Algorithmic bias
6 articles · search the full text for this term
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A Study on the Ethical Implications and Data Privacy Challenges in the Age of Artificial Intelligence
Abstract: The fast adoption of Artificial Intelligence (AI) in areas like education, business, and everyday life comes with both tectonic and important ethical and data privacy issues. This paper examines the principle-practice divide between the ideals of the ethics as they are set and applied in the realities of AI implementation. The study is based on a mixed-methodology design, comprising of a quantitative survey of 52 participants and a qualitative study …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 Read article
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Revolutionizing Gender Justice: The Intersection of AI and Third-Gender Rights in Indian Legal Systems
Abstract: Artificiаl intеlligеncе (AI) аnd third-gеndеr rights in Indiа convеrgе аt а рivotаl juncturе for аdvаncing еquitаblе justicе systems. A trаnsformаtivе cараcity emеrgеs whеn аlgorithmic tools аrе strаtеgicаlly alignеd with lеgаl frаmеworks, раrticulаrly in reducing systemic bаrriеrs through еnhаncеd judiciаl аccеssibility. This аnаlysis еvаluаtеs AI’s duаl rolе аs both cаtаlyst аnd chаllеngе within Indiа’s evolving рolicy lаndscаре, focusing on thrее domains: lеgislаtivе dеsign, рredictivе jurisрrudеncе, аnd rights-bаsеd govеrnаncе structurеs. Currеnt rеsеаrch …
Published in Recent Trends in Social Studies · Vol. 3, Issue 1, 2026 · pp. 25–31 Read article
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Human-in-the-Loop AI in HR Decision-Making: Insights from Big 4 AI Governance Reports
Abstract: The integration of artificial intelligence (AI) in human resource (HR) decision-making has transformed recruitment, performance evaluations, and talent management. However, biases embedded in AI-driven HR systems present significant ethical and operational challenges. Human-in-the-Loop (HITL) AI offers a hybrid approach that combines AI efficiency with human oversight to enhance fairness and accountability. This paper systematically analyses HITL AI in HR decision-making using qualitative analysis of AI governance reports from Big 4 …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 43–50 Read article
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AI Bias: Causes, Impacts, and Ways to Address It
Abstract: As artificial intelligence (AI) continues to permeate various aspects of society, from healthcare and criminal justice to finance and hiring, concerns over its ethical implications have gained increasing attention. A significant ethical concern is the existence of bias in AI systems. Such biases, often rooted in the prejudices present in training data, can lead to unfair and discriminatory consequences, disproportionately affecting marginalized groups. This paper examines the ethical challenges related …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 55–62 Read article
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Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Unveiling Fairness: A Quest for Ethical Artificial Intelligence and Bias Mitigation
Abstract: Artificial intelligence (AI) systems have become ubiquitous across areas like finance, healthcare, employment, and criminal justice. However, they suffer from issues of unfair bias, lack of transparency, and broad ethical implications impacting vulnerable societal groups disproportionately. This paper reviews key challenges around AI ethics and bias while proposing data-driven guidelines mitigating such algorithmic harms through rigorous statistical testing, predictive modeling ensembles adjusting distortion vectors and AI audits by domain experts …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 28–31 Read article