Analyzing media bias in defense and foreign affairs: A deep learning and eXplainable artificial intelligence approach DOI
Jungkyun Lee, Min Su Park, Eunil Park

и другие.

Telematics and Informatics, Год журнала: 2024, Номер unknown, С. 102227 - 102227

Опубликована: Дек. 1, 2024

Язык: Английский

Synthetic Data for Radioactive Waste Management: A Comparative Study for Disused Sealed Radioactive Sources in Indonesia DOI Creative Commons
Pendi Rusadi, Zico Pratama Putra,

Ajrieh Setyawan

и другие.

Nuclear Engineering and Technology, Год журнала: 2025, Номер unknown, С. 103524 - 103524

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Justifying AI regulation: Examining multi-stakeholder responses to the AI Act DOI Creative Commons
Kaisla Kajava, Ana Paula Gonzalez Torres,

Antti Rannisto

и другие.

Telematics and Informatics, Год журнала: 2025, Номер unknown, С. 102278 - 102278

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Bridging the gap: inequalities that divide those who can and cannot create sustainable outcomes with AI DOI Creative Commons
Teresa Hammerschmidt, Katharina Stolz, Oliver Posegga

и другие.

Behaviour and Information Technology, Год журнала: 2025, Номер unknown, С. 1 - 30

Опубликована: Май 9, 2025

Язык: Английский

Процитировано

0

Implications and Considerations of AI-Generative Tools for Higher Education Practices DOI
Sereyrath Em,

Sarom Mok,

Rany Sam

и другие.

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 297 - 332

Опубликована: Май 9, 2025

This chapter focuses on artificial intelligence (AI)-generative tools and their application to the higher education system, specifically instructional design processes. Digitalization advancement of AI have significantly transformed educational sector, presenting stakeholders involved in digital content with an expanded toolkit AI-driven solutions like chatbots, virtual teaching assistants, AI-generated feedback, among others. AI-generative tools, which are designed as support systems, intrinsically adopt intelligent characteristics based machine learning principles explorative methods, allowing end-user produce natural language text, video, image that is both coherent instructive. Therefore, this delves into implementation education, emphasizing tools' opportunities challenges, well outlining potential future directions.

Язык: Английский

Процитировано

0

Designing Secure and Inclusive Digital Welfare Systems DOI
Hrishikesh Desai

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 603 - 632

Опубликована: Апрель 11, 2025

The digitization of welfare systems has improved fraud detection and beneficiary authentication, yet it presents challenges in balancing deterrence accessibility. While biometric blockchain identity verification, AI-driven reduce fraudulent claims, strict authentication policies can wrongfully exclude eligible recipients, particularly marginalized populations. This chapter develops a Bayesian game-theoretic model to analyze how governments strategically optimize strictness accuracy minimize while maintaining Nash Equilibrium (BNE) framework formalizes the interactions between government agencies, legitimate fraudsters, determines optimal policy trade-offs. numerical experiment demonstrates that higher benefits justify stricter low-welfare programs, must be prioritized. Sensitivity analysis confirms small adjustments significantly impact efficiency.

Язык: Английский

Процитировано

0

Designing Secure and Inclusive Digital Welfare Systems: A Strategic Analysis of Fraud Detection and Access DOI
Hrishikesh Desai

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

An Ambiguous Relationship between Public Administration and AI DOI Creative Commons
Aleksandra Puczko

IntechOpen eBooks, Год журнала: 2024, Номер unknown

Опубликована: Авг. 7, 2024

This chapter is an attempt to present how artificial intelligence (AI) impacts public administration and the basic ethical challenges it brings this environment. The introduction shows main model of relation between AI also gives questions that will guide all argumentations. second section sets up framework for further analysis explains rudimental whole term AI. In section, fields use in are shown, including decision-making process other forms services. third dedicated issues inextricably linked with usage.

Язык: Английский

Процитировано

0

Analyzing media bias in defense and foreign affairs: A deep learning and eXplainable artificial intelligence approach DOI
Jungkyun Lee, Min Su Park, Eunil Park

и другие.

Telematics and Informatics, Год журнала: 2024, Номер unknown, С. 102227 - 102227

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

0