “In the case law, it was unclear how damages can be calculated in cases in which negotiations have broken down. Do you only compensate the costs incurred or also the lost profit? When can you claim what? Using network analysis, our student found at least one verdict that illustrates how you can approach this decision-making process. All the experts had overlooked it, but this young guy in his early 20s found it.”