The metaverse is reshaping media industries by providing immersive 3D environments that challenge traditional communication models. This study investigates virtual spaces created by three major media outlets in Portugal: RFM (radio station), TVI (television channel), and Expresso (newspaper). Using virtual ethnographic methods, this study explores how these media brands represent themselves in the metaverse, identifying their differential attributes in terms of content variety, interactive features, and monetisation opportunities. While RFM primarily seeks platform expansion, TVI and Expresso utilise the metaverse as commemorative environments to mark their anniversaries, resulting in distinct experiential approaches. RFM reinforces its identity oriented towards entertainment and youth through gamification and avatar-based engagement mechanisms, including challenges, contests, and a points-based reward system. TVI diverges most from its traditional identity, emphasising innovation with a futuristic cosmic-themed space featuring non-fungible tokens (NFTs) of iconic broadcast pieces. Expresso adopts a more conservative approach, using the metaverse to support journalistic heritage through historical storytelling and new interactive formats. The findings indicate that, despite the participatory potential of the metaverse, Portuguese media outlets are choosing to maintain editorial control over content and user interactions. Ultimately, the research shows that the metaverse is not a one-size-fits-all solution, but a diverse and evolving environment where media brands promote different immersive experiences to position themselves as innovators and leaders in rapidly evolving digital ecosystems.
This chapter explores the convergence of artificial intelligence and decentralized finance, illustrating how these two transformative forces are reshaping the digital landscape. Through the story of Yemi’s innovative mobile application connecting farmers to urban markets, the chapter highlights AI’s evolution – from early theoretical ideas and AI winters to the modern era of deep learning and open-source tools. It examines how AI enhances efficiency and decision-making across sectors such as healthcare, finance, and creative industries, while also addressing ethical challenges like bias and data privacy. The chapter further investigates the synergy between AI and blockchain, revealing potential applications in dynamic risk management, yield optimization, and decentralized governance. Actionable steps guide readers on integrating AI into Web3 projects, emphasizing continuous learning, strategic scaling, and responsible innovation for a more inclusive digital future.
Artificial Intelligence (AI), Internet of Things (IoT), and blockchain-powered chatbots are revolutionizing customer service, significantly enhancing customer satisfaction, experience, and loyalty. This research paper investigates the development and implementation of AI chatbots, emphasizing their capability to facilitate personalized and efficient customer interactions. Utilizing natural language processing (NLP) and machine learning (ML), these chatbots can comprehend and address customer inquiries in real-time, providing smooth support akin to human conversations. The paper highlights current trends, such as the use of sentiment analysis to understand customer emotions and customize responses accordingly, creating a more interactive and empathetic experience. Additionally, the deployment of predictive analytics allows chatbots to foresee customer needs and offer proactive solutions, thereby minimizing response times and boosting overall satisfaction. Moreover, the study examines how AI chatbots enhance customer loyalty by delivering consistent, round-the-clock support, making customers feel appreciated and heard. Through various industry studies, the research demonstrates the positive effects of AI chatbots on customer retention and brand reputation. The study suggests that ongoing innovation and the integration of sophisticated AI features will continue to improve the efficiency of chatbots in the customer service sector.
This study focuses on automating the formation of ephemeral teams in the search for specialized professionals for software development projects characterized by well-defined requirements. In such cases, it is crucial to identify professionals with the specific skills necessary to meet the project’s overall needs. Two primary challenges emerge in defining an effective system. The first is the need to standardize the required skills. The second pertains to the application method that candidates should use to apply for specific positions, which should also facilitate automatic evaluation. In the proposed solution, we utilize a system of two smart contracts to ensure automation, security, and transparency in interactions. Additionally, the use of standard frameworks for skills, particularly the SFIA 9 framework, facilitates the precise mapping and classification of both required and possessed skills, aligning candidate selection with project requirements. This approach streamlines the recruitment and selection of ephemeral team members, reducing recruitment time and costs while enhancing the efficiency of software project delivery.
The purpose of this chapter is to examine the ethical concerns and benefits associated with the integration of Artificial Intelligence (AI), particularly chatbots, in education. A comprehensive literature review was conducted to identify and analyze ethical considerations related to AI in education. The applicability of the web3 application in the identification and analysis of ethical concerns of AI chatbots is also explored. The findings revealed a spectrum of ethical concerns spanning fairness, transparency, privacy, autonomy, and educational inequality. Ethical concerns also include the misuse of private data, algorithmic biases, surveillance, and threats to job security. Conversely, the benefits of AI in education encompass improved learner experiences, enhanced teaching efficiency, and personalized learning opportunities. Chatbots, in particular, demonstrate potential in fostering engagement, increasing interest in subjects, and offering immediate support to students.
