A future between open access and artificial intelligence: Which economic model for legal publishing in Belgium ?

Federal Belgium offers multiple legal orders and as many official sources of law. This multilingual and multifaceted legal environment makes the analysis of the legal publishing market and its par excellence "captive audiences" interesting, following one possible scenario, especially for the French-speaking part of Belgium. We no longer speak of the "computerization of law" but rather of an additional stage in this computerization: the introduction of artificial intelligence whose application to law is based mainly on the use of two techniques, natural language processing and machine learning. What does this have to do with publishing? The link is very simple as "Doctrine" equates to unstructured information.
Under the impact of a weakening of their economic model confronted with information and communication technologies as well as the Open Access movement, legal "publishers" are moving towards services with high added value as they still control in an important way the three main sources of law (legislation, case law and doctrine). Publishers want to continue to play a decisive and deciding role in the "legal market".
For several years now, major legal publishers have been investing in artificial intelligence solutions and rely in part on the acquired capital and the remanence of the conventional editorial process.
The strong editorial control on the legislative and regulatory texts consolidation process, the possession of exclusive collections of case law as well as the hold over doctrine – here understood as a "captive audience" – given the control of publishers over a far from negligible part of the editorial process and management of doctrinal publications, make available a material on which new applications of information technology can be built. Thus, it would seem that the publishing, at least part of it, of a certain doctrine only becomes the essential supplement of information to "refine ontologies" set after having recourse to data mining within databases in which the information is structured.
The challenge is to structure the "legal information" represented by the "published doctrine", since we are in the presence of sources containing information that is not structured and that is recorded in natural language. It is easy to imagine – and the doctrine has already asked itself the question – that the language and writing of the law, not only that of legislation and jurisprudence but that of doctrine, are in a hurry to adapt in order to ensure that the data are "cleaned and adjusted" so that the machine can obtain better analytical results thanks to the technique that is text mining.
Our contribution will aim to show the slow but certain evolution of the economic model within a well-defined publishing framework but influenced by wider phenomena.