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            <front>

                <journal-meta>
                                                                <journal-id>deneti̇şi̇m</journal-id>
            <journal-title-group>
                                                                                    <journal-title>Denetişim</journal-title>
            </journal-title-group>
                            <issn pub-type="ppub">1308-8335</issn>
                                                                                                        <publisher>
                    <publisher-name>Kamu İç Denetçileri Derneği</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id pub-id-type="doi">10.58348/denetisim.1540801</article-id>
                                                                <article-categories>
                                            <subj-group  xml:lang="en">
                                                            <subject>Finance Studies (Other)</subject>
                                                    </subj-group>
                                            <subj-group  xml:lang="tr">
                                                            <subject>Maliye Çalışmaları (Diğer)</subject>
                                                    </subj-group>
                                    </article-categories>
                                                                                                                                                        <title-group>
                                                                                                                        <article-title>VERGİ DENETİMİNİ REVİZE ETMEK: ALGORİTMİK KARAR ALMA SÜREÇLERİNDE ÜÇÜNCÜ TARAF KONTROLÖRÜ OLARAK İNSAN FAKTÖRÜNÜN İNCELENMESİ</article-title>
                                                                                                                                                                                                <trans-title-group xml:lang="en">
                                    <trans-title>REVISING THE TAX AUDIT: ANALYSING THE HUMAN FACTOR AS A THIRD PARTY CONTROLLER IN ALGORITHMIC DECISION-MAKING PROCESSES</trans-title>
                                </trans-title-group>
                                                                                                    </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0001-9577-4348</contrib-id>
                                                                <name>
                                    <surname>Yücel</surname>
                                    <given-names>Ayşegül</given-names>
                                </name>
                                                                    <aff>BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-9337-2895</contrib-id>
                                                                <name>
                                    <surname>Bozdoğanoğlu</surname>
                                    <given-names>Burçin</given-names>
                                </name>
                                                                    <aff>BANDIRMA ONYEDİ EYLÜL ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20241201">
                    <day>12</day>
                    <month>01</month>
                    <year>2024</year>
                </pub-date>
                                                    <issue>31</issue>
                                        <fpage>47</fpage>
                                        <lpage>58</lpage>
                        
                        <history>
                                    <date date-type="received" iso-8601-date="20240829">
                        <day>08</day>
                        <month>29</month>
                        <year>2024</year>
                    </date>
                                                    <date date-type="accepted" iso-8601-date="20241003">
                        <day>10</day>
                        <month>03</month>
                        <year>2024</year>
                    </date>
                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 2009, Denetişim</copyright-statement>
                    <copyright-year>2009</copyright-year>
                    <copyright-holder>Denetişim</copyright-holder>
                </permissions>
            
                                                                                                <abstract><p>Yapay zeka teknolojisi, kamu ve özel sektörün iş akışlarında zaman ve maliyetten tasarruf etme amacıyla kullanılmaya başlayan, işlenen veri ve kodlara bağlı öğrenebilen, analiz edebilen, karar alabilen dijital bir araçtır. Derin ve sürekli öğrenme yetisine sahip yapay zeka teknolojisi kullanıldığı adalet, savunma, sağlık, hukuk gibi önemli konularda algoritmalarına bağlı olarak kararlar alabilmekte, işlediği ve tasnif ettiği veriler sayesinde tahmine dayalı işlemler yapabilmektedir. Fakat yapay zeka teknolojisinin kararları hangi veri setleri ve kodlara dayanarak ve hangi gerekçelerle aldığının şeffaf olmayışı nedeniyle hukuka aykırı sonuçların doğması muhtemeldir. Böyle bir durumda yapay zeka kullanıcıları şeffaf olmayan süreçler sonucunda alınan kararların hukuki ve fiili etkilerinden zarar görme ihtimali taşımaktadır. Bu durum, yaşanabilecek hak ihlallerinin önüne geçmek amacıyla, insan ürünü olan yapay zekanın  tasarım ve uygulama aşamalarında denetlenmesi gerekliliğini gündeme getirmektedir. Fakat yapay zeka teknolojisinin denetlenmesine dair hukuki mevzuatın yetersizliği, hangi denetim türünün hangi aşamada uygulacağının dahi belirsizliği literatürde büyük bir eksikliğe neden olmaktadır. Çalışmada, yapay zeka teknolojisinin hangi yöntem ve yollar izlenerek denetleneceği tartışılmakta, geleneksel denetim yollarının dijital dünyada etkisinin kaybolduğu belirtilmektedir. Yeni bir denetim türü olan üçüncü taraf denetiminin özellikle etik temelli yöntemi kullanmasının yapay zeka denetiminde daha etkili olacağı düşünülmektedir. Çalışma, yapay zeka denetimini genel bir bakış açısıyla ele aldıktan sonra, vergilendirme sürecinde kullanılan yapay zeka teknolojisinin neden olacağı hak ihlallerinin önüne geçilmesi amacıyla vergi denetim sürecine revizyon talebinde bulunmakta, kesintisiz ve sürekli bir vergi yönetimi açısından geleneksel denetim modelleri ile üçüncü taraf denetimlerinin işbirliği içinde çalıştığı karma bir denetim modeli önermektedir.</p></abstract>
                                                                                                                                    <trans-abstract xml:lang="en">
                            <p>Artificial intelligence technology is a digital tool that can learn, analyse and make decisions based on processed data and codes, which has started to be used in the workflows of the public and private sectors in order to save time and cost. Artificial intelligence technology, which is capable of deep and continuous learning, can make decisions on important issues such as justice, defence, health and law depending on its algorithms, and can make predictions based on the data it processes and classifies. However, it is possible that unlawful consequences may arise due to the non-transparency of the data sets and codes on which artificial intelligence technology makes decisions and on what grounds. In such a case, artificial intelligence users are likely to be harmed by the legal and actual effects of decisions taken as a result of non-transparent processes. This situation brings up the necessity of supervising artificial intelligence, which is a human product, at the design and implementation stages in order to prevent possible violations of rights. However, the inadequacy of the legal legislation on the supervision of artificial intelligence technology and the uncertainty of which type of supervision will be applied at which stage causes a great deficiency in the literature. In this study, the methods and ways of auditing artificial intelligence technology are discussed, and it is stated that the traditional audit methods have lost their effect in the digital world. It is thought that third-party auditing, which is a new type of auditing, will be more effective in AI auditing, especially if it uses the ethics-based method. After discussing artificial intelligence auditing from a general perspective, the study calls for a revision of the tax audit process in order to prevent violations of rights caused by artificial intelligence technology used in the taxation process, and proposes a hybrid audit model in which traditional audit models and third-party audits work in cooperation for an uninterrupted and continuous tax management.</p></trans-abstract>
                                                            
            
                                                            <kwd-group>
                                                    <kwd>Vergi Denetimi</kwd>
                                                    <kwd>  Yapay Zekâ</kwd>
                                                    <kwd>  Algoritmik Karar Alma</kwd>
                                                    <kwd>  Kara Kutu</kwd>
                                                    <kwd>  Üçüncü Taraf Denetimi</kwd>
                                            </kwd-group>
                                                        
                                                                            <kwd-group xml:lang="en">
                                                    <kwd>Tax Audit</kwd>
                                                    <kwd>  Artificial Intelligence</kwd>
                                                    <kwd>  Algorithmic Decision Making</kwd>
                                                    <kwd>  Black Box</kwd>
                                                    <kwd>  Third-Party Audit</kwd>
                                            </kwd-group>
                                                                                                            </article-meta>
    </front>
    <back>
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