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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMIR</journal-id>
      <journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id>
      <journal-title>Journal of Medical Internet Research</journal-title>
      <issn pub-type="epub">1438-8871</issn>
      <publisher>
        <publisher-name>JMIR Publications</publisher-name>
        <publisher-loc>Toronto, Canada</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">v25i1e50591</article-id>
      <article-id pub-id-type="pmid">37651167</article-id>
      <article-id pub-id-type="doi">10.2196/50591</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Letter to the Editor</subject>
        </subj-group>
        <subj-group subj-group-type="article-type">
          <subject>Letter to the Editor</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>AI Increases the Pressure to Overhaul the Scientific Peer Review Process. Comment on “Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles: Pandora’s Box Has Been Opened”</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Leung</surname>
            <given-names>Tiffany</given-names>
          </name>
        </contrib>
      </contrib-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Liu</surname>
            <given-names>Nicholas</given-names>
          </name>
          <degrees>BA</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <address>
            <institution>John A Burns School of Medicine</institution>
            <institution>University of Hawai'i at Mānoa</institution>
            <addr-line>651 Ilalo St</addr-line>
            <addr-line>Honolulu, HI, 96813</addr-line>
            <country>United States</country>
            <phone>1 808 692 1000</phone>
            <email>nliu6@hawaii.edu</email>
          </address>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-9614-6941</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author">
          <name name-style="western">
            <surname>Brown</surname>
            <given-names>Amy</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-7550-5308</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>John A Burns School of Medicine</institution>
        <institution>University of Hawai'i at Mānoa</institution>
        <addr-line>Honolulu, HI</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>Department of Quantitative Health Sciences</institution>
        <institution>John A Burns School of Medicine</institution>
        <institution>University of Hawai'i at Mānoa</institution>
        <addr-line>Honolulu, HI</addr-line>
        <country>United States</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Nicholas Liu <email>nliu6@hawaii.edu</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2023</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>31</day>
        <month>8</month>
        <year>2023</year>
      </pub-date>
      <volume>25</volume>
      <elocation-id>e50591</elocation-id>
      <history>
        <date date-type="received">
          <day>6</day>
          <month>7</month>
          <year>2023</year>
        </date>
        <date date-type="accepted">
          <day>12</day>
          <month>8</month>
          <year>2023</year>
        </date>
      </history>
      <copyright-statement>©Nicholas Liu, Amy Brown. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.08.2023.</copyright-statement>
      <copyright-year>2023</copyright-year>
      <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
        <p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://www.jmir.org/2023/1/e50591" xlink:type="simple"/>
      <related-article related-article-type="commentary-article" id="v25i1e46924" ext-link-type="doi" xlink:href="10.2196/46924" vol="25" page="e46924" xlink:type="simple">http://www.jmir.org/2023/1/e46924/</related-article>
      <related-article related-article-type="commentary" id="v25i1e50844" ext-link-type="doi" xlink:href="10.2196/50844" vol="25" page="e50844" xlink:type="simple">http://www.jmir.org/2023/1/e50844/</related-article>
      <kwd-group>
        <kwd>artificial intelligence</kwd>
        <kwd>AI</kwd>
        <kwd>publications</kwd>
        <kwd>ethics</kwd>
        <kwd>neurosurgery</kwd>
        <kwd>ChatGPT</kwd>
        <kwd>Chat Generative Pre-trained Transformer</kwd>
        <kwd>language models</kwd>
        <kwd>fraudulent medical articles</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <p>Májovský and colleagues’ [<xref ref-type="bibr" rid="ref1">1</xref>] concern regarding OpenAI’s ChatGPT is valid. Seven months ago, the release of ChatGPT was quickly tempered by warnings of perpetuating biases and spreading misinformation. Artificial intelligence (AI) tools threaten to amplify preexisting issues in academic publishing, particularly the scientific peer review process. This outdated system is overwhelmed by the volume of new journals and papers produced by a growing global academic community [<xref ref-type="bibr" rid="ref2">2</xref>], a problem that AI is fit to accentuate. Here are three areas in need of modification:</p>
