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  <titleInfo>
    <title>Artificial intelligence: From ethics to policy</title>
  </titleInfo>
  <name type="personal">
    <namePart> van Wynsberghe, Aimee</namePart>
  </name>
  <name type="corporate">
    <namePart>Parlamento Europeo</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">Brussels</placeTerm>
    </place>
    <publisher>Europan Union</publisher>
    <dateIssued>2020</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <extent>37 pág.</extent>
  </physicalDescription>
  <abstract>There  is   little   doubt  that  artificial intelligence  (AI)  and  ma ch inelearning (ML) will  revolutionise public services. However, th e  p ower  for  positive  change  that  AI  provides  simultaneously  holds   the  potential for negative impacts on society. AI  ethics work to uncover the variety  of ethical issues resulting from the design, development, and deployment of AI. The question at the centre of all  current work in AI ethics is: How can  we move from AI ethics to specific policy and legislation for governing AI? Based on a framing of 'AI as a social experiment', this study arrives at policy   options   for    public    administrations   and    governmental organisations who are looking to deploy AI/ML solutions, as well  as the private companies who are creating AI/ML solutions for use in the  public  arena. The  reasons for targeting this application sector concern: the need for a  high  standard of transparency, respect for democratic  values,  and  legitimacy.   The  policy  options  presented here chart a  path towards accountability; procedures and decisions of   an   ethical   nature   are   systematically   logged prior   to    the   deployment of an AI system. This logging is the first step in allowing ethics to play a crucial role in the implementation of AI for the public good</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <subject authority="lcsh">
    <topic>Inteligencia Artificial</topic>
  </subject>
  <subject>
    <topic>AI</topic>
  </subject>
  <subject>
    <topic>machine learning </topic>
  </subject>
  <subject>
    <topic>ML</topic>
  </subject>
  <subject>
    <topic>public services</topic>
  </subject>
  <subject>
    <topic>policies</topic>
  </subject>
  <subject>
    <topic>governing AI</topic>
  </subject>
  <identifier type="isbn">9789284658558 </identifier>
  <identifier type="uri">https://www.europarl.europa.eu/RegData/etudes/STUD/2020/641507/EPRS_STU(2020)641507_EN.pdf</identifier>
  <identifier type="uri">https://www.europarl.europa.eu/thinktank/en/document.html?reference=EPRS_STU(2020)641507</identifier>
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    <url displayLabel="acceso al documento">https://www.europarl.europa.eu/RegData/etudes/STUD/2020/641507/EPRS_STU(2020)641507_EN.pdf</url>
  </location>
  <location>
    <url displayLabel="Más información">https://www.europarl.europa.eu/thinktank/en/document.html?reference=EPRS_STU(2020)641507</url>
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