Ethical Implication of Artificial Intelligence (AI) Adoption in Financial Decision Making

Computer and Information Science, Год журнала: 2024, Номер 17(1), С. 49 - 49

Опубликована: Апрель 30, 2024

The integration of artificial intelligence (AI) into the financial sector has raised ethical concerns that need to be addressed. This paper analyzes implications using AI in decision-making and emphasizes importance an framework ensure its fair trustworthy deployment. study explores various considerations, including address algorithmic bias, promote transparency explainability systems, adhere regulations protect equity, accountability, public trust. By synthesizing research empirical evidence, highlights complex relationship between innovation integrity finance. To tackle this issue, proposes a comprehensive actionable advocates for clear guidelines, governance structures, regular audits, collaboration among stakeholders. aims maximize potential while minimizing negative impacts unintended consequences. serves as valuable resource policymakers, industry professionals, researchers, other stakeholders, facilitating informed discussions, evidence-based decision-making, development best practices responsible sector. ultimate goal is fairness, transparency, accountability reaping benefits both society.

Язык: Английский

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Ethical Challenges in the Integration of Artificial Intelligence in Palliative Care

Journal of Medicine Surgery and Public Health, Год журнала: 2024, Номер unknown, С. 100158 - 100158

Опубликована: Ноя. 1, 2024

Язык: Английский

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Ethical Considerations in AI-Enabled Healthcare

Studies in computational intelligence, Год журнала: 2025, Номер unknown, С. 271 - 282

Опубликована: Янв. 1, 2025

Язык: Английский

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Opportunities and Barriers to Artificial Intelligence Adoption in Palliative/Hospice Care for Underrepresented Groups

Journal of Hospice and Palliative Nursing, Год журнала: 2025, Номер unknown

Опубликована: Апрель 2, 2025

Underrepresented groups (URGs) in the United States, including African Americans, Latino/Hispanic Asian Pacific Islanders, and Native face significant barriers to accessing hospice palliative care. Factors such as language barriers, cultural perceptions, mistrust healthcare systems contribute underutilization of these services. Recent advancements artificial intelligence (AI) offer potential solutions challenges by enhancing sensitivity, improving communication, personalizing This article aims synthesize literature on AI palliative/hospice care for URGs through Technology Acceptance Model (TAM), highlighting current research application practice. The scoping review methodology, based framework developed Arksey O’Malley, was applied rapidly map field A systematic search conducted 9 databases identify studies examining applications URGs. Articles were independently assessed 2 reviewers then synthesized via narrative lens TAM framework, which focuses technology acceptance factors perceived ease use usefulness. Seventeen identified. Findings suggest that has improve decision-making, enhance timely referrals, bridge gaps. Artificial tools found predictive accuracy, support serious illness assist addressing thus promoting equitable However, limited generalizability, biases data, infrastructure noted, hindering full adoption settings. transformative enabling more interventions. fully realize its potential, must address data biases, limitations, nuances. Future should prioritize developing culturally competent are transparent, explainable, scalable ensure access services all populations.

Язык: Английский

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Smart healthcare in mobile hospitals: enhancing response to Disease X

BMC Infectious Diseases, Год журнала: 2025, Номер 25(1)

Опубликована: Апрель 10, 2025

Scientific and technological advancements have significantly augmented our capacity to comprehend manage "Disease X," while improving the efficiency accuracy of outbreak management. Infectious disease prevention control technology is advancing toward unmanned intelligent methods, shifting from a traditional reactive response public health emergencies more proactive efficient management mechanism. This study aims investigate transformation mobile hospitals, with objective bolstering their emergency capabilities fortifying strategies for unknown infectious diseases. This, in turn, seeks mitigate spread epidemics protect health. Semi-structured interviews 10 experts were conducted. A framework analysis was used organize interview results distill experts' overall views on smart building hospitals. The hospitals plays crucial role responding emergencies. status analyzed through five key dimensions: significance, characteristics, challenges, necessity feasibility, influencing factors. When confronting emergencies, offer significant advantages over medical institutions. In addressing these accordance contemporary trends, facilitating swift epidemic responses, precise patient management, resource allocation, improved adaptability diverse environments service demands. It sustainable biosafety system.

