Positive law, inscribed in legal texts, entails an authority not inherent in literary texts, generating legal consequences that can have real effects on a person’s life and liberty. The interpretation of legal texts, necessarily a normative undertaking, resists the mechanical application of rules, though still requiring a measure of predictability, coherence with other relevant legal norms and compliance with constitutional safeguards. The present proliferation of legal texts on the internet (codes, statutes, judgments, treaties, doctrinal treatises) renders the selection of relevant texts and cases next to impossible. We may expect that systems to mine these texts to find arguments that support one’s case, as well as expert systems that support the decision-making process of courts, will end up doing much of the work. This raises the question of the difference between human interpretation and computational pattern-recognition and the issue of whether this difference makes a difference for the meaning of law. Possibly, data mining will produce patterns that disclose habits of the minds of judges and legislators that would have otherwise gone unnoticed (reinforcing the argument of the ‘legal realists’ at the beginning of the 20th century). Also, after the data analysis it will still be up to the judge to decide how to interpret the results or up to the prosecution which patterns to engage in the construction of evidence (requiring a hermeneutics of computational patterns instead of texts). My focus in this paper regards the fact that the mining process necessarily disambiguates the legal texts in order to transform them into a machine-readable data set, while the algorithms used for the analysis embody a strategy that will co-determine the outcome of the patterns. There seems a major due process concern here to the extent that these patterns are invisible for the naked human eye and will not be contestable in a court of law, due to their hidden complexity and computational nature. This position paper aims to explain what is at stake in the computational turn with regard to legal texts. This prepares for the question I want to put forward to those involved in distant reading and not-reading of texts: could a visualization of computational patterns constitute a new way of un-hiding the complexity involved, opening the results of computational ‘knowledge’ to citizens’ scrutiny?