AI in Service Interactions
Ethics and Social Impacts of AI
Artificial Intelligence in Healthcare and Education
Personal AI assistants (e.g., Apple Intelligence, Meta AI) offer proactive recommendations that simplify everyday tasks, but their reliance on sensitive user data raises concerns about privacy and trust. To address these challenges, we introduce the Guardian of Data (GOD), a secure, privacy-preserving framework for training and evaluating AI assistants directly on-device. Unlike traditional benchmarks, the GOD model measures how well assistants can anticipate user needs-such as suggesting gifts-while protecting user data and autonomy. Functioning like an AI school, it addresses the cold start problem by simulating user queries and employing a curriculum-based approach to refine the performance of each assistant. Running within a Trusted Execution Environment (TEE), it safeguards user data while applying reinforcement and imitation learning to refine AI recommendations. A token-based incentive system encourages users to share data securely, creating a data flywheel that drives continuous improvement. Specifically, users mine with their data, and the mining rate is determined by GOD's evaluation of how well their AI assistant understands them across categories such as shopping, social interactions, productivity, trading, and Web3. By integrating privacy, personalization, and trust, the GOD model provides a scalable, responsible path for advancing personal AI assistants. For community collaboration, part of the framework is open-sourced at https://github.com/PIN-AI/God-Model.
In our pursuit of sustainable innovation for Intangible Cultural Heritage (ICH), we have adopted a methodology driven by the co-creation of human and artificial intelligence (AI). Our inclusive community, consisting of diverse stakeholders such as folk inheritors, professional choreographers, cultural center staff, square dance enthusiasts, designers, and AI engineers, forms a robust foundation for innovative practices. The community’s outputs, including dataset, experimental dance, creative short film, digital 3D works, Non-Fungible Tokens (NFTs), and an App, are multi-modal transformable. We underscore the communal utilization of resources across diverse practices and advocate for the transformation of outputs across various modalities. Importantly, each of these practices integrates AI technology into the workflow, positioning it as a pivotal enabler for fostering sustainable innovation within the domain of ICH.
AI in Service Interactions
Artificial Intelligence in Healthcare and Education
In this chapter, we provide details of key enablers of Web3 and the metaverse. It will discuss how several new technologies that are enabling the vision of Web3 and the metaverse, such as AR and VR headsets, are becoming cheaper and more powerful, leading to improved user experience. It discusses major opportunities that can result from Web3 and the metaverse. It provides a perspective on the roles of the metaverse in enhancing branding, empowering consumers, and increasing customer satisfaction with services. This chapter also highlights the various challenges that Web3 and the metaverse face. It discusses how human resources-related challenges and technical constraints can hinder the success of Web3 and the metaverse. It also offers an overview of the lack of standards and standardization to ensure interoperability within the metaverse ecosystem.
Abstract The ever-changing global educational landscape, coupled with the advancement of Web3, is seeing rapid changes in the ways pedagogical artificially intelligent conversational agents are being developed and used to advance teaching and learning in higher education. Given the rapidly evolving research landscape, there is a need to establish what the current state of the art is in terms of the pedagogical applications and technological functions of these conversational agents and to identify the key existing research gaps, and future research directions, in the field. A literature survey of the state of the art of pedagogical AI conversational agents in higher education was conducted. The resulting literature sample (n = 92) was analysed using thematic template analysis, the results of which were used to develop a conceptual framework of pedagogical conversational agents in higher education. Furthermore, a survey of the state of the art was then presented as a function of the framework. The conceptual framework proposes that pedagogical AI conversational agents can primarily be considered in terms of their pedagogical applications and their pedagogical purposes , which include pastoral , instructional and cognitive , and are further considered in terms of mode of study and intent . The technological functions of the agents are also considered in terms of embodiment (embodied/disembodied) and functional type and features . This research proposes that there are numerous opportunities for future research, such as, the use of conversational agents for enhancing assessment, reflective practice and to support more effective administration and management practice. In terms of technological functions, future research would benefit from focusing on enhancing the level of personalisation and media richness of interaction that can be achieved by AI conversational agents.
