Risultati della ricerca - "Algorithmic fairness"

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  1. 1

    Ethical theories, governance models, and strategic frameworks for responsible AI adoption and organizational success di Mitra Madanchian, Hamed Taherdoost, Hamed Taherdoost

    Pubblicazione 2025-07-01

    As artificial intelligence (AI) becomes integral to organizational transformation, ethical adoption has emerged as a strategic concern. This paper reviews ethical theories, governance models, and implementation strategies that enable responsible AI integration in business contexts. It explores how e...

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  2. 2

    Clinical Algorithms and the Legacy of Race-Based Correction: Historical Errors, Contemporary Revisions and Equity-Oriented Methodologies for Epidemiologists di Horsfall LJ, Bondaronek P, Ive J, Poduval S

    Pubblicazione 2025-07-01

    Laura J Horsfall, Paulina Bondaronek, Julia Ive, Shoba Poduval Institute of Health Informatics, University College London, London, UKCorrespondence: Laura J Horsfall, Email laura.horsfall@ucl.ac.ukAbstract: Clinical algorithms are widely used tools for predicting, diagnosing, and managing diseases....

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  3. 3

    Mitigating Algorithmic Bias Through Probability Calibration: A Case Study on Lead Generation Data di Miroslav Nikolić, Danilo Nikolić, Miroslav Stefanović, Sara Koprivica, Darko Stefanović

    Pubblicazione 2025-07-01

    Probability calibration is commonly utilized to enhance the reliability and interpretability of probabilistic classifiers, yet its potential for reducing algorithmic bias remains under-explored. In this study, the role of probability calibration techniques in mitigating bias associated with sensitiv...

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  4. 4

    Implications of algorithmic bias in AI-driven emergency response systems di Katsiaryna Bahamazava

    Pubblicazione 2026-01-01

    In this paper, we introduce a framework to evaluate the economic implications of algorithmic bias specifically for the emergency response systems that incorporate AI. Unlike existing research, which mostly addresses technical or ethical aspects in isolation, our approach integrates economic theory w...

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    “...Unlike existing research, which mostly addresses technical or ethical aspects in isolation, our approach integrates economic theory with algorithmic fairness to quantify and systematically analyze how biases in data quality and algorithm design impact resource allocation efficiency, response time equity, healthcare outcomes, and social welfare. ...”
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  5. 5

    Racial disparities in continuous glucose monitoring-based 60-min glucose predictions among people with type 1 diabetes. di Helene Bei Thomsen, Livie Yumeng Li, Anders Aasted Isaksen, Benjamin Lebiecka-Johansen, Charline Bour, Guy Fagherazzi, William P T M van Doorn, Tibor V Varga, Adam Hulman

    Pubblicazione 2025-06-01

    Non-Hispanic white (White) populations are overrepresented in medical studies. Potential healthcare disparities can happen when machine learning models, used in diabetes technologies, are trained on data from primarily White patients. We aimed to evaluate algorithmic fairness in glucose predictions....

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    “...We aimed to evaluate algorithmic fairness in glucose predictions. This study utilized continuous glucose monitoring (CGM) data from 101 White and 104 Black participants with type 1 diabetes collected by the JAEB Center for Health Research, US. ...”
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  6. 6

    Ethical Dilemmas and Coping Strategies in the Use of Psychological Scales in the Era of Big Data di Lirong LIU, Yanan ZHENG

    Pubblicazione 2025-04-01

    Focusing on the ethical risks arising from the reconstruction of psychological scales due to innovations in big data technology, a systematic analysis is conducted on the research and current use of psychological scales within the context of big data. Ethical issues are explored across five dimensio...

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    “...In response, five strategies are proposed: establishing a comprehensive data lifecycle protection mechanism, innovating informed consent models, optimizing algorithm fairness assessments, constructing diverse datasets, and empowering vulnerable groups. ...”
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  7. 7

    Unifying The Evaluation Criteria Of Many Objectives Optimization Using Fuzzy Delphi Method di Rawia Tahrir Mohammed, Razali Yaakob, Nurfadhlina Mohd Sharef, Rusli Abdullah

    Pubblicazione 2021-12-01

    Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various ap...

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    “...Lastly, the most suitable criteria outcomes are formulated in the unifying model and evaluate by experts to verify the appropriateness and suitability of the model in assessing the MaOO algorithms fairly and effectively....”
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