Reconstruction of Criminal Responsibility for Crimes Committed Through Generative Artificial Intelligence

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      <journal-id journal-id-type="actanova-preservation">Journal Customary Law</journal-id>
      <journal-title-group>
        <journal-title>Journal Customary Law</journal-title>
      </journal-title-group>
      <issn pub-type="epub">3026-460X</issn>
      <publisher>
        <publisher-name>Indonesian Journal Publisher</publisher-name>
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    <article-meta>
      <article-id pub-id-type="publisher-id">reconstruction-of-criminal-responsibility-for-crimes-committed-through-generative-artificial-intelligence</article-id>
      <article-id pub-id-type="doi">10.47134/jcl.v3i4.6257</article-id>
      <title-group>
        <article-title>Reconstruction of Criminal Responsibility for Crimes Committed Through Generative Artificial Intelligence</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Pattinasarany</surname>
            <given-names>Eva Berta</given-names>
          </name>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Santiago</surname>
            <given-names>Faisal</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date pub-type="epub">
        <day>06</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      <volume>3</volume>
      <issue>4</issue>
      <permissions>
        <copyright-statement>© 2026 Indonesian Journal Publisher</copyright-statement>
        <copyright-year>2026</copyright-year>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
          <license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
      <abstract>
        <p>The development of generative Artificial Intelligence (AI) has changed the characteristics of criminal acts through its ability to produce text, images, sound, video, and program code that can be used to commit various forms of crime, such as deepfakes, voice cloning, digital document forgery, phishing, and malware distribution. These changes present new legal issues because the doctrine of criminal liability in Indonesian positive law is still based on the assumption that the perpetrator commits the act giving rise to legal consequences, whereas generative AI creates a relationship mediated by an algorithmic system. This study aims to analyze the construction of criminal liability for crimes committed through generative artificial intelligence, identify weaknesses in the applicable legal norms, and formulate a reconstruction of the concept of criminal liability that is more adaptive to technological developments. The study uses a normative juridical method with statutory, conceptual, and comparative approaches. Legal materials are obtained through literature studies and analyzed qualitatively using descriptive-analytical and prescriptive methods. The research found that Law Number 1 of 2023 concerning the Criminal Code, Law Number 11 of 2008 concerning Electronic Information and Transactions, as most recently amended by Law Number 1 of 2024, and Law Number 27 of 2022 concerning Personal Data Protection do not provide adequate regulations regarding the division of criminal liability among users, developers, platform providers, and corporations in the generative AI ecosystem. This gap creates uncertainty in determining perpetrators, proving fault, causal relationships, and inclusion. This research proposes a reconstruction of the doctrine of criminal liability through a Role-Based Criminal Liability model that integrates classical criminal law theory with the principles of AI Governance, Risk-Based Regulation, and Responsible AI. This model divides liability based on the level of control, the ability to prevent risks, and the predictability of consequences. It is hoped that it will provide legal certainty, protect the public, and support the responsible development of AI technology.</p>
      </abstract>
      <kwd-group kwd-group-type="author">
        <kwd>Generative Artificial Intelligence</kwd>
        <kwd>Criminal Liability</kwd>
        <kwd>Role-Based Criminal Liability</kwd>
        <kwd>AI Governance</kwd>
        <kwd>Criminal Law Reconstruction</kwd>
      </kwd-group>
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        <caption xml:lang="en"><p>Original PDF file published by Indonesian Journal Publisher</p></caption>
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      <p>The development of generative Artificial Intelligence (AI) has changed the characteristics of criminal acts through its ability to produce text, images, sound, video, and program code that can be used to commit various forms of crime, such as deepfakes, voice cloning, digital document forgery, phishing, and malware distribution. These changes present new legal issues because the doctrine of criminal liability in Indonesian positive law is still based on the assumption that the perpetrator commits the act giving rise to legal consequences, whereas generative AI creates a relationship mediated by an algorithmic system. This study aims to analyze the construction of criminal liability for crimes committed through generative artificial intelligence, identify weaknesses in the applicable legal norms, and formulate a reconstruction of the concept of criminal liability that is more adaptive to technological developments. The study uses a normative juridical method with statutory, conceptual, and comparative approaches. Legal materials are obtained through literature studies and analyzed qualitatively using descriptive-analytical and prescriptive methods. The research found that Law Number 1 of 2023 concerning the Criminal Code, Law Number 11 of 2008 concerning Electronic Information and Transactions, as most recently amended by Law Number 1 of 2024, and Law Number 27 of 2022 concerning Personal Data Protection do not provide adequate regulations regarding the division of criminal liability among users, developers, platform providers, and corporations in the generative AI ecosystem. This gap creates uncertainty in determining perpetrators, proving fault, causal relationships, and inclusion. This research proposes a reconstruction of the doctrine of criminal liability through a Role-Based Criminal Liability model that integrates classical criminal law theory with the principles of AI Governance, Risk-Based Regulation, and Responsible AI. This model divides liability based on the level of control, the ability to prevent risks, and the predictability of consequences. It is hoped that it will provide legal certainty, protect the public, and support the responsible development of AI technology.</p>
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