Leveraging FinTech Compliance to Mitigate Cryptocurrency Volatility for Secure US Employee Retirement Benefits: Bitcoin ETF Case Study

Asian Journal of Economics Business and Accounting, Год журнала: 2024, Номер 24(4), С. 147 - 167

Опубликована: Фев. 26, 2024

The integration of cryptocurrencies, particularly Bitcoin, into retirement savings plans has recently garnered significant attention. This interest been amplified by the U.S. Securities and Exchange Commission's approval Bitcoin Exchange-Traded Funds (ETFs) in January 2024 Fidelity Investments' decision to include their 401(k) plans. These landmark developments represent a paradigm shift investment strategies, merging traditional financial planning with dynamic volatile world cryptocurrencies. entry introduces novel challenges, including increased volatility regulatory uncertainty, necessitating comprehensive examination its impacts on savings. study sought explore role Financial Technology (FinTech) managing these risks assess adequacy current frameworks. Employing quantitative research approach, collected data from 386 participants, FinTech practitioners portfolio managers through survey that combining closed-ended open-ended questions. Multiple regression was used analyze relationships between variables such as integration, compliance, risk associated cryptocurrency-inclusive portfolios. revealed inclusion significantly increases volatility. It also found advanced management techniques enhance mitigation, while frameworks are inadequate for governing cryptocurrencies A framework compliance shown effectively reduce risks. recommends cautious consideration portfolios, an emphasis assessing appetite participants. advocates enhanced use real-time management. suggests plan providers should adopt integrated technological innovations oversight, navigate complexities cryptocurrency investments effectively.

Язык: Английский

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Leading in a Time of Crisis: The Coronavirus Effect on Leadership in America

Asian Journal of Economics Business and Accounting, Год журнала: 2024, Номер 24(4), С. 1 - 20

Опубликована: Фев. 20, 2024

In light of the COVID-19 pandemic, an unprecedented global health emergency, study explores vulnerabilities and challenges faced by leadership. The crisis, exemplified issues such as misinformation around Omicron Boosters in rural America, has brought to complex interplay between leadership, public initiatives, societal dynamics. This scenario underscores study's aim: analyze understand specific attributes, styles, communication strategies that define effective crisis leadership within American context. Adopting a quantitative research methodology, conducted survey with 521 respondents, encompassing diverse cross-section society, including members minority communities, volunteers, students, healthcare workers, business owners, residents areas significantly impacted pandemic. survey, focused on collecting data through structured questionnaire, assess independent variables (transparency, empathy, stakeholder engagement, context-sensitive style, adaptable targeted communication, culturally sensitive strategies) dependent (success improved management), using Likert scale questions. collected were used test hypothesis, regression analysis. findings reveal significant insights: transparency, engagement stakeholders are crucial for successful leadership; styles more than rigid ones scenarios; targeted, improve management outcomes. These results underscore multifaceted nature importance nuanced, approaches times uncertainty while agrees assertions McGregor Burns (2004) Kouzes Posner (2023) leader’s competencies key moments this further reveals vitality stakeholders’ contributions Also, study’s align those Erickson (2021) transparency exhibiting empathy along is very essential Therefore, recommends developing qualities emphasize enhancing adaptability styles. Additionally, it highlights need strategies, tailored audiences.

Язык: Английский

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Exploring the Concept of Explainable AI and Developing Information Governance Standards for Enhancing Trust and Transparency in Handling Customer Data

Journal of Engineering Research and Reports, Год журнала: 2024, Номер 26(7), С. 244 - 268

Опубликована: Июнь 27, 2024

The increasing integration of Artificial Intelligence (AI) systems in diverse sectors has raised concerns regarding transparency, trust, and ethical data handling. This study investigates the impact Explainable AI (XAI) models robust information governance standards on enhancing use customer data. A mixed-methods approach was employed, combining a comprehensive literature review with survey 342 respondents across various industries. findings reveal that implementation XAI significantly increases user trust compared to black-box models. Additionally, strong positive correlation found between adoption data, highlighting importance transparency frameworks mechanisms. Furthermore, underscores critical role education fostering facilitating informed decision-making interactions. results emphasize need for organizations prioritize techniques, establish frameworks, invest education, foster culture use. These recommendations provide roadmap harness benefits while mitigating potential risks ensuring responsible trustworthy practices.

Язык: Английский

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AI for Identity and Access Management (IAM) in the Cloud: Exploring the Potential of Artificial Intelligence to Improve User Authentication, Authorization, and Access Control within Cloud-Based Systems

SSRN Electronic Journal, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

This comprehensive study explores the integration and effectiveness of Artificial Intelligence (AI) in Identity Access Management (IAM) within cloud environments. It primarily focuses on how AI can enhance user authentication, authorization, access control, addressing challenges possibilities computing. The adopts a mixed-methods approach, employing both quantitative qualitative analyses. A survey involving 582 cybersecurity experts provides insights into current state potential IAM, while multiple regression analysis examines impact various factors system effectiveness. Four hypotheses are explored: hardware software configurations accuracy (H1), influence computational environments reliability (H2), role demographic acceptance (H3), effect technological enhancements performance (H4). Findings indicate significant correlations between these IAM. Notably, security concerns accuracy; environment variations affect reliability; acceptance; such as feedback, advancements technology, continuous learning algorithms, transparency improve acceptance. These underscore need for advanced hardware, standardized software, user-centric design, improvement technologies effective IAM actionable recommendations service providers developers, emphasizing importance users development processes, ensuring transparency, adopting adaptive algorithms. Future research directions include longitudinal studies exploring demographic-specific responses to AI-integrated solutions.

