In December 2025 the Supreme Court of Korea adopted a staged Judicial AI Roadmap. Sentencing-system improvement and recidivism assessment sit among its declared tasks. A public-sector institution has thus committed to governing adjudication, a liberty-bearing state function, with AI, and the questions studied internationally under the heading of Legal Judgment Prediction (LJP) have become immediately practical for Korea. This article maps Korea’s LJP literature in a scoping review. Reading that corpus against the global field, it claims that the field’s defining feature is a normative-empirical disconnect. Its normative (legal) and empirical (technical) literatures have developed separately, with little cross-engagement between them, in that no study in either literature is co-authored by an engineer and a jurist, and no normative work evaluates a domestic model. This article makes two contributions from this diagnosis. First, it argues that engineer-jurist collaboration must tie the technical design of Korea’s LJP to the culpability principle, reason-giving, and judicial independence, treating these constitutional values as design constraints rather than ex post safeguards, and proposes that governed data access and interpretable baselines with legally legible feature attribution (e.g., SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME)) precede deployment. Second, it re-conceives the prediction target of LJP datasets for Korean criminal procedure as three distinct stages, which are guilt determination, applicable provision, and sentence, showing that task definition is itself a legally consequential design decision.

This article examines how national legal structures affect the reception of the European Union framework for digital preservation and public-domain access outside the Union. Articles 6, 7 and 14 of Directive 2019/790 provide the benchmark. They address preservation copying by cultural heritage institutions, protection of exceptions against contractual restrictions and their connection with rules on technological protection measures, and the exclusion of new copyright or related rights in non-original reproductions of public-domain visual art. The analysis identifies two regulatory configurations among EU Member States: copyright-centered implementation of the Directive, and copyright implementation operating alongside non-harmonized national public-law controls over cultural heritage reproductions. Ukraine and Türkiye are examined as two ways of responding to EU copyright rules. Ukraine has moved closer to the EU model through copyright reform and participation in European digital cultural heritage initiatives. Its legislation already covers some functions reflected in Articles 6 and 14, but gaps remain. These include contractual override, the use of works for preservation when technological protection measures prevent access, and the status of non-original reproductions of public-domain visual art. Türkiye follows a different approach. Copyright, legal deposit, and cultural heritage rules regulate these issues separately. Electronic legal deposit supports preservation through the National Library, but there is no copyright exception allowing cultural heritage institutions to preserve collections. Administrative permissions and controls also affect the creation and reuse of cultural heritage reproductions. The comparison identifies three modes of functional reception–direct legal transmission, institutional and procedural transmission, and functional convergence–and treats non-transmission as a separate category for EU functions left unperformed. In the cases examined, reception is more complete where copyright permissions, technological safeguards, legal-deposit mechanisms and cultural heritage administration are institutionally coordinated. Equivalent protection for preservation and public-domain access depends on the coordinated legal and institutional effects of the national framework.

Artificial intelligence (AI)-driven genomic research challenges prevailing consent frameworks by enabling iterative data reuse, cumulative inference, and intergenerational risk that static, one-off consent cannot adequately address. This article applies the Social Construction of Technology (SCOT) and the principle of Respect for Persons (PRP), interpreted through relational autonomy, to examine how regulatory categories such as broad consent, minimal risk, and compatible purpose are socially constructed, institutionally stabilised, and ethically consequential. In this context, consent rules operate not merely as mechanisms of authorisation but as governance tools that allocate responsibility, shape expectations, and determine the legitimacy of downstream data use over time. Through a comparative analysis of the EU General Data Protection Regulation (GDPR) and the U.S. Common Rule (U.S.C.R.), the article demonstrates how categorical exemptions and procedural consent under the U.S.C.R. fail to ensure sustained participant protection in genomic AI, while the GDPR embeds consent within a cumulative legality architecture grounded in Articles 5, 6(4), 9, and 89(1), with Recital 33 guiding interpretation. The article argues that dynamic consent does not constitute an independent lawful basis under the GDPR but may offer a doctrinally compatible and ethically robust governance mechanism capable of operationalising existing GDPR obligations. It may do so by enabling iterative engagement, granular permissions, and accountability across evolving research contexts, particularly in dual-regulation environments such as Qatar, where GDPR-style frameworks coexist with U.S.C.R. requirements.