<?xml version='1.0' encoding='UTF-8'?><?xml-stylesheet href='static/style.xsl' type='text/xsl'?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-05T03:01:34Z</responseDate><request verb="GetRecord" identifier="oai:ebiltegia.mondragon.edu:20.500.11984/14627" metadataPrefix="rdf">https://ebiltegia.mondragon.edu/oai/request</request><GetRecord><record><header><identifier>oai:ebiltegia.mondragon.edu:20.500.11984/14627</identifier><datestamp>2026-07-15T06:15:49Z</datestamp><setSpec>com_20.500.11984_473</setSpec><setSpec>com_20.500.11984_14090</setSpec><setSpec>col_20.500.11984_478</setSpec></header><metadata><rdf:RDF xmlns:rdf="http://www.openarchives.org/OAI/2.0/rdf/" xmlns:ow="http://www.ontoweb.org/ontology/1#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:ds="http://dspace.org/ds/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/rdf/ http://www.openarchives.org/OAI/2.0/rdf.xsd">
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      <dc:title>Explainable and Evaluative Artificial Intelligence: Alternatives to Ensure Equity in Decision-Making</dc:title>
      <dc:creator>Villuendas Rey, Yenny</dc:creator>
      <dc:creator>Camacho-Nieto, OSCAR</dc:creator>
      <dc:creator>Tusell Rey, Claudia</dc:creator>
      <dc:creator>Salinas García, Viridiana </dc:creator>
      <dc:creator>Pino Gómez, Joel</dc:creator>
      <dc:subject>Explainable artificial intelligence</dc:subject>
      <dc:subject>evaluative artificial intelligence</dc:subject>
      <dc:subject>decision-making</dc:subject>
      <dc:subject>equity and justice</dc:subject>
      <dc:subject>ODS 8 Trabajo decente y crecimiento económico</dc:subject>
      <dc:subject>ODS 10 Reducción de las desigualdades</dc:subject>
      <dc:subject>ODS 16 Paz, justicia e instituciones sólidas</dc:subject>
      <dc:description>Explainable Artificial Intelligence (XAI) and Evaluative Artificial Intelligence (EAI) are crucial approaches to ensuring fairness in decision-making. XAI refers to the ability of Artificial Intelligence (AI) systems to be understood and explained by humans, while EAI is a new paradigm that focuses on identifying possible decisions for intelligent algorithms by formulating hypotheses for and against them.</dc:description>
      <dc:date>2026-07-14T08:18:12Z</dc:date>
      <dc:date>2026-07-14T08:18:12Z</dc:date>
      <dc:date>2026</dc:date>
      <dc:identifier>2007-9737</dc:identifier>
      <dc:identifier>https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&amp;ficha_no=201711</dc:identifier>
      <dc:identifier>https://hdl.handle.net/20.500.11984/14627</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>© Instituto Politecnico Nacional</dc:rights>
      <dc:publisher>Instituto Politecnico Nacional</dc:publisher>
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