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Preprint . 2025
License: CC BY
Data sources: ZENODO
https://doi.org/10.2139/ssrn.5...
Article . 2026 . Peer-reviewed
Data sources: Crossref
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Corporate Culpa Lata in Artificial Intelligence Offenses: Reconstruction of Criminal Liability and Reorientation of Evidence Under the 2023 Criminal Code

Authors: Darmawan, Imam Sahroni;

Corporate Culpa Lata in Artificial Intelligence Offenses: Reconstruction of Criminal Liability and Reorientation of Evidence Under the 2023 Criminal Code

Abstract

This deposit contains a preprint version of a legal research article examining corporate criminal liability for harms caused by autonomous artificial intelligence systems under Indonesia’s Criminal Code 2023 (Law No. 1 of 2023). The paper proposes a doctrinal reconstruction of culpa lata (gross negligence) as a normative basis for attributing criminal responsibility to corporate controllers through a model of “Algorithmic Managerial Negligence”. Rather than focusing on unpredictable machine outputs, the analysis reorients fault assessment toward ex-ante risk governance, professional standards, and realizable risk theory. Methodologically, the study employs normative legal research with a conceptual and statutory approach, engaging comparative insights from global AI liability discourse while remaining anchored in Indonesian criminal law principles, including the legality principle and fair trial guarantees. Status: This manuscript is a preprint / working paper and has not yet undergone peer review. A revised version may be submitted to an academic journal. Version note: This version is made available for scholarly discussion and citation. Subsequent revisions may differ.

Keywords

Criminal Evidence, Artificial Intelligence, Gross Negligence, 2023 Criminal Code, Corporate Liability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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