Search
33 articles for “algorithmic fairness”
-
The Future of Healthcare: Role of Artificial Intelligence in Revolutionizing Nursing
Abstract: Artificial intelligence (AI) is rapidly transforming the healthcare industry, and nursing professionals stand to benefit significantly from its integration. This article explores the role of AI in revolutionizing nursing, highlighting its applications, benefits, challenges, and ethical considerations. Drawing on examples from countries actively integrating AI into nursing services such as the United States, the United Kingdom, China, and Japan, the article discusses how AI supports nursing tasks, enhances patient care, …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 1, 2024 · pp. 1–5 Read article
-
The New Digital Accord: Ethics, Society and the Future of Online Interaction
Abstract: In a time when digital technology feels like our second home, every click leaves a mark, and every share holds significance. The ‘New Digital Accord’ aims to explore the complex relationship between technological progress and ethical responsibilities, examining how our constant connectivity shapes social behaviours, digital safety, and moral values. This paper addresses key challenges such as cybersecurity threats, misinformation, digital addiction, online harassment, and the ethical questions surrounding artificial …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 3, 2025 · pp. 102–113 Read article
-
Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
-
Revolution of Artificial Intelligence and Machine Learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are profoundly transforming various industries by introducing groundbreaking technologies such as deep learning, federated learning, reinforcement learning, and natural language processing. These innovations are not only reshaping the way organizations operate but are also opening new avenues for solving complex problems across diverse sectors, including healthcare, finance, transportation, and more. This study provides a comprehensive exploration of these emerging technologies, emphasizing their practical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 38–44 Read article
-
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
-
Ethical Considerations in AI-Driven Rehabilitation Robotics: Balancing Innovation and Responsibility
Abstract: Artificial intelligence (AI) is transforming robotics rehabilitation by introducing advanced capabilities such as adaptive therapy, real-time feedback, and personalized assistance, significantly improving outcomes for individuals with neurological and physical impairments. These AI-powered systems offer high levels of precision and consistency in therapy delivery, making them especially beneficial in pediatric and adult rehabilitation settings where engagement and tailored interventions are crucial. However, the integration of AI in healthcare also presents critical …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 24–29 Read article
-
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
-
Analyzing the Cognitive Proficiencies of Artificial Intelligence Within the Legal Paradigm: Prospects Within the Jurisdiction of India
Abstract: The swift progress of artificial intelligence (AI) has become a pivotal factor in various industries, notably affecting the legal sector. This study extensively investigates the substantial effects of AI on legal research and case analysis, mapping out the progression of AI technology within the legal domain. The exploration goes beyond mere acknowledgment of AI‘s presence, delving into a nuanced analysis of its potential advantages and the formidable challenges it poses …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 84–112 Read article
-
Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
-
Charting the Path Forward: An In-Depth Analysis of Breakthroughs and Hurdles in Artificial Intelligence
Abstract: Recent years have witnessed tremendous progress in artificial intelligence (AI), fueled by exponential increases in processing power and data accessibility. These developments have made it possible for AI to be widely used in a variety of industries, such as healthcare, finance, autonomous driving, and more. Significant difficulties are presented by the "black-box" nature of many AI systems, which lack transparency and the capacity to explain. By encouraging algorithms that can …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 13–23 Read article
-
AI-Driven Promotion Platforms: Increasing Customer Engagement in Banking
Abstract: Artificial Intelligence has been in talk since data was considered as an asset. Using this data, prolific information has been extracted to gather detailed information and create datasets. Artificial intelligence is shaping the narrative of the world in the 21st century. It has become a driving force behind innovation, influencing various industries and redefining traditional practices. Artificial intelligence has revolutionized customer engagement strategies across industries, particularly Banking. This study explores …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 87–92 Read article
-
Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
-
Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article