Consolidating the pact between technology, education, and transparency is urgent; the State cannot hide within its own data.

An analysis of the consolidation of precedent theory in Brazil, considering the innovations introduced by the 2015 Code of Civil Procedure (CPC), reveals a significant moment in the quest for predictability and rationality within the judicial system. Since this milestone, judicial decisions have gained binding force, becoming fundamental references for both administrative bodies and the courts. This not only implies institutional deference but also demands a robust organisational structure, firmly anchored in memory and transparency.

The challenge ahead extends beyond the legal field, encompassing structural aspects. The effectiveness of the precedent system requires the State, across its various spheres and bodies, to establish legal databases capable of storing, classifying, interpreting, and interconnecting a broad array of decisions, agreements, and normative expressions. This necessity is not confined to the Judiciary alone; it equally involves regulatory agencies, audit courts, the Public Prosecutor’s Office, and administrative bodies responsible for decisions of legal significance.

However, it is crucial to recognise that the administrative sphere represents the weakest link in Brazil’s institutional chain. Despite significant initiatives within the Brazilian Judiciary, the reality demonstrates that the vast majority of public institutions still lack databases that are structured, auditable, and semantically organised.

Consequently, administrative decisions, disciplinary proceedings, judicial and extrajudicial agreements, as well as contracts and the entire universe of disciplinary and sanctioning jurisprudence, remain scattered and fragmented, hindering access to institutional memory, which should guide the State’s actions.

In this context, the role of algorithms is fundamental. Currently, organising precedents depends on systems using legal, semantic, and statistical parameters. Implementing algorithms to categorise them requires a solid normative basis, technical curation, and a data structure that can be audited. Without these prerequisites, there is a risk that repetition will prevail over coherence, making automation a threat to the very essence of judicial reasoning.

The scope of statistics must be understood in the context of AI’s impact. Statistics can be classified by different parameters. For reference, one may speak of inferential, predictive, diagnostic, multivariate, frequentist, Bayesian, non-parametric, jurimetrics, forensic, social, political, educational, descriptive, explanatory, high-dimensional statistics, and multiple variations, according to the discipline applied—such as biostatistics, psychometrics, computational statistics, and so forth.

In other words, legal databases also serve statistical research, integrated with AI, to derive developments in various other areas and public policies. It is known that normative decisions impact the economy and public policies across numerous other spheres of society as a whole. In this regard, the interpretation of law is necessarily transdisciplinary and is not limited merely to the economic analysis of law.

Organising precedents, therefore, ensures the right to understanding (the right to understand public decisions arises from fundamental rights enshrined in Articles 37 (head), 51 (item 14), 5 (item 60), and 1 (item 3) of the Constitution). Each individual, whether a natural or legal person, has the right to understand the criteria underpinning the public decisions affecting them. This fundamental right to comprehension is intrinsically linked to transparency, traceability, and institutional legitimacy and is realised only when decisions are intelligible, auditable, and consistent with consolidated jurisprudence.

Without well-structured legal databases, there are no real precedents—only a disordered accumulation of decisions. And where accumulation exists, noise, inequalities, and arbitrariness arise, compromising justice and the system’s effectiveness. A structured legal database functions as a digital platform capable of storing, classifying, and correlating administrative and judicial decisions, norms, agreements, and regulatory documents. This organisation must follow clearly defined legal criteria, with rigorous classifications ensuring traceability and version control. Beyond mere preservation, the database must guarantee institutional coherence, facilitate intelligent searches, consistent interpretations, and decisions aligned with the historical jurisprudence of institutions and precedent systems.

In this context, legal databases constitute genuine living ecosystems, continually fed by normative and decisional indexing based on algorithmic logics, metadata, discursive hierarchies, and pre-established patterns. Contemporary statistics, in its multiple facets, performs critical roles, offering causal and algorithmic effectiveness with profound impacts on the institutional interpretation of mapped and indexed norms and decisions.

One cannot overlook that statistical functions, integrated within databases, facilitate numerous functionalities in comprehending how certain decisions consolidate into normative standards and their subsequent societal consequences and impacts, including deviations, dysfunctions, underlying hermeneutic currents, and numerous subjective or objective pathologies inherent to decision-making or algorithmic phenomena. AI, in turn, operates in conjunction with contemporary statistics to facilitate advanced, rapid analyses derived from massive datasets. AI also plays varied roles based fundamentally on statistics, though its functions are distinct and integrated within this domain, provided they maintain auditable and rationally traceable premises.

Technology, at this juncture, will deeply impact classification models based on the language of precedents, argumentative similarities, prevailing legal grounds, recognition of argumentative and normative patterns within decisions, detection of frequent contradictions, inconsistencies, essential coherences, predictive models, and a vast series of patterns aimed at ensuring predictability, legal certainty, and efficiency within the normative system.

In an era of transparency and complexity, the right to understand public decisions emerges as a fundamental right derived from the principle prohibiting arbitrariness by public powers, inherent in the substantial due legal process (Article 5, item 54, of the Brazilian Constitution). Publishing decisions in official gazettes is insufficient, as these instruments do not allow substantial access to transparency regarding the full set of decisions that constitute the norms embodied in precedents. On the other hand, judicial databases are also inadequate, as they do not ensure interconnection with other branches of government nor the effective efficacy of precedents throughout the Brazilian State.

Furthermore, the formation of precedents itself demands cultural strengthening among public and private actors in decision-making processes, involving deeper transformations in Brazilian education and research on jurisprudential production as a whole. Thus, it is urgent for legal education institutions, judicial academies, Public Prosecutor’s Office training programmes, Public Defenders’ offices, law firms, and education overall, as well as the Ministry of Education itself, to integrate precedent theory as a central curricular vector—indeed as a standalone discipline rather than an appendix to Civil Procedure Law.

Brazil must abandon fragmentary interpretation and cultivate a legal culture rooted in institutional memory, argumentative coherence, and collective responsibility. To achieve this, AI must be incorporated into legal curricula, not merely as a technological novelty but as a tool promoting the rational organisation of law, grounded in ethical, epistemological, and normative principles, acting as an aid to human intelligence and ensuring auditability.

Precedent theory must not only be applied but taught, debated, and systematised. To consolidate it, material improvements alone are insufficient: a cultural transformation is required. Structured legal databases must move beyond governmental tools to become platforms for teaching, research, and critical reconstruction of decision-making practices. Recognising the right to comprehensible information allows the country to develop a robust, ethical, and inclusive public transparency policy.

This construction demands more than adopting new technologies; it requires curation, training, and a genuine willingness to listen and reflect. Without this awareness, precedents become empty, decisions become isolated, and access to justice becomes an opaque normative labyrinth.

Consolidating the pact between technology, education, and transparency is urgent. The State cannot hide within its own data; it must organise, explain, and share them—that is the essence of institutional legitimacy in the 21st century. In this sense, it is crucial to acknowledge that access to justice begins with access to the logic of decisions—comprehensible only when organised in public, coherent, and accessible databases, and taught from the outset. Promoting a culture of precedents thus becomes a public policy aimed at institutional integrity. Without this foundation, rights remain unattainable and justice incomprehensible.