    <p>The scientific peer review process</p>
    <list list-type="bullet">
      <list-item>
        <p>The body of qualified reviewers is drowning in a rising sea of writers that includes top researchers, undergraduate students, and academics at all levels in between [<xref ref-type="bibr" rid="ref2">2</xref>].</p>
      </list-item>
      <list-item>
        <p>Peer review lacks formal standards or guidelines, as well as training, particularly in statistics [<xref ref-type="bibr" rid="ref3">3</xref>], creating a restricted and top-heavy pool of qualified reviewers [<xref ref-type="bibr" rid="ref2">2</xref>].</p>
      </list-item>
      <list-item>
        <p>Reviewers are declining to perform reviews more often since the notion of reviewing as a professional obligation fails to sufficiently recognize or reward the burden it imposes [<xref ref-type="bibr" rid="ref2">2</xref>].</p>
      </list-item>
      <list-item>
        <p>Peer review fraud, which involves conflicts of interest, influence, and false identities, has evolved out of a need for reviews.</p>
      </list-item>
    </list>
    <p>Publication pressure</p>
    <list list-type="bullet">
      <list-item>
        <p>The dearth of reviewers is compounded by the proliferation of plagiarized, fraudulent, and otherwise low-quality work [<xref ref-type="bibr" rid="ref4">4</xref>].</p>
      </list-item>
      <list-item>
        <p>Pressure to “publish or perish” has led to high-profile cases of academic fraud and likewise feeds “paper mills” that churn out questionable research for academics who are desperate to progress in their careers [<xref ref-type="bibr" rid="ref4">4</xref>].</p>
      </list-item>
      <list-item>
        <p>The proliferation of “for-profit” journals subverts respectful publishing through financialization that exploits and alienates scientists [<xref ref-type="bibr" rid="ref2">2</xref>].</p>
      </list-item>
    </list>
    <p>AI integration</p>
    <list list-type="bullet">
      <list-item>
        <p>Májovský et al [<xref ref-type="bibr" rid="ref1">1</xref>] displayed the effectiveness of ChatGPT as an open access ghostwriter, capable of fabricating a complete and convincing article in just one hour.</p>
      </list-item>
      <list-item>
        <p>In one study, only 63% of ChatGPT-generated abstracts were caught by reviewers as fakes [<xref ref-type="bibr" rid="ref5">5</xref>]. In response to such findings, Science is updating its license and editorial policies to prohibit AI-generated text, figures, or graphics [<xref ref-type="bibr" rid="ref5">5</xref>].</p>
      </list-item>
      <list-item>
        <p>Such staunch resistance is misguided; AI may not be an author per se, but its utility in all stages of research, from generating topics and compiling information to writing text, cannot be ignored. If an AI-generated, human-reviewed paper communicates quality research, why should it be disallowed? Moreover, how would we tell?</p>
      </list-item>
      <list-item>
        <p>Although AI-generated text detection software can help [<xref ref-type="bibr" rid="ref1">1</xref>], detection bypass tools are similarly available online.</p>
      </list-item>
    </list>
    <p>AI makes the need for high-quality peer reviews greater and more pressing than ever before. The cornerstone of scientific integrity is on the path to obsoletion without a viable successor. As academic pursuits become increasingly inseparable from industry, conceptualizing peer review as a duty to science will no longer suffice. Respecting and empowering the peer review system will involve considering reviewers as expert consultants, performing reviews as productive work, and creating system-wide guidelines that integrate (rather than resist) AI technologies. This problem, emerging from an imperative for success, needs a peer review system and publication process that has more teeth than trust, a commodity that served us well in the past, but whose restoration bears reinvention.</p>
  </body>
  <back>
    <app-group/>
    <glossary>
      <title>Abbreviations</title>
      <def-list>
        <def-item>
          <term id="abb1">AI</term>
          <def>
            <p>artificial intelligence</p>
          </def>
        </def-item>
      </def-list>
    </glossary>
    <fn-group>
      <fn fn-type="conflict">
        <p>None declared.</p>
      </fn>
    </fn-group>
    <ref-list>
      <ref id="ref1">
        <label>1</label>
        <nlm-citation citation-type="journal">
          <person-group person-group-type="author">
            <name name-style="western">
              <surname>Májovský</surname>
              <given-names>M</given-names>
            </name>
            <name name-style="western">
              <surname>Černý</surname>
              <given-names>M</given-names>
            </name>
            <name name-style="western">
              <surname>Kasal</surname>
