<?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>2007-3607</journal-id>
<journal-title><![CDATA[PAAKAT: revista de tecnología y sociedad]]></journal-title>
<abbrev-journal-title><![CDATA[PAAKAT: rev. tecnol. soc.]]></abbrev-journal-title>
<issn>2007-3607</issn>
<publisher>
<publisher-name><![CDATA[Universidad de Guadalajara, Sistema de Universidad Virtual]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-36072024000200001</article-id>
<article-id pub-id-type="doi">10.32870/pk.a14n27.885</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Beneficios y riesgos del uso de la Inteligencia Artificial en el Servicio de Administración Tributaria de México (SAT). Un análisis desde la perspectiva de investigadores académicos]]></article-title>
<article-title xml:lang="en"><![CDATA[Benefits and risks of using Artificial Intelligence in the Mexican Tax Administration Service (SAT). An analysis from the perspective of academic researchers]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Arguelles Toache]]></surname>
<given-names><![CDATA[Eugenio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional Autónoma de México Instituto de Investigaciones Sociales ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2024</year>
</pub-date>
<volume>14</volume>
<numero>27</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-36072024000200001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-36072024000200001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-36072024000200001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En el Plan Maestro 2024 el Servicio de Administración Tributaria de México (SAT) anunció formalmente que la Inteligencia Artificial (IA) será utilizada para clasificar a los contribuyentes de acuerdo con su riesgo fiscal, identificar redes complejas de elusión y evasión, y detectar inconsistencias asociadas con el contrabando y empresas fachada. El objetivo de este trabajo es identificar, analizar y comparar la percepción de investigadores académicos sobre los posibles beneficios y los potenciales riesgos del uso de la IA en el SAT. Para ello, se elaboró un cuestionario que fue respondido por 65 investigadores adscritos a grupos o institutos de investigación especializados en IA o administración tributaria de distintas universidades mexicanas. De acuerdo con dichos investigadores los posibles beneficios del uso de la IA en el SAT son: optimización del tiempo y recursos; mayor eficiencia y eficacia en los procesos; reducción del fraude y la evasión fiscal; mayor precisión en los cálculos; reducción de los costos operativos; aumento en la recaudación tributaria; y mejoramiento del servicio a los contribuyentes. Por otro lado, los potenciales riesgos del uso de la IA en el SAT son: utilización de algoritmos con sesgos socioeconómicos, de raza, nacionalidad y género que se traducen en procesos de discriminación, exclusión e injusticias; desaparición de puestos de trabajo; procesos que se convierten en una &#8220;caja negra&#8221;; hacer difusa la responsabilidad de los servidores públicos; problemas de transparencia; generación de desempleo, y uso no autorizado de los datos de los contribuyentes.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In the 2024 Master Plan, the Mexican Tax Administration Service (SAT) formally announced that Artificial Intelligence (AI) will be used to classify taxpayers according to their tax risk, identify complex networks of avoidance and evasion, and detect inconsistencies associated with smuggling and front companies. The objective of this work is to identify, analyze and compare the perception of academic researchers on the possible benefits and potential risks of using AI in the SAT. To do so, a questionnaire was developed that was answered by 65 researchers attached to research groups or institutes specialized in AI or tax administration from different Mexican universities. According to these researchers, the possible benefits of using AI in the SAT are optimization of time and resources; greater efficiency and effectiveness in processes; reduction of fraud and tax evasion; greater precision in calculations; reduction of operating costs; increase in tax collection; and improvement of service to taxpayers. On the other hand, the potential risks of using AI in the SAT are the use of algorithms with socioeconomic, racial, national and gender biases that result in processes of discrimination, exclusion and injustice; the disappearance of jobs; processes that become a &#8220;black box&#8221;; the diffusion of the responsibility of public servants; transparency problems; the generation of unemployment, and unauthorized use of taxpayer data.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[gobierno electrónico]]></kwd>
<kwd lng="es"><![CDATA[administración pública inteligente]]></kwd>
<kwd lng="es"><![CDATA[sistema tributario]]></kwd>
<kwd lng="es"><![CDATA[algoritmos]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje automático]]></kwd>
<kwd lng="en"><![CDATA[e-government]]></kwd>
<kwd lng="en"><![CDATA[smart public administration]]></kwd>
<kwd lng="en"><![CDATA[tax system]]></kwd>
<kwd lng="en"><![CDATA[algorithms]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
</kwd-group>
</article-meta>
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