Язык: Английский

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Artificial Intelligence in Religious Education: Ethical, Pedagogical, and Theological Perspectives

Religions, Год журнала: 2025, Номер 16(5), С. 563 - 563

Опубликована: Апрель 28, 2025

This study investigates the integration of Artificial Intelligence (AI) in Religious Education (RE), a field traditionally rooted spiritual formation and human interaction. Amid increasing digital transformation education, theological institutions are exploring AI tools for teaching, assessment, pastoral engagement. Using critical literature review analysis institutional case studies, paper examines historical development current applications general contexts, ethical challenges it introduces, especially regarding decision making, data privacy, bias as well didactically grounded opportunities such AI-mediated dialogic simulations. The identifies both pedagogical advantages AI, personalization administrative efficiency, risks distortion, overreliance, epistemic conformity. It presents range real-world implementations from like Harvard Divinity School Oxford Centre Digital Theology, highlighting best practices cautionary approaches. findings suggest that can enrich RE when deployed thoughtfully ethically, but must not replace relational formational aspects central to RE. concludes by recommending policy development, oversight, interdisciplinary collaboration guide responsible integration. research contributes growing discourse on how be aligned with intellectual goals rapidly evolving age.

Язык: Английский

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AI in Financial Decision Making

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 125 - 142

Опубликована: Апрель 25, 2025

This chapter examines how technology and artificial intelligence (AI) are revolutionizing several industries by enhancing company processes' accuracy, speed, trust. When combined, they assist companies in automating, augmenting, achieving authenticity their workflows. For example, blockchain financial services increase the speed accuracy of procedures like loan approvals. combination increases decreases manual labor, fosters consumer Better care treatments possible healthcare industry thanks to blockchain's secure record-keeping intelligence's data analysis capabilities, which give clinicians access patient records while maintaining privacy. AI manage inventory, optimize routes, even monitor carbon emissions for sustainability. Early success indicates a bright future, despite certain obstacles correct keeping tools current. By utilizing these solutions, businesses may enhance customer happiness, security, save time.

Язык: Английский

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Emotional Intelligence and AI in Geriatric Nursing

Advances in human and social aspects of technology book series, Год журнала: 2024, Номер unknown, С. 199 - 232

Опубликована: Окт. 18, 2024

The rise of Artificial Intelligence (AI) in healthcare has led to significant advancements geriatric nursing, transforming both clinical outcomes and care delivery. Yet, as AI plays an increasing role patient care, there is growing recognition the need balance technological innovation with compassionate, human-centred care. This chapter explores how emotional intelligence (EI) can complement one another improve physical mental health older adults. examines critical nursing discusses support, rather than replace, empathetic emotionally aware provided by nurses. Through case studies, practical applications, theoretical analysis, this illustrates integrating EI enhance while maintaining human touch essential nursing. Ethical considerations, such dignity autonomy, future AI-driven world are also explored.

Язык: Английский

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A Deep Learning Framework Using Data Augmentation for Accuracy Improvement to Analyze Users Posts on Social Media to Find Signs of Mental Illness

International Journal on Recent and Innovation Trends in Computing and Communication, Год журнала: 2023, Номер 11(6), С. 509 - 513

Опубликована: Июнь 30, 2023

Through their posts on social media, users frequently express feelings. A deep learning model was developed for this study to determine a user’s mental state based the data they posted. We gathered articles purpose from Reddit forums dedicated health. Our suggested may disorder, anxiety, depression and Schizophrenia by examining posting information published users. Based posts, we think our algorithm can help identify people who could be experiencing illness. The consequences of model, which used in combination other methods track health individuals use internet extensively, are also discussed paper.

Язык: Английский

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A Dense Network Model for Outlier Prediction Using Learning Approaches

International Journal on Recent and Innovation Trends in Computing and Communication, Год журнала: 2023, Номер 11(11), С. 548 - 559

Опубликована: Дек. 31, 2023

There are various sub-categories in outlier prediction and the investigators show less attention to related domains like outliers audio recognition, video music etc. However, this research is specific medical data analysis. It specifically concentrates on predicting from database. Here, feature mapping representation achieved by adopting stacked LSTM-based CNN. The extracted features fed as an input Linear Support Vector Machine () used for classification purposes. Based analysis, it known that there a strong correlation between individual's emotions. can be analyzed both static dynamic manner. Adopting learning approaches done boost drawbacks of one another. statistical analysis with MATLAB 2016a environment where metrics ROC, MCC, AUC, co-efficiency, accuracy evaluated compared existing standard CNN, SVM, logistic regression, multi-layer perceptrons, so on. anticipated model shows superior outcomes, more concentration provided select emotion recognition dataset connected all sub-domains.

Язык: Английский

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