Open access
AI in Service Interactions
Online Learning and Analytics
Intelligent Tutoring Systems and Adaptive Learning
Tran Le Nguyen, Van Kien Pham, Linh Le Phuong Giao
Cryptocurrencies have become mainstream financial instruments, yet adoption remains uneven in emerging markets such as Vietnam, where rapid digitalization and regulatory uncertainty shape user behavior. Existing studies either use behavioral models that offer theoretical clarity but assume linear effects, or machine learning models that capture complexity but lack interpretability. This study combines behavioral theory with explainable artificial intelligence to examine cryptocurrency adoption in Vietnam using survey data from 1,039 respondents. Ten supervised learning algorithms were tested through repeated cross validation, and Random Forest delivered the highest accuracy. SHapley Additive exPlanations were used to interpret model outputs. Results show that trust, perceived usefulness, behavioral control, and financial literacy are key predictors, while perceived risk follows a curvilinear pattern. Interaction analysis reveals that usefulness rises with stronger behavioral control, and trust reduces risk only to a certain point. The study offers a theory informed and interpretable machine learning framework.Cryptocurrencies have become mainstream financial instruments, yet adoption remains uneven in emerging markets such as Vietnam, where rapid digitalization and regulatory uncertainty shape user behavior. Existing studies either use behavioral models that offer theoretical clarity but assume linear effects, or machine learning models that capture complexity but lack interpretability. This study combines behavioral theory with explainable artificial intelligence to examine cryptocurrency adoption in Vietnam using survey data from 1,039 respondents. Ten supervised learning algorithms were tested through repeated cross validation, and Random Forest delivered the highest accuracy. SHapley Additive exPlanations were used to interpret model outputs. Results show that trust, perceived usefulness, behavioral control, and financial literacy are key predictors, while perceived risk follows a curvilinear pattern. Interaction analysis reveals that usefulness rises with stronger behavioral control, and trust reduces risk only to a certain point. The study offers a theory informed and interpretable machine learning framework.
We examine how Web3-specific education and AI-generated investment guidance affect retail investor performance in crypto markets. In a twelve-month randomized controlled trial with 3,948 participants trading real tokens on a simulated CEX, investors were assigned to a control group, Web3 education, AI recommendations, or both. Measured by raw return, alpha, and portfolio diversification, both interventions improved performance, with the combined treatment producing the largest gains. Education effects accumulated over time, AI effects were immediate, and benefits were greatest for less experienced investors and on high-complexity news days. A portion of gains persisted after support was withdrawn, especially for education-based treatments, suggesting lasting benefits from knowledge acquisition alongside real-time decision support.
Stephan Rau, Alexander Rau, Johanna Nattenmüller, Anna Maria Fink · 7 authors
BACKGROUND: We investigated the potential of an imaging-aware GPT-4-based chatbot in providing diagnoses based on imaging descriptions of abdominal pathologies. METHODS: Utilizing zero-shot learning via the LlamaIndex framework, GPT-4 was enhanced using the 96 documents from the Radiographics Top 10 Reading List on gastrointestinal imaging, creating a gastrointestinal imaging-aware chatbot (GIA-CB). To assess its diagnostic capability, 50 cases on a variety of abdominal pathologies were created, comprising radiological findings in fluoroscopy, MRI, and CT. We compared the GIA-CB to the generic GPT-4 chatbot (g-CB) in providing the primary and 2 additional differential diagnoses, using interpretations from senior-level radiologists as ground truth. The trustworthiness of the GIA-CB was evaluated by investigating the source documents as provided by the knowledge-retrieval mechanism. Mann-Whitney U test was employed. RESULTS: The GIA-CB demonstrated a high capability to identify the most appropriate differential diagnosis in 39/50 cases (78%), significantly surpassing the g-CB in 27/50 cases (54%) (p = 0.006). Notably, the GIA-CB offered the primary differential in the top 3 differential diagnoses in 45/50 cases (90%) versus g-CB with 37/50 cases (74%) (p = 0.022) and always with appropriate explanations. The median response time was 29.8 s for GIA-CB and 15.7 s for g-CB, and the mean cost per case was $0.15 and $0.02, respectively. CONCLUSIONS: The GIA-CB not only provided an accurate diagnosis for gastrointestinal pathologies, but also direct access to source documents, providing insight into the decision-making process, a step towards trustworthy and explainable AI. Integrating context-specific data into AI models can support evidence-based clinical decision-making. RELEVANCE STATEMENT: A context-aware GPT-4 chatbot demonstrates high accuracy in providing differential diagnoses based on imaging descriptions, surpassing the generic GPT-4. It provided formulated rationale and source excerpts supporting the diagnoses, thus enhancing trustworthy decision-support. KEY POINTS: • Knowledge retrieval enhances differential diagnoses in a gastrointestinal imaging-aware chatbot (GIA-CB). • GIA-CB outperformed the generic counterpart, providing formulated rationale and source excerpts. • GIA-CB has the potential to pave the way for AI-assisted decision support systems.
