<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0041-8633</journal-id>
<journal-title><![CDATA[Boletín mexicano de derecho comparado]]></journal-title>
<abbrev-journal-title><![CDATA[Bol. Mex. Der. Comp.]]></abbrev-journal-title>
<issn>0041-8633</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Instituto de Investigaciones Jurídicas]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0041-86332025000300206</article-id>
<article-id pub-id-type="doi">10.22201/iij.24484873e.2025.174.20220</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Inteligencia artificial y derecho de autor. Apuntes sobre la generación de contenidos]]></article-title>
<article-title xml:lang="en"><![CDATA[Artificial Intelligence and Copyright Law. Notes on Content Generation]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Núñez Rocha]]></surname>
<given-names><![CDATA[Hernán]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Alcalá  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Spain</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<volume>58</volume>
<numero>174</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0041-86332025000300206&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0041-86332025000300206&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0041-86332025000300206&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: El presente trabajo examina la posibilidad de reconocer protección por el derecho de autor a los contenidos generados por sistemas de inteligencia artificial, a partir de que la noción de &#8220;obra&#8221; exige autoría humana y un umbral mínimo de creatividad. El objetivo es determinar si los productos de la IA generativa pueden incorporarse al régimen contemporáneo del derecho de autor. La aproximación es dogmática y comparada, con revisión normativa, doctrinal y jurisprudencial sobre originalidad y autoría en distintos ordenamientos, con especial atención en precedentes recientes de Estados Unidos y China. Los resultados muestran que los sistemas generativos carecen de impronta personal y del grado mínimo de creatividad humana requerido por el derecho de autor, por lo que sus productos no califican como obras en sentido jurídico. El estudio se circunscribe al análisis jurídico-comparado y no agota implicaciones técnicas o económicas del entrenamiento de modelos, lo que acota el alcance de sus conclusiones. Su valor radica en articular la evolución tecnológica de la inteligencia artificial con los principios estructurales del derecho de autor y en proponer criterios interpretativos para identificar, con base jurídica, la intervención creativa humana en la generación de contenidos. Se concluye que, como regla general, los productos generados de manera autónoma por sistemas de inteligencia artificial deben reputarse de dominio público y se reserva la protección autoral únicamente a los casos en que la participación humana sea demostrable, determinante y susceptible de individualización jurídica.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: This article explores whether the products generated by artificial intelligence systems can qualify as &#8220;works&#8221; within the meaning of contemporary copyright law, considering that such recognition presupposes human authorship and a minimum threshold of creativity. Adopting a dogmatic and comparative approach, the study draws upon normative, doctrinal, and jurisprudential sources to examine the concepts of authorship and originality across different legal systems, with particular attention to recent developments in the United States and China. The findings indicate that generative systems lack the personal imprint and creative autonomy required for copyright protection, and therefore their outputs cannot be regarded as works in the legal sense. The research is confined to a legal-comparative analysis and does not extend to the technical or economic dimensions of AI training models, which delineates the scope of its conclusions. Its contribution lies in linking the technological evolution of artificial intelligence with the structural principles of copyright law and in proposing interpretative criteria to assess the extent of human creative involvement in content generation. As a general rule, autonomously generated outputs of artificial intelligence should be treated as part of the public domain, while copyright protection ought to be reserved for those cases in which human participation is demonstrable, decisive, and legally attributable.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[inteligencia artificial generativa]]></kwd>
<kwd lng="es"><![CDATA[derechos de autor]]></kwd>
<kwd lng="es"><![CDATA[autoría]]></kwd>
<kwd lng="es"><![CDATA[obra]]></kwd>
<kwd lng="es"><![CDATA[originalidad]]></kwd>
<kwd lng="en"><![CDATA[generative artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[copyright]]></kwd>
<kwd lng="en"><![CDATA[autorship]]></kwd>
<kwd lng="en"><![CDATA[production]]></kwd>
<kwd lng="en"><![CDATA[originality]]></kwd>
</kwd-group>
</article-meta>
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