Kazakhstan enacts its laws in Kazakh and Russian, both authentic, yet the two texts are not compared when the state’s reference database of legal acts is formed. On the Criminal Code, this benchmark tests cross-lingual similarity and explicit rules against synthetic one-sided edits, differences between editions and a blinded review of 192 units by two legal experts and an arbiter. The best models matched 98.6–100% of 487 articles to their counterparts, which is not detection. A global similarity threshold detected edits weakly (area under the receiver operating characteristic curve 0.49–0.67; at most 0.81 after length calibration, still missing over half of the changed references at a 5% false-positive rate), whereas comparing a unit with its previous text registered most edits. No similarity score ranked expert-identified discrepancies above chance after adjustment for multiple comparisons. Prototype rules on structure, numbers, references and units flagged 16 articles, 10 with a discrepancy, six at the flagged element. Of 150 random unflagged units, eight (5.3%) held a discrepancy, mostly in terms or the scope of qualifiers, which no rule reads; the flags thus pointed to an estimated 7% (4–13%) of the units with discrepancies (at most 14% under other expert references). On a second code, only three of 52 and seven of 34 flags of the two quantity readers marked real differences. The rules can guide expert review on the code they were built for but do not transfer without adaptation and cannot replace it.

This article examines how deficiencies in data used by artificial intelligence systems become legally relevant and how the resulting harm is allocated across a multi-actor chain. This study combines doctrinal analysis, functional comparison, a targeted narrative review, and normative modelling; its creditworthiness scenario is hypothetical. Ten analytical categories are grouped into data quality, legal origin, and governance/evidential defects and linked to legal and technical sources. Kazakhstan’s civil and procedural law is compared with bounded European Union mechanisms and Korean civil and personal information legislation. The analysis identifies existing rules on presumed fault, evidence production, obstruction of expert examination, and joint causation before defining residual gaps. The proposed model preserves ordinary remedies, develops purpose-specific warranties and protected disclosure, and confines additional presumptions to specified records and causal issues. Exceptional operator liability without proof of fault requires express legislative designation and justification of residual risk beyond existing remedies. Joint and several liability depends on joint causation, not technical participation or missing documentation alone. The key contribution of the study is a domestically grounded coordination model that distinguishes existing law, interpretation, and legislative proposals without treating every inaccurate outcome as compensable harm.