Artificial Intelligence Services Research Articles

Consumer Behaviour Analysis for AI Services in the Tourism Industry

Amidst the integration of Artificial Intelligence (AI) and robotics, this study investigates consumer behaviour with a specific emphasis on the determinants that impact the adoption and purchase of AI tourism applications by tourists, thereby augmenting their perceived value. The study aims to identify the factors that impact tourists’ inclination to adopt and buy AI tourism applications, with a focus on enhancing perceived value. Using data collected from a survey of 301 visitors of different nationalities visiting Greece, this study conducts structural equation modelling to assess the relationship between technology adoption and certain factors influencing customers’ perceived value in the tourism sector, considering the Value Adoption Model (VAM). Findings indicate that suggested modifications in the VAM demonstrate that factors including Happiness, Perceived Immersion, Trust and Effort are relevant to the successful acceptance concept of paying for using AI tourism apps. The most likely outcome is the mediating role of Perceived Value in willingness to accept and pay for AI tourism apps. The study recontextualizes the VAM theory by analyzing the acceptance of AI apps in tourism and hospitality sector research. The findings are valuable to hotel directors, ICT developers, and researchers studying the difficulties of technology adoption and implementation of service management in the hospitality industry.

Integrating Artificial Intelligence and Customer Experience

Artificial intelligence (AI) has been widely adopted in the service sector to enhance the customer experience and gain a competitive advantage. However, there are a limited number of papers that focus on the relationship between AI and customer experience, and there is no clear framework to reveal how AI influences the customer experience. Therefore, this paper will address how AI affects the customer experience and develop a conceptual framework of AI applications in customer experience along the customer journey. A two-step research design is adopted in this paper. The first phase aims to identify a framework through an extensive systematic literature review of the relevant databases. The findings cover three main themes: AI experience, AI functions, and AI services. A research framework is created on the basis of the findings. This paper contributes to consumer behavior and services by integrating AI with customer experience and providing a comprehensive framework for guiding future research. The study also offers practical implications for practitioners to enhance customer experience.

РОЗРОБКА КІБЕРФІЗИЧНОЇ СИСТЕМИ ДЛЯ АВТОМАТИЗАЦІЇ ТА КЕРУВАННЯ ІНТЕРНЕТОМ РЕЧЕЙ З ВИКОРИСТАННЯМ ПЛАТФОРМИ HOME ASSISTANT

The paper presents the development of a cyber-physical system based on the HomeAssistant platform for efficient automation and control of Internet of Things (IoT) devices. The architectural features, technical implementation and prospects for the development of the system are considered, with an emphasis on the ability to integrate a wide range of sensors and IoT devices into a single network to create adaptive and intelligent solutions. The main focus is on the implementation of automation scenarios for indoor climate control, which optimise living conditions depending on the internal needs of users and external weather conditions, significantly increasing energy efficiency and overall comfort. Data storage and analysis strategies are described in detail, including the use of NAS servers for backup, the use of MariaDB for storage and InfluxDB and Grafana for analytics and visualisation, ensuring a high level of reliability and availability of information. Testing was conducted to assess the delay of notifications transmitted via Telegram and the internal network of the cyber-physical system. The obtained results confirm the high efficiency of the implemented cyber-physical system in ensuring instant delivery of notifications, which is a key aspect for rapid response to critical situations in a dynamic environment. The Home Assistant platform has been found to have extensive capabilities to support artificial intelligence services. It integrates with a variety of services such as Google Assistant, TensorFlow, DeepStack, Amazon Alexa, and allows you to easily expand its functionality with additional components and plug-ins. Using intelligent algorithms and data analysis, the system can independently make decisions on the optimal use of resources, monitor devices in accordance with changing conditions and user needs, and respond to dangerous or unpredictable situations.

Cardiac Disease Diagnosis Using K-Nearest Neighbor Algorithm: A Study on Heart Failure Clinical Records Dataset

This article introduces an approach to diagnose heart diseases utilizing the K-Nearest Neighbor algorithm and diverse correlation filters for selecting the most pertinent attributes. Results high- light that meticulous filter selection enhances survival predictions in patients with heart diseases. Employing K = 5 and correlation filter CF = 0.1, key attributes for classification were identified as anemia, high blood pressure, serum creatinine, and sex. Omitting the 'time' attribute led to information loss but was crucial to prevent biases and generalize predictions across various clinical scenarios. Utilizing these classification parameters, we designed an Android mobile application called “Heart Info System”, functioning as an artificial intelligence service. It employs the K-Nearest Neighbor algorithm with optimal parameters to evaluate the probability of survival in the progression of heart disease. The main activity of the application retrieves data from a Firebase database. While the study results show promise, the accuracy of the application may be influenced by inaccurate or incomplete input data. Nevertheless, this application has the potential to improve the early detection of heart diseases, paving the way for life-saving interventions.

