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            <name>Title</name>
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                <text>Faculty Publications</text>
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    <name>Conference Paper</name>
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          <name>Creator</name>
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              <text>Kumar Jain, Yogesh; Sahu, Santosh; Singh, Jagriti; Maheshwari, Abhishek; Choudhary, Deepak Kumar; Bhagwati, Malleshappa T.</text>
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          <name>Title</name>
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              <text>Scalable AI Models for Real-Time Ethical Decision-Making in Autonomous Business Operations</text>
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          <name>Date</name>
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              <text>01-01-2025</text>
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              <text>2025 International Conference on Automation and Computation, AUTOCOM 2025;pp.1503-1508</text>
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              <text>&lt;a href="https://doi.org/10.1109/AUTOCOM64127.2025.10957624" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/AUTOCOM64127.2025.10957624&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105003902469?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105003902469?origin=resultslist&lt;/a&gt;</text>
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              <text>Kumar Jain Y., Dr. D. Y. Patil Vidyapeeth - Col, Pune, India; Sahu S., Amity School of Engineering and Technology (ASET), Amity University, Department of Cse, Gwalior, India; Singh J., Manipal University Jaipur, India; Maheshwari A., School of Commerce, Finance and Accountancy, Christ (Deemed to be) University, Ghaziabad, India; Choudhary D.K., Muzaffarpur Institute of Technology, Department of Computer Science and Engineering, Muzaffarpur, India; Bhagwati M.T., Dr. D. Y. Patil Vidyapeeth - Col, Pune, India</text>
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              <text>This study explores the application of scalable AI for real-time ethical decision-making in autonomous business running. The study takes into an account the crucial concerns i.e., the bias, fairness, robustness etc., working on the congruency of ethics and operational efficiency. This research investigates AI's impact on decision quality through a series of analyses interpreting visuals (in the form of decision accuracy comparisons, stakeholder satisfaction, and resilience when facing adversarial scenarios). Results show that scalable AI models display higher ethical adaptability and an ability to learn from changing regulatory and operational environments. The research emphasises the need for proper balance of morals and technological advancement in order to enable transparency, accountability, and reliability in autonomous devices.  2025 IEEE.</text>
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              <text>AIScalable AI; Autonomous Business Operations; Bias Mitigation; Ethical Decision-Making; Fairness and Transparency; Gradient Boosting Decision Trees; Neural Network; Prune NN; SSNN</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>ISBN: 979-833154237-5;</text>
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              <text>English</text>
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              <text>Restricted Access; Hardcopy may be available in the library</text>
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              <text>online</text>
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