Open access
Artificial Intelligence in Healthcare and Education
The present study is based on the role of NFTs and crypto currencies in unleashing the potential of metaverse. Retail which is as old as human history has gone through various paradigm shifts such as introduction of physical currency in the trade, introduction of e-commerce, digital payments, and now a new dimension—i.e., metauniverse, non-fungible tokens, and cryptocurrency—has been added to it, which is shaped up with the use of artificial intelligence. Metaverse has become a social amalgamation of virtual reality, real-world, and electronic dimension. It seems like meta universe and crypto currency are natural partners, as metaverse which is based on augmented reality; it does require a digital currency which can be used by virtual avatars at meta retail stores. So crypto currency which is a digital currency can be used in meta universe. The crypto currency is based on block chain technology which gives the avatars a sign of security and safety.
The non-fungible token (NFT) market has indeed expanded dramatically during the past few years. The way we see and interact with digital assets—such as music, artwork, collectibles, and gaming items—is being transformed by non-fungible tokens. The distinctive IDs of these tokens are based on blockchain technology and may be connected to digital or virtual assets. All recognized properties can be freely traded using NFTs, which serve as a distinct price and authenticity guarantee for digital commodities. The difficulties in this developing sector can be overcome, even though the user experience is still clumsy and regulation has not yet been harmonized. NFTs offer the perfect mix of skills to rethink how businesses interact with their customers, including through loyalty and rewards programs as well as other innovative methods. This chapter makes an effort to critically analyze the benefits and drawbacks of the global NFT ecosystem as well as the various ways that modern marketers might use NFT to improve customer engagement in the digital era.
van Trijp, Remi, Beuls, Katrien; id_orcid 0000-0003-4451-4778, Van Eecke, Paul
This paper presents a case study on how to process cooking recipes (and more generally, how-to instructions) in a way that makes it possible for a robot or artificial cooking assistant to support human chefs in the kitchen. Such AI assistants would be of great benefit to society, as they can help to sustain the autonomy of aging adults or people with a physical impairment, or they may reduce the stress in a professional kitchen. We propose a novel approach to computational recipe understanding that mimics the human sense-making process, which is narrative-based. Using an English recipe for almond crescent cookies as illustration, we show how recipes can be modelled as rich narrative structures by integrating various knowledge sources such as language processing, ontologies, and mental simulation. We show how such narrative structures can be used for (a) dealing with the challenges of recipe language, such as zero anaphora, (b) optimizing a robot's planning process, (c) measuring how well an AI system understands its current tasks, and (d) allowing recipe annotations to become language-independent.
The metaverse, a term first coined in Neal Stephenson’s 1992 science fiction novel Snow Crash , represents a collective virtual shared space, created by the convergence of virtually enhanced physical reality, augmented reality (AR) and the Internet. This digital universe allows users to interact with a computer-generated environment and other users. The concept has evolved from fictional imaginations to a significant focus of technological development, aiming to create immersive, digital worlds where people can work, play, socialise and participate in a variety of experiences that span across both the digital and physical worlds.
Since years the hackers' movement warns about it. For a huge cultural misunderstanding, we are going on trying to learn new technologies according to the rules of the old school or using them as if we could learn directly from the market. The most cannot properly use the present devices too powerful and easy, and many ideas on the future come from science fiction. It's difficult to understand that the Web is made by each of us and depends on what we put in it, more than on our visits online. Once the Internet was attended by a small vanguard capable of managing websites and blogs, gathering in communities, innovating audiovisual and media, sharing experiences and knowledge. Since several years we are billions crowded in networks much more commercial than social, where no technical skills or references to reality are required: Really “ready” for the incoming metaverse, AI and the Web3?