ВІДПОВІДАЛЬНЕ ТА ЕТИЧНЕ ВИКОРИСТАННЯ ШТУЧНОГО ІНТЕЛЕКТУ В ДОСЛІДНИЦЬКІЙ І ПУБЛІКАЦІЙНІЙ ДІЯЛЬНОСТІ

Artificial intelligence (AI) is gradually gaining a stable place in our lives, and its use is spreading too quickly in all areas of activity, changing approaches and simplifying the solution of some tasks. AI can help at certain stages of scientific research, but it also poses risks of plagiarism, lack of academic integrity and high ethical standards. The problem of plagiarism and its prevention in the research and publication process has reached a high degree of relevance, especially with the use of AI programs and services. The article presents a comprehensive analysis of scientific sources covering the prevention of plagiarism in scientific publications, the development of AI in research culture, the observance of academic integrity in the university environment, and changes in the assessment of students' academic achievements..Using the GoogleTrends service, based on the search engine's statistical data, it was determined that recently, scientific topics related to ChatGPT have been dominating in the queries of Internet users, while the discourse related to plagiarism, academic integrity, research ethics, and responsible use of AI is not noticeably relevant, and there is an increase in related queries between "plagiarism" and AI tools. The authors substantiate the impact of the use of AI on the responsible attitude to the presentation of research results. After processing the downloaded data in Excel, a hypothesis is formulated regarding the convergence of interests and joint consideration of the problems of ethics in research and responsible use of AI. The analysed data demonstrate that the relevance of ethical and responsible use of artificial intelligence tools in writing scientific manuscripts is extremely high. The article demonstrates how digital tools such as Connected Papers, Inciteful, LitMaps, Scite.Ai, ResearchRabbit, and Semantic Scholar can conveniently visualise documents related to search terms. The article offers recommendations for researchers and editorial board members of scientific journals to promote responsible presentation of research findings in the context of the growing availability and use of AI.

Online dynamic multi-user computation offloading and resource allocation for HAP-assisted MEC: an energy efficient approach

Nowadays, the paradigm of mobile computing is evolving from a centralized cloud model towards Mobile Edge Computing (MEC). In regions without ground communication infrastructure, incorporating aerial edge computing nodes into network emerges as an efficient approach to deliver Artificial Intelligence (AI) services to Ground Devices (GDs). The computation offloading and resource allocation problem within a HAP-assisted MEC system is investigated in this paper. Our goal is to minimize the energy consumption. Considering the randomness and dynamism of the task arrival of GDs and the quality of wireless communication, stochastic optimization techniques are utilized to transform the long-term dynamic optimization problem into a deterministic optimization problem. Subsequently, the problem is further decomposed into three sub-problems which can be solved in parallel. An online Energy Efficient Dynamic Offloading (EEDO) algorithm is proposed to address these problems. Then, we conduct the theoretical performance analysis for EEDO. Finally, we carry out parameter analysis and comparative experiments, demonstrating that the EEDO algorithm can effectively reduce system energy consumption while maintaining the stability of the system.

Personality of organizational social media accounts and its relationship with characteristics of their photos: analyses of startups’ Instagram photos

BackgroundOrganizational accounts of social networking sites (SNSs) are similar to individual accounts in terms of their online behaviors. Thus, they can be investigated from the perspective of personality, as individual accounts have been in the literature. Focusing on startups’ Instagram accounts, this study aimed to investigate the characteristics of Big Five personality traits and the relationships between the traits and the characteristics of photos in organizational SNS accounts.MethodsThe personality traits of 108 startups’ accounts were assessed with an online artificial intelligence service, and a correspondence analysis was performed to identify the key dimensions where the account were distributed by their personality. Photo features were extracted at the content and pixel levels, and correlational analyses between personality traits and photo features were conducted. Moreover, predictive analyses were performed using random forest regression models.ResultsThe results indicated that personality of the accounts had high openness, agreeableness, and conscientiousness and moderate extraversion and neuroticism. In addition, the two dimensions of high vs. low in neuroticism and extraversion/openness vs. conscientiousness/agreeableness in the accounts’ distribution by their personality traits were identified. Conscientiousness was the trait most associated with photo features—in particular, with content category, pixel-color, and visual features, while agreeableness was the trait least associated with photo features. Neuroticism was mainly correlated with pixel-level features, openness was correlated mainly with pixel-color features, and extraversion was correlated mainly with facial features. The personality traits, except neuroticism, were predicted from the photo features.ConclusionsThis study applied the theoretical lens of personality, which has been mainly used to examine individuals’ behaviors, to investigate the SNS communication of startups. Moreover, it focused on the visual communication of organizational accounts, which has not been actively studied in the literature. This study has implications for expanding the realm of personality research to organizational SNS accounts.