              <given-names>M</given-names>
            </name>
            <name name-style="western">
              <surname>Komarc</surname>
              <given-names>M</given-names>
            </name>
            <name name-style="western">
              <surname>Netuka</surname>
              <given-names>D</given-names>
            </name>
          </person-group>
          <article-title>Artificial intelligence can generate fraudulent but authentic-looking scientific medical articles: Pandora’s box has been opened</article-title>
          <source>J Med Internet Res</source>
          <year>2023</year>
          <month>05</month>
          <day>31</day>
          <volume>25</volume>
          <fpage>e46924</fpage>
          <comment>
            <ext-link ext-link-type="uri" xlink:type="simple" xlink:href="https://www.jmir.org/2023//e46924/"/>
          </comment>
          <pub-id pub-id-type="doi">10.2196/46924</pub-id>
          <pub-id pub-id-type="medline">37256685</pub-id>
          <pub-id pub-id-type="pii">v25i1e46924</pub-id>
          <pub-id pub-id-type="pmcid">PMC10267787</pub-id>
        </nlm-citation>
      </ref>
      <ref id="ref2">
        <label>2</label>
        <nlm-citation citation-type="journal">
          <person-group person-group-type="author">
            <name name-style="western">
              <surname>Dance</surname>
              <given-names>A</given-names>
            </name>
          </person-group>
          <article-title>Stop the peer-review treadmill. I want to get off</article-title>
          <source>Nature</source>
          <year>2023</year>
          <month>02</month>
          <day>13</day>
          <volume>614</volume>
          <issue>7948</issue>
          <fpage>581</fpage>
          <lpage>583</lpage>
          <pub-id pub-id-type="doi">10.1038/d41586-023-00403-8</pub-id>
          <pub-id pub-id-type="medline">36781962</pub-id>
          <pub-id pub-id-type="pii">10.1038/d41586-023-00403-8</pub-id>
        </nlm-citation>
      </ref>
      <ref id="ref3">
        <label>3</label>
        <nlm-citation citation-type="journal">
          <person-group person-group-type="author">
            <name name-style="western">
              <surname>Ballester</surname>
              <given-names>PL</given-names>
            </name>
          </person-group>
          <article-title>Open science and software assistance: commentary on “Artificial intelligence can generate fraudulent but authentic-looking scientific medical articles: Pandora’s box has been opened”</article-title>
          <source>J Med Internet Res</source>
          <year>2023</year>
          <month>05</month>
          <day>31</day>
          <volume>25</volume>
          <fpage>e49323</fpage>
          <comment>
            <ext-link ext-link-type="uri" xlink:type="simple" xlink:href="https://www.jmir.org/2023//e49323/"/>
          </comment>
          <pub-id pub-id-type="doi">10.2196/49323</pub-id>
          <pub-id pub-id-type="medline">37256656</pub-id>
          <pub-id pub-id-type="pii">v25i1e49323</pub-id>
          <pub-id pub-id-type="pmcid">PMC10267777</pub-id>
        </nlm-citation>
      </ref>
      <ref id="ref4">
        <label>4</label>
        <nlm-citation citation-type="journal">
          <person-group person-group-type="author">
            <name name-style="western">
              <surname>Else</surname>
              <given-names>H</given-names>
            </name>
            <name name-style="western">
              <surname>Van Noorden</surname>
              <given-names>R</given-names>
            </name>
          </person-group>
          <article-title>The fight against fake-paper factories that churn out sham science</article-title>
          <source>Nature</source>
          <year>2021</year>
          <month>03</month>
          <day>23</day>
          <volume>591</volume>
          <issue>7851</issue>
          <fpage>516</fpage>
          <lpage>519</lpage>
          <pub-id pub-id-type="doi">10.1038/d41586-021-00733-5</pub-id>
          <pub-id pub-id-type="medline">33758408</pub-id>
          <pub-id pub-id-type="pii">10.1038/d41586-021-00733-5</pub-id>
        </nlm-citation>
      </ref>
      <ref id="ref5">
        <label>5</label>
        <nlm-citation citation-type="journal">
          <person-group person-group-type="author">
            <name name-style="western">
              <surname>Thorp</surname>
              <given-names>HH</given-names>
            </name>
          </person-group>
          <article-title>ChatGPT is fun, but not an author</article-title>
          <source>Science</source>
          <year>2023</year>
          <month>01</month>
          <day>27</day>
          <volume>379</volume>
          <issue>6630</issue>
          <fpage>313</fpage>
          <lpage>313</lpage>
          <pub-id pub-id-type="doi">10.1126/science.adg7879</pub-id>
          <pub-id pub-id-type="medline">36701446</pub-id>
        </nlm-citation>
      </ref>
    </ref-list>
  </back>
</article>
