<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Legal Studies in Digital Age</JournalTitle>
      <Issn></Issn>
      <Volume></Volume>
      <Issue>In Press</Issue>
      <PubDate PubStatus="epublish">
        <Year>2027</Year>
        <Month>03</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Challenges to the Principle of Transparency, the Right to Explanation, and the Right to Redress Against AI-Based Decisions in Administrative Law</ArticleTitle>
    <VernacularTitle>Challenges to the Principle of Transparency, the Right to Explanation, and the Right to Redress Against AI-Based Decisions in Administrative Law</VernacularTitle>
    <FirstPage>1</FirstPage>
    <LastPage>7</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2026</Year>
        <Month>02</Month>
        <Day>20</Day>
      </PubDate>
    </History>
    <Abstract>&lt;p&gt;This study aims to systematically review the specialized literature and analyze the challenges related to transparency, the right to explanation, and the right to redress in response to AI-based administrative decisions. Based on the PRISMA 2020 framework, a systematic search was conducted in the databases of Scopus, Web of Science, Google Scholar, and two Persian-language databases, namely the Comprehensive Portal of Humanities and Social Sciences and SID, covering the period from 2016 to 2025. Following the application of rigorous inclusion and exclusion criteria and a three-stage screening process, 9 articles (6 in English and 3 in Persian) were ultimately selected from an initial pool of 255 records for final qualitative synthesis. The extracted data were categorized and analyzed across six major themes. The analysis revealed an inherent tension between the efficiency-driven logic of algorithms and the protective legal requirements of administrative law. In the area of transparency, the literature demonstrates a transition from the concept of “formal transparency” (information disclosure) to “meaningful transparency” (citizen-oriented interpretability and comprehensibility). Regarding the right to explanation, the “gap between technical explainability (XAI) and legal explainability” was identified as the principal barrier to realizing this right. The most significant finding was the identification of the “right to redress” as the weakest dimension of the protective triad; traditional mechanisms of judicial review were deemed insufficient in addressing the complexities of algorithmic “black-box” systems, underscoring the need for new procedural standards and anticipatory oversight mechanisms, such as independent audits. The findings further suggest that the challenges of algorithmic administrative law are not solely legal and technical in nature but are intertwined with broader dimensions, including democratic accountability, the exacerbation of social inequalities, and organizational culture. Ensuring transparency, the right to explanation, and the right to redress in the era of algorithmic governance requires a conceptual reengineering of traditional principles of administrative law and the adoption of a multidimensional strategy encompassing technical (development of explainability tools), legal (formulation of new procedural standards), institutional (establishment of specialized and independent oversight bodies), and cultural (institutionalization of a culture of accountability) dimensions.&lt;/p&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Algorithmic Transparency</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Right to Explanation</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Judicial Review</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Administrative Law</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Artificial Intelligence</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://jlsda.com/index.php/lsda/article/download/417/349</ArchiveCopySource>
  </Article>
</ArticleSet>