Ensuring Compliance Integrity in AI ML Cloud Environments: The Role of Data Guardianship

Artificial intelligence (AI) has become ubiquitous across various industries, including security, healthcare, finance, and national defense. However, alongside its transformative potential, there has been a concerning rise in malicious exploitation of AI capabilities. Simultaneously, the rapid advancement of cloud computing technology has led to the emergence of cloud-based AI systems. Unfortunately, vulnerabilities inherent in cloud infrastructure also pose security risks to AI services. We recognize the critical role of maintaining the integrity of training data, as any compromise therein directly impacts the effectiveness of AI systems. In response to this challenge, we emphasize the paramount importance of preserving data integrity within AI systems. To address this need, we propose a data integrity architecture guided by the National Institute of Standards and Technology (NIST) cybersecurity framework. Leveraging blockchain technology and smart contracts presents a suitable solution for addressing integrity challenges, given their features of shared and decentralized ledgers. Smart contracts enable automated policy enforcement, facilitate continuous monitoring of data integrity, and help mitigate the risk of data tampering.

Ensuring Compliance Integrity in AI ML Cloud Environments: The Role of Data Guardianship

Artificial intelligence (AI) has become ubiquitous across various industries, including security, healthcare, finance, and national defense. However, alongside its transformative potential, there has been a concerning rise in malicious exploitation of AI capabilities. Simultaneously, the rapid advancement of cloud computing technology has led to the emergence of cloud-based AI systems. Unfortunately, vulnerabilities inherent in cloud infrastructure also pose security risks to AI services. We recognize the critical role of maintaining the integrity of training data, as any compromise therein directly impacts the effectiveness of AI systems. In response to this challenge, we emphasize the paramount importance of preserving data integrity within AI systems. To address this need, we propose a data integrity architecture guided by the National Institute of Standards and Technology (NIST) cybersecurity framework. Leveraging blockchain technology and smart contracts presents a suitable solution for addressing integrity challenges, given their features of shared and decentralized ledgers. Smart contracts enable automated policy enforcement, facilitate continuous monitoring of data integrity, and help mitigate the risk of data tampering.

Is ChatGPT-like technology going to replace commercial search engines?

Purpose This paper aims to give an overview of the history and evolution of commercial search engines. It traces the development of search engines from their early days to their current form as complex technology-powered systems that offer a wide range of features and services. Design/methodology/approach In recent years, advancements in artificial intelligence (AI) technology have led to the development of AI-powered chat services. This study explores official announcements and releases of three major search engines, Google, Bing and Baidu, of AI-powered chat services. Findings Three major players in the search engine market, Google, Microsoft and Baidu started to integrate AI chat into their search results. Google has released Bard, later upgraded to Gemini, a LaMDA-powered conversational AI service. Microsoft has launched Bing Chat, renamed later to Copilot, a GPT-powered by OpenAI search engine. The largest search engine in China, Baidu, released a similar service called Ernie. There are also new AI-based search engines, which are briefly described. Originality/value This paper discusses the strengths and weaknesses of the traditional – algorithmic powered search engines and modern search with generative AI support, and the possibilities of merging them into one service. This study stresses the types of inquiries provided to search engines, users’ habits of using search engines and the technological advantage of search engine infrastructure.

Radiology: Cardiothoracic Imaging Highlights 2023.

