Suchergebnisse - Algorithm transparency vs. explainability

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  1. 1

    On conflicts between ethical and logical principles in artificial intelligence von D’Acquisto, Giuseppe

    ISSN: 0951-5666, 1435-5655
    Veröffentlicht: London Springer London 01.12.2020
    Veröffentlicht in AI & society (01.12.2020)
    “… Artificial intelligence is nowadays a reality. Setting rules on the potential outcomes of intelligent machines, so that no surprise can be expected by humans …”
    Volltext
    Journal Article
  2. 2

    The Effects of Explainability and User Control on Algorithmic Transparency: The Moderating Role of Algorithmic Literacy von Moon, Jang Ho, Kim, Seheon, Jung, Youngju, Bang, Jaeyeon, Sung, Yongjun

    ISSN: 2152-2723, 2152-2723
    Veröffentlicht: United States 01.07.2025
    Veröffentlicht in Cyberpsychology, behavior and social networking (01.07.2025)
    “… In response, platforms have introduced transparency features such as algorithm-based recommendation explanations and user control features …”
    Weitere Angaben
    Journal Article
  3. 3

    It is Not "Accuracy vs. Explainability"-We Need Both for Trustworthy AI Systems von Petkovic, Dragutin

    ISSN: 2637-6415, 2637-6415
    Veröffentlicht: New York IEEE 01.03.2023
    Veröffentlicht in IEEE transactions on technology and society (01.03.2023)
    “… However, AI systems may produce errors, can exhibit bias, may be sensitive to noise in the data, and often lack technical and judicial transparency resulting in reduction in trust and challenges to their adoption …”
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    Journal Article
  4. 4

    Detection of COVID-19 in X-ray Images Using Densely Connected Squeeze Convolutional Neural Network (DCSCNN): Focusing on Interpretability and Explainability of the Black Box Model von Ali, Sikandar, Hussain, Ali, Bhattacharjee, Subrata, Athar, Ali, Abdullah, Kim, Hee-Cheol

    ISSN: 1424-8220, 1424-8220
    Veröffentlicht: Switzerland MDPI AG 01.12.2022
    Veröffentlicht in Sensors (Basel, Switzerland) (01.12.2022)
    “… The novel coronavirus (COVID-19), which emerged as a pandemic, has engulfed so many lives and affected millions of people across the world since December 2019 …”
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    Journal Article
  5. 5

    Reflections and attentiveness on eXplainable Artificial Intelligence (XAI). The journey ahead from criticisms to human–AI collaboration von Herrera, Francisco

    ISSN: 1566-2535
    Veröffentlicht: Elsevier B.V 01.09.2025
    Veröffentlicht in Information fusion (01.09.2025)
    “… ). As AI systems grow in size and complexity, ensuring interpretability and transparency becomes essential, especially in high-stakes applications …”
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    Journal Article
  6. 6

    From Black Box to Glass Box: A Practical Review of Explainable Artificial Intelligence (XAI) von Liu, Xiaoming, Huang, Danni, Yao, Jingyu, Dong, Jing, Song, Litong, Wang, Hui, Yao, Chao, Chu, Weishen

    ISSN: 2673-2688, 2673-2688
    Veröffentlicht: Basel MDPI AG 01.11.2025
    Veröffentlicht in AI (Basel) (01.11.2025)
    “… ”, limiting trust and accountability. However, most existing reviews treat explainability either as a technical problem or a philosophical issue, without connecting interpretability techniques to their real-world implications …”
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    Journal Article Book Review
  7. 7

    Artificial intelligence in diabetes care: from predictive analytics to generative AI and implementation challenges von Deng, Mengqi, Yang, Ruiye, Zheng, Xiaoran, Deng, Yaoqi, Jiang, Junyi

    ISSN: 1664-2392, 1664-2392
    Veröffentlicht: Switzerland Frontiers Media S.A 19.11.2025
    Veröffentlicht in Frontiers in endocrinology (Lausanne) (19.11.2025)
    “… From a technology point of view, explainability solutions and culturally-aware design align transparency with cultural sensibility …”
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    Journal Article
  8. 8

    A cloud-based architecture for explainable Big Data analytics using self-structuring Artificial Intelligence von Mills, Nishan, Issadeen, Zafar, Matharaarachchi, Amali, Bandaragoda, Tharindu, De Silva, Daswin, Jennings, Andrew, Manic, Milos

    ISSN: 2731-0809, 2731-0809
    Veröffentlicht: Cham Springer International Publishing 01.12.2024
    Veröffentlicht in Discover Artificial Intelligence (01.12.2024)
    “… It is increasingly challenging for conventional AI algorithms to process and transform this data, analyse and visualise a broad spectrum of insights, and then formulate the explainability …”
    Volltext
    Journal Article
  9. 9

    Managing Paradoxical Tensions in the Implementation of Explainable AI for Product Innovation von Amarilli, Fabrizio, Uboldi, Sara, Saraceni, Francesca, Tencati, Lorenzo

    Veröffentlicht: IEEE 23.07.2025
    “… We identify four persistent tensions: automation vs. human judgment, transparency vs. complexity, speed vs …”
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    Tagungsbericht
  10. 10

    Systematic Literature Review On Explainable AI In Finance: Methods, Applications, And Research Gaps von Bhardwaj, Alok

    ISSN: 2582-2160, 2582-2160
    Veröffentlicht: 28.10.2025
    “… ” algorithms still hinder financial organizations. SHAP, LIME, Integrated Gradients, and Layer-wise Relevance Propagation increase model transparency, accountability, and confidence …”
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    Journal Article
  11. 11

    Consumer Responses to Algorithmic Decisions von Demirdag, Bilge Ipek

    ISBN: 9798802748510
    Veröffentlicht: ProQuest Dissertations & Theses 01.01.2022
    “… Nevertheless, people are often algorithm averse, that is, they are less willing to rely on algorithms than humans in tasks such as forecasting …”
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    Dissertation
  12. 12

    Understanding the Role of Interactivity and Explanation in Adaptive Experiences von Guo, Lijie

    ISBN: 9798381373066
    Veröffentlicht: ProQuest Dissertations & Theses 01.01.2023
    “… Whether the currently ongoing research on adaptive experiences has focused on personalization algorithms, explainability, user engagement, or privacy and security, there is growing interest …”
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    Dissertation
  13. 13

    Machine Learning for Patent Intelligence Opportunities and Challenges von Denter, Nils

    ISBN: 9798315718505
    Veröffentlicht: ProQuest Dissertations & Theses 01.01.2022
    “… The analysis of large data volumes for decision-making has evolved from a sideline to a key driver of economic success in the business world of today. As being …”
    Volltext
    Dissertation