Язык: Английский

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Formulating Global Policies and Strategies for Combating Criminal Use and Abuse of Artificial Intelligence

Archives of Current Research International, Год журнала: 2024, Номер 24(5), С. 612 - 629

Опубликована: Июнь 15, 2024

This study investigates the criminal use and abuse of artificial intelligence (AI), exploring effectiveness various mitigation strategies. It employs a mixed-methods approach, combining quantitative data from survey 211 experts with qualitative insights academic, governmental, industrial publications. The research examines four key hypotheses: impact public organizational awareness, role advanced detection technologies, ethical guidelines, influence penalties enforcement. findings reveal that technology, ethics, enforcement all contribute to mitigating AI misuse. concludes by proposing comprehensive strategies, including targeted awareness campaigns, investment in robust strengthened legal frameworks, effectively combat AI.

Язык: Английский

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Bias in adjudication: Investigating the impact of artificial intelligence, media, financial and legal institutions in pursuit of social justice

PLoS ONE, Год журнала: 2025, Номер 20(1), С. e0315270 - e0315270

Опубликована: Янв. 3, 2025

The latest global progress report highlights numerous challenges in achieving justice goals, with bias artificial intelligence (AI) emerging as a significant yet underexplored issue. This paper investigates the role of AI addressing within judicial system to promote equitable social justice. Analyzing weekly data from January 1, 2019, December 31, 2023, through wavelet quantile correlation, this study examines short, medium, and long-term impacts integrating AI, media, international legal influence (ILI), financial institutions (IFI) crucial factors Sustainable Development Goal 16 (SDG-16), which focuses on findings indicate that ILI, IFI can help reduce medium long term, although their effects appear mixed less short term. Our research proposes comprehensive policy framework addresses complexities implementing these technologies system. We conclude successfully requires supportive environment embraces technological innovation, backing, robust regulation prevent potential disruptions could reinforce inequalities, perpetuate structural injustices, exacerbate human rights issues, ultimately leading more biased outcomes

Язык: Английский

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Smart Media or Biased Media: The Impacts and Challenges of AI and Big Data on the Media Industry

Asian Journal of Research in Computer Science, Год журнала: 2024, Номер 17(7), С. 128 - 144

Опубликована: Июль 6, 2024

This study critically analyzes the impact of artificial intelligence (AI) and big data on media industry, focusing ethical challenges biases introduced by these technologies. The research aims to uncover extent which AI influence content personalization, creation, marketing, ramifications influences cultural diversity societal norms. A mixed-methods approach was employed, combining quantitative analysis through a survey 532 respondents qualitative thematic 10 academic literatures. findings reveal significant associations between automated creation tools biases, personalized recommendation systems echo chambers, algorithmic recommendations homogenization. Conversely, no association found analytics privacy concerns. highlights need for guidelines, enhanced diversity, strengthened measures, increased transparency mitigate in AI-driven platforms. These insights contribute broader understanding data's role shaping offering valuable implications future research, policy-making, industry practices.

Язык: Английский

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Real-Time Deepfake Video Detection Using Eye Movement Analysis with a Hybrid Deep Learning Approach

Electronics, Год журнала: 2024, Номер 13(15), С. 2947 - 2947

Опубликована: Июль 26, 2024

Deepfake technology uses artificial intelligence to create realistic but false audio, images, and videos. poses a significant threat the authenticity of visual content, particularly in live-stream scenarios where immediacy detection is crucial. Existing approaches have limitations challenges, prompting need for more robust accurate solutions. This research proposes an innovative approach: combining eye movement analysis with hybrid deep learning model address real-time detection. The proposed integrates two neural network architectures, MesoNet4 ResNet101, leverage their respective architectures’ strengths effective classification. lightweight CNN designed explicitly detect subtle manipulations facial images. At same time, ResNet101 handles complex data feature extraction. Combining localized deeper, comprehensive representations our achieves enhanced performance distinguishing between manipulated authentic videos, which cannot be conducted naked or traditional methods. evaluated on diverse datasets, including FaceForensics++, CelebV1, CelebV2, demonstrating compelling accuracy results, attaining 0.9873 0.9689 0.9790 showcasing its robustness potential real-world deployment content integrity verification video forensics applications.

Язык: Английский

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Assessing the Effectiveness of Network Security Tools in Mitigating the Impact of Deepfakes AI on Public Trust in Media

Archives of Current Research International, Год журнала: 2024, Номер 24(6), С. 355 - 375

Опубликована: Июль 27, 2024

The rising threat of deepfake technology challenges public trust in media, necessitating robust countermeasures. This study proposes the Anti-DFK framework, a comprehensive strategy to mitigate spread deepfakes on major social platforms such as Instagram, Facebook, YouTube, and Twitter. framework integrates deep learning-based detection engines, digital watermarking, advanced network access controls, including URL filtering, domain reputation content-type Geo-IP blocking. Analyzing historical data, user engagement metrics, sentiment from Kaggle Datasets, employed learning models—CNNs, LSTMs, Transformer-based—to evaluate capabilities, achieving highest controlled environment accuracy 0.97. Digital watermarking techniques were tested for robustness against various attacks, with DCT method displaying significant resilience. Network controls assessed their effectiveness curtailing deepfakes, content filtering proving most effective by reducing dissemination nearly 80%. Findings indicate critical negative impact trust, underscoring need integrated approach offered framework. concludes that implementing these sophisticated tools, combined stringent can significantly enhance integrity media restore confidence.

Язык: Английский

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Beyond efficiency: Revisiting AI platforms, servitization and power relations from a critical perspective

International Journal of Production Economics, Год журнала: 2025, Номер unknown, С. 109550 - 109550

Опубликована: Янв. 1, 2025

Язык: Английский

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