Radiology: Cardiothoracic Imaging publishes novel research and technical developments in cardiac, thoracic, and vascular imaging. The journal published many innovative studies during 2023 and achieved an impact factor for the first time since its inaugural issue in 2019, with an impact factor of 7.0. The current review article, led by the Radiology: Cardiothoracic Imaging trainee editorial board, highlights the most impactful articles published in the journal between November 2022 and October 2023. The review encompasses various aspects of coronary CT, photon-counting detector CT, PET/MRI, cardiac MRI, congenital heart disease, vascular imaging, thoracic imaging, artificial intelligence, and health services research. Key highlights include the potential for photon-counting detector CT to reduce contrast media volumes, utility of combined PET/MRI in the evaluation of cardiac sarcoidosis, the prognostic value of left atrial late gadolinium enhancement at MRI in predicting incident atrial fibrillation, the utility of an artificial intelligence tool to optimize detection of incidental pulmonary embolism, and standardization of medical terminology for cardiac CT. Ongoing research and future directions include evaluation of novel PET tracers for assessment of myocardial fibrosis, deployment of AI tools in clinical cardiovascular imaging workflows, and growing awareness of the need to improve environmental sustainability in imaging. Keywords: Coronary CT, Photon-counting Detector CT, PET/MRI, Cardiac MRI, Congenital Heart Disease, Vascular Imaging, Thoracic Imaging, Artificial Intelligence, Health Services Research © RSNA, 2024.

Impact of Voice AI Beauty Experience Service on User Expectations and Intention to Use Voice AI Services

Purpose: This study aimed to investigate the impact of voice artificial intelligence (AI) beauty experience services on the acceptance expectations of voice AI services and the intention to use voice AI. Methods: We collected data from hairdressing professionals in their 20s and 30s and analyzed them using Statistical Package for the Social Sciences version 22.0. The analysis methods included frequency, factor, reliability, and regression analyses. Results: The general characteristics of the survey participants were as follows: female gender, age in the 20s, college education (enrolled/graduated), work experience of <2 years, monthly salary under 1.5–2 million KRW, working hours of ≤8, working days of 2 per week, and >10 employees in the workplace. Scalp management was the most preferred voice AI service consultation topic. Validity and reliability tests revealed interest, usefulness, reliability, and ease of use as factors for voice AI beauty experience services; performance expectations and usage expectations as factors for the acceptance expectations of voice AI services; and usage intention as a factor for the intention to use voice AI services. Acceptance expectations of voice AI services and the intention to use voice AI demonstrated a positive and significant impact on voice AI beauty experience services. Conclusion: The results of this study provide foundational data for the development of the beauty industry. The beauty industry should plan and implement the development of voice AI beauty experience service programs.

Report: China’s New AI Regulations

The People’s Republic of China (PRC) has moved ahead of other jurisdictions in regulating Artificial Intelligence (AI) by enacting a set of regulations aimed at addressing risks associated with AI. This article reviews three key AI specific regulations enacted in the PRC in 2022 and 2023. Together these regulations set out comprehensive obligations on the use of generative AI and algorithmic recommendation services in the PRC. The obligations include general requirements such as to comply with the law and principles of fairness as well as to protect against incorrect political direction and violation of social morality. There are also more specific obligations to achieve those objectives. These include, ensuring the regulator has visibility of certain algorithms by requiring the filing of information about the relevant algorithms. Further there are specific obligations on service providers such as to label training data appropriately, take measures to screen illegal or harmful content, verify the identities of users for some services, protect against fake news and label artificial intelligence generated content as synthetic. The regulations also provide a suite of rights for users, including the right not to be targeted on the basis of their personal characteristics by services using AI algorithms. The obligations under these regulations are significant and it will be interesting to see how the PRC’s regulatory approach impacts the AI industry in the PRC in contrast to other jurisdictions where regulators are still looking at how to regulate AI or taking a different approach. PRC, China, Artificial Intelligence, AI Regulations

A Study on the Intention of ChatGPT Usage in the Characteristics of Generative Artificial Intelligence Services

A Study on the Intention of ChatGPT Usage in the Characteristics of Generative Artificial Intelligence Services

Personalizing Government Services through Artificial Intelligence: Opportunities and Challenges

Using artificial intelligence (AI) to customize government services brings advantages and challenges. On the one side, artificial intelligence (AI) can assist government organizations in better comprehending the needs and preferences of citizens, improving service delivery and raising citizen happiness. On the other hand, there are concerns around privacy, security, and ethical considerations related to the use of AI in government services. This article reviews the existing literature on the use of AI in personalizing government services, identifies key opportunities and challenges, and presents case studies of successful AI implementations in government services. The article concludes with recommendations for future research and practice in the area of AI and government services.

