<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName>KMAN Publication Incorporation</PublisherName>
      <JournalTitle>Interdisciplinary Studies in Society, Law, and Politics</JournalTitle>
      <Issn>3060-5687</Issn>
      <Volume>4</Volume>
      <Issue>Serial Number 15</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>10</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>The Legal Personhood of AI: Philosophical and Political Foundations for a New Juridical Subject</ArticleTitle>
    <VernacularTitle>The Legal Personhood of AI: Philosophical and Political Foundations for a New Juridical Subject</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>10</LastPage>
    <ELocationID EIdType="doi">10.61838/kman.isslp.4.4.23</ELocationID>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2025</Year>
        <Month>03</Month>
        <Day>23</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;This article aims to explore the philosophical and political foundations for recognizing artificial intelligence (AI) as a potential juridical subject within contemporary legal systems. The study employs a narrative review design based on a descriptive analysis method to examine theoretical and legal literature published between 2021 and 2024. Scholarly sources were selected from academic databases, focusing on legal theory, philosophy of personhood, political implications, and AI governance. The analysis was organized thematically across legal history, philosophical debates, political frameworks, and proposed legal models for AI personhood. The findings highlight that classical theories of personhood, including rationality, autonomy, and recognition, form the conceptual basis for legal personhood but pose significant challenges when applied to AI. Contemporary debates suggest that AI lacks consciousness and moral autonomy but may still be integrated into legal frameworks through functional or hybrid models. These include proposals for partial personhood, relational legal theories, and distributed agency models, which offer ways to assign legal status to AI based on their roles and capacities. The study also reveals that extending legal personhood to AI could disrupt liberal democratic principles, create accountability gaps, and generate ethical risks if not carefully regulated. Nevertheless, emerging models from various jurisdictions indicate a growing interest in redefining legal subjectivity to accommodate non-human actors. Recognizing AI as a juridical subject requires cautious, interdisciplinary deliberation. While traditional legal categories are being challenged by technological advances, any transformation in the legal status of AI must preserve human accountability, democratic values, and ethical coherence. Future research should focus on refining hybrid legal models and developing safeguards to prevent misuse or unintended legal consequences.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Artificial intelligence</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">legal personhood</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">juridical subject</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">moral agency</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">political philosophy</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">hybrid models</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">distributed agency</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">digital governance</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://journalisslp.com/index.php/isslp/article/download/448/869</ArchiveCopySource>
  </Article>
</ArticleSet>