Review of the legal regulation of generative artificial intelligence services in China

Recently, the UK and EU have introduced legislation in the field of generative artificial intelligence, using different models of legal regulation. China, based on the experience of different countries, has taken an eclectic position in relation to generative artificial intelligence. The Cyberspace Administration of the People’s Republic of China has published a number of regulations to regulate generative artificial intelligence services that create content based on data sets. The article provides an overview of legal regulation in the field of generative artificial intelligence, analyzes the shortcomings and features of Chinese legislation in this area, and offers recommendations for its improvement, which can be used, among other things, to change Russian legislation in this area.

Assessing the customer adoption and perceptions for AI-driven sustainable initiatives in Indian banking sector

It is said, “Technology is a weapon and there is no escape from technology.” Many businesses are getting growth and expansion because of the usage of technology. Banking sector is one of them. It is must for banking sector to exploit the available opportunities by using technologies to penetrate the urban as well as rural areas. Usage of artificial intelligence (AI) based tools products and services is contemporary developments in banking. Banks are achieving accelerated growth and expansion. AI applications can fetch the financially left out individuals into formal and structured financial services segment utilizing their exclusive characteristics such as speed, security, cost-effectiveness and customization. Transition in banking sector is getting implemented by use of AI enabled robots, mobile banking, chatbots etc. Artificial intelligence is making banking and financial institutions powerful by utilizing the technology and redefining the way they used to operate to achieve more efficiency and growth. It is clearly observed from the available literature that banking sector is utilizing artificial intelligence to grow and follow sustainable approach. The main objective of the present research work is to understand and acknowledge the customer’s perception related to bank powered AI tools, products and services after analyzing the data collected through survey of customers through structured questionnaire. Research work aims to understand the customer review on usage of AI tools, technology and their adoption so that future strategies related to adoption of AI for banking can be erected. Research work mainly focuses on primary data by constructing the structured questionnaire. The outcome will assist bankers to apply, modify and upgrade the artificial intelligence tools to attract the population as well as to enhance customer satisfaction. The major findings of the research are the AI tools used by the banks should be user friendly and gender neutral.

The Road to a Trustworthy 6G; On the Need for a “Zero Trust 6G” Paradigm

The high-level aspects of 6G are slowly being agreed upon. It is safe to assume that 6G will bring many enhancements to 5G, including pervasive application of Artificial Intelligence (AI) and Machine Learning (ML) services. The “softwareization” trend is likely to continue and become even more prevalent. Security and trustworthiness are recognized goals for 6G. Accordingly, we predict that Zero Trust principles will become fully integrated in the 6G architecture. While necessary, this will not be sufficient. With the “softwareization” in mind, we postulate a need for increased focus on software development and deployment practices. Thus, we propose to extend the Zero Trust paradigm to encompass software development assurance and bring about a Zero Trust 6G regime. This will also be in line with the current developments for improved accountability for software and services.

Artificial Intelligence Services at Academic Libraries in Tanzania: Awareness, Adoption and Prospects

Libraries use various information management systems for organizing, packaging, and repackaging services to mention a few. The reliability of these services is highly affected by several factors including; an increase in the number of users, limited resources, decentralized learning, and the emergence of digital resources. Bearing the benefits that AI technologies offer to libraries including cost-effective operations, improved services, and timely analyses, research to investigate the awareness and prospects have been conducted in various countries. Several studies investigated the level of adopting AI technologies for effective services in academic libraries for a particular study area. The general observation from such studies indicates that the level of AI adoption and awareness varies depending on a particular country under investigation. Therefore, due to the diversification of awareness and adoption levels from various areas, it is vital to investigate it in the Tanzanian context. This study aims to investigate the level of awareness and prospects of AI adoption in Tanzanian academic libraries using a qualitative approach in which 36 librarians from 7 giant and widespread higher learning institutions (HLI) are interviewed. The findings reported in this study indicate that the level of awareness is high (68.3%) while that of adoption is low (23%). Furthermore, the findings imply that the demand and readiness for the adoption of AI among librarians is very high. Therefore, this work provides new information to librarians, HLIs’ management, and policymakers regarding the trend of artificial intelligence adoption in academic libraries. The findings reported in this paper can be used by librarians and management to align their plans toward AI adoption for effective and better service delivery.

An Exploratory Study of Artificial Intelligence and Robotic Healthcare Services in Aging Society: A Case Study of Japan

An Exploratory Study of Artificial Intelligence and Robotic Healthcare Services in Aging Society: A